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Spatial and temporal geomorphic variability and coastal land use planning, Northeast Florida

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Spatial and temporal geomorphic variability and coastal land use planning, Northeast Florida
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Lannon, Heidi J. L
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English
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xvi, 203 leaves : ill. ; 29 cm.

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Area development ( jstor )
Barrier islands ( jstor )
Beaches ( jstor )
Coasts ( jstor )
Counties ( jstor )
Dunes ( jstor )
Geomorphology ( jstor )
Hurricanes ( jstor )
Land use ( jstor )
Shorelines ( jstor )
Dissertations, Academic -- Geography -- UF ( lcsh )
Geography thesis, Ph. D ( lcsh )
Brevard County ( local )
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bibliography ( marcgt )
theses ( marcgt )
non-fiction ( marcgt )

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Thesis:
Thesis (Ph. D.)--University of Florida, 2005.
Bibliography:
Includes bibliographical references.
General Note:
Printout.
General Note:
Vita.
Statement of Responsibility:
by Heidi J. L. Lannon.

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University of Florida
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University of Florida
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Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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027715315 ( ALEPH )
847495568 ( OCLC )

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SPATIAL AND TEMPORAL GEOMORPHIC VARIABILITY AND
COASTAL LAND USE PLANNING, NORTHEAST FLORIDA













By

HEIDI J. L. LANNON





















A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY

UNIVERSITY OF FLORIDA

2005






















Copyright 2005

by

Heidi J. L. Lannon





















To Evelyn and Margaret, for adventure and intellect; and to Kurt, Jeremy, and Emma, for their
patience and understanding
















ACKNOWLEDGMENTS

I would like to acknowledge the assistance of my supervisory committee chair (Dr. Mossa)

and members (Drs. Caviedes, Fik, Waylen, and Zwick). Several State of Florida and local

government officials provided invaluable assistance in data collection and interpretation: Tom

Watters and Emmett Foster, Department of Environmental Protection, Division of Beaches and

Shores; Mike Campbell, Corey Bowens, and Tim Brown, St Johns County; Mel Scott and Ann

Rembert, Brevard County; Sue Carrol and Albert Tolley, Brevard County Property Appraiser;

and the cities of Cocoa Beach, Melbourne, and Satellite Beach. I gratefully acknowledge receipt

of an O. Ruth McQuown Scholarship to fund this research, and funding provided by the

following: Department of Geography, University of Florida; College of Liberal Arts and

Sciences, University of Florida; the Florida Society of Geographers; and the City of Gainesville.

My sincere thanks go to my family and friends for their support and encouragement (especially

Kurt, Jeremy, and Emma); and to the Godmother of this endeavor, Sharon Cobb.























iv

















TABLE OF CONTENTS

page

ACKNOW LEDGM ENTS ........................................ ........................................................iv

LIST OF TABLES ........................................................................................................................viii

LIST OF FIGURES ................................................................................... .............................xiii

ABSTRACT................................ ............................................................................................. xv

1. INTRODUCTION......................................................................... ...................................... 1

Research Purpose ................................................................................... ............................ 4

2. LITERATURE REVIEW ....................................................................... ............................ 5

Use of Spatial and Temporal Data in Geomorphology .................... ........ ............. 6
Techniques and Data; GIS and Aerial Photography........................ .... ................9
Beach Profiles and Applicability................................................... .......................... 12
Population and the Coast........................................................................... ....................... 15
Contemporary Coastal Settlement Patterns............................. ... ...................... 16
Legislated Incentives for Development........................... .................... 17
Land Use Planning in Florida...................... ......... ... .....................21
Research Hypotheses...................... .. ........................................ 23

3. STUDY AREA.................................................................................... .............................26

Geomorphological Characteristics of the Florida Coast and Study Area............................. 27
Barrier Islands ........................................................ .... .................................28
S edim ents ................................................................................... .............................. 3 0
D unes.................................................................................. ......................................3 0
Tide, W ave and Longshore Drift Characteristics................... .......................... 31
Storm s................................................................................ .......................................33
W inter Storms.............................................................................. ............................ 36
Development History ............................................................................. ..........................37
Inlets ..................... ......................................................................................................40
Coastal Structures........................ .......................................... ........................ 41
Renourishment of the Shoreface ................................................ ........................42

4. M ETHODOLOGY...................................................................... .................... ..............44

Actual Geomorphology Variables................................................. 46
Beach W idth Index (BW )............................................................................................... 46



V









Maximum Dune Height (DH) and Distance to Maximum Height (DHBW) .................48
Monument to Maximum Dune Height (MDH).................................. .........................49
Long Term Shoreline Change (LT)............................................. ........................49
Coastal Structures (SW) and Renourishment Projects (RN, RND)............................56
Geographic Location (POS) and Orientation (OR)........................................................ 57
Distance (ACC), Direction (DACC) and Location (ROAD) of Access......................58
Dynamic Geomorphology Variables...................... .... ................................... 59
C om pilation of D ata.................................... .............. ...................................................61
D evelopm ent V ariables............................................................................. .................... 64
Dwelling Units (UN) and Dwelling Units per Hectare (UH)........................................ 65
Impervious Area (IMP) and Percentage Impervious Area (PIM) ..................................66
Future Land Use (FLU, FLUD, FLUC) .............................. .............................68
Application of Variables in Hypotheses............................................ 70
D ata A nalyses............................................. ................................................................. 75
Methodology Implications....................... ........... ..... .......................77

5. ANALYSES AND RESULTS............................................................. ......................79

Independent Variable Characteristics.................................................. 79
Beach W idth (BW ).................................... .......................................................79
Maximum Dune Height (DH) .............................. ................................ 80
Monument to Maximum Dune Height (MDH).................................. ............. 87
Maximum Dune Height to NGVD (DHBW)..................................................... 88
Long Term Change (LT) ................................... .... .......... ........................... 89
Access (ACC, DACC) Variables ........................................................90
Dependent Variables Characteristics................... .......... .......................91
Number of Dwelling Units (UN)............................ .... ... .....................91
Dwelling Units per Hectare (UH).........................................92
Future Land Use Variables (FLU, FLUD) ................................... .....................93
Impervious Area (IMP) and Percent Impervious Area (PIM)........................................94
Commercial (C) and Commercial Future Land Use (FLUC) Variables.......................98
Hypotheses Testing, Bivariate Statistical Analysis.......................................... ........ .......100
Beach W idth Index (BW )............................................................. .......................... 100
M aximum Dune Height (DH) ................... ...... ....................... ..................... 103
Monument to Maximum Dune Height (MDH)...................... ......................... 104
Maximum Height to NGVD (DHBW)............................................................ 106
Long Term Change (LT) ............................................................. 107
Summary of Non-parametric Results by Hypothesis ............................................... 109
M ultivariate Statistical Analyses....................................................................................... 111
Hypothesis 1: Local Geomorphology and Human Variables at each Time Interval.... 112
Hypothesis 2: The Dynamic Geomorphology and Human Variables........................115
Hypothesis 3: Temporal Lag of Geomorphic and Human Variables....................... 117
Hypothesis 4: Dependent and Independent Variables in Separate Jurisdictions.......... 118
Post Study Period D ata.................................................. .............................................. 118

6. DISCUSSION AND CONCLUSIONS............................... ............. 120

Actual Geomorphology and Human Variables .................................................... 121
Dynamic Geomorphology and Dependent Variables............................................ 122
Influence of Geomorphic Variables on Subsequent Development............................. 124
V ariation by Location....................... ..... .... .......................................... 124


vi









Inaccurate Assumptions and Hypotheses Misspecifications........................................ 125
Potential for Future Research ....................................................... 127

APPENDIX

A HURRICANES AND TROPICAL STORMS IN THE NORTHEAST FLORIDA
R E G IO N .................................................................... ............................................... 130

B DEPENDENT AND INDEPENDENT VARIABLE DETAILS....................................... 133

C SAMPLE RAW DATA FROM THE DEPARTMENT OF ENVIRONMENTAL
PR O T E C T IO N .................................................................................. ............................ 137

D USE OF AERIAL PHOTOGRAPHY AND EXCLUSION OF AREAS
UNAVAILABLE FOR DEVELOPMENT............................. .......... ............. 138

E COUNTY MONUMENT POSITION AND PROFILE DETAILS................................... 139

F BREVARD COUNTY LONG TERM CHANGE DETERMINATION ........................... 150

G DESCRIPTIVE STATISTICS, BREVARD AND ST. JOHNS COUNTY....................... 155

H NON-PARAMETRIC STATISTICS (SPEARMAN RANK) ROW WISE
CORRELATIONS, BREVARD AND ST. JOHNS COUNTY ........................................ 160

I TIME SERIES GEOMORPHIC VARIABLES...................... ......................... 177

J REGRESSION RESULTS, BREVARD AND ST. JOHNS COUNTY............................. 184

LIST O F REFEREN C ES .......................................................................... ....................... 191

BIOGRAPHICAL SKETCH ................................................ 203
























vii
















LIST OF TABLES

Table pagg

2-1. Importance of scale in spatial and temporal research.................... ........ .............. 7

2-2. Use of aerial photography in coastal geomorphology ............................................ 12

2-3. Beach-profile research; geomorphic and human variables............................ ............ 14

2-4. Coastal and growth management legislation that impacts the Florida coast....................... 19

3-1. Hurricane and tropical storm activity in the study areas...................... ............................ 34

3-2. Renourishment projects in Brevard County during 1972 to 1997 study period ..................42

3-3. Recent renourishment projects, Brevard County................................... ..................... 43

3-4. Recent renourishment projects, St. Johns County. .................................. .........................43

4-1. Geomorphic data availability by study area.............................. .....................47

4-2. Independent (geomorphic) variable details..................................................47

4-3. Profile measurement metadata, monuments 1 to 200, Brevard County...............................48

4-4. Profile measurement metadata, monuments 1 to 209, St. Johns County .............................51

4-5. Brevard County shoreline position records ................... ....................................57

4-6. Sample data changes for landward (west) relocation of monument......................................63

4-7. Sample data changes for seaward (east) relocation of monument.............................. ...64

4-8. Dependent (human/development) variable details.............................................................. 66

4-9. Land use data availability by study area............................... .... .....................68

4-10. Hypothesis la, actual geomorphic and human variable relationships.................................. 72

4-11. Hypothesis I b, actual geomorphic and future land use variable relationships. .................. 72

4-12. Hypothesis 2a, dynamic geomorphic and human variable relationships............................ 73

4-13. Hypothesis 2b, dynamic geomorphic and future land use relationships.............................74



viii









4-14. Hypothesis 3, lagged geomorphic and human variable relationships...................................75

4-15. Hypothesis 4, variable interactions by jurisdiction...................... ............................. 75

5-1. Descriptive statistics, beach width (BW )................................................. ......................81

5-2. Descriptive Statistics, maximum dune height (DH)......................... ......................... 84

5-3. Descriptive Statistics, maximum dune height (DH), Anastasia Island.................................. 84

5-4. Descriptive statistics, long-term change (LT), orientation (OR) and monument
position from north (POS), distance to access (ACC) and distance and direction
to access (D A C C ) ............................................................................. ....................... 90

5-5. Descriptive statistics, density (UH), and future land use density (FLUD).......................... 95

5-6. Descriptive statistics, percentage of impervious area (PIM) ................................................ 98

5-7. Beach width change 1972 to 1986 and development variables in Brevard County............. 100

5-8. Beach width and impervious area in St. Johns County............................................ 101

5-9. Beach width and future land use in St. Johns County............................................ 102

5-10. Beach width and future land use in St. Johns County (monuments 141 to 198)................102

5-11. Beach width factor and human variables in St. Johns ................................................. 103

5-12. Dune height and impervious area in Brevard County......................... ............... 103

5-13. Dune height and future land use density in Brevard County............................................ 103

5-14. Dune height and human variable change (1986 to 1997) in Brevard County................... 104

5-15. Distance from the monument to maximum height and development variables in
B revard C ounty.................................. ..................... ..... .... ...................... 105

5-16. Distance from the monument to maximum dune height and future land use in
B revard C ounty .................................................................................................................. 105

5-17. Distance from the monument to maximum dune height and development variables in
B revard C ounty ............................................ .......................................................... .... 105

5-18. Lagged relationship between the 1986 distance from dune height to NGVD
and adopted future land use variables in Brevard County .............................................. 107

5-19. 1999 Distance from dune height to NGVD and change in human variables in
St. Johns County...................... .. ... .. .................... .................................... 107

5-20. Long term change, development and future land use variables, Brevard County .............. 108

5-21. Long term change, development and future land use variables, St. Johns County............. 108


ix









5-22. Summary of non-parametric results by hypothesis, Brevard County............................... 109

5-23. Summary of non-parametric results by hypothesis, St. Johns County........................... 110

5-24. Summary of non-parametric results by hypothesis, Northern St. Johns County,
Ponte Vedra to Vilano Beach .......................................................... ...................... 110

5-25. Summary of non-parametric results by hypothesis, Anastasia Island, St. Johns
C ounty ........................................ ............................ ................ ................. ...........

6-1. Summary ofbivariate analyses of actual geomorphology and human variables by
jurisd ictio n ........................................... ........................................................................ 12 1

6-2. Bivariate analyses of dynamic geomorphology and human variables............................... 123

6-3. Proposed development suitability matrix.................................. .................... 128

A-I. Hurricanes and tropical storms that have impacted Brevard County.................................. 130

A-2. Hurricanes and tropical storms that have impacted St. Johns County.............................. 132

B-1. Dependent and independent variable details..................................... ...................... 133

E-l. Brevard County Monument position and profile details............................................... 139

E-2. St. Johns County Monument position and profile details.......................................... 144

F-I. Brevard County long term change determination..................... ........... ............ 150

G-l. Descriptive statistics, dependent and independent variables, Brevard County................. 155

G-2. Descriptive statistics, dependent and independent variables, St. Johns County ............... 156

G-3. Descriptive statistics, dependent and independent variables, Ponte Vedra to
St. Augustine Pass (Monument I to 122) St. Johns County............................................ 157

G-4. Descriptive statistics, dependent and independent variables, Anastasia Island
(Monuments 141-195), St. Johns County........................................ ..................... 159

H-1. Brevard County Spearman Rank analyses, Beach Width (BW) and dependent
variables at 0.05 significance.............................. .. ........ ...... ........................ 160

H-2. Brevard County Spearman Rank analyses, Dune Height (DH)) and dependent
variables at 0.05 significance.......................... ................. ....................... ...... 162

H-3. Brevard County Spearman Rank analyses, Monument to Dune Height (MDH)) and
dependent variables at 0.05 significance .................... .. ......... ...................... 163

H-4. Brevard County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW) ) and dependent variables at 0.05 significance ............................................... 164




x









H-5. St Johns County Spearman Rank analyses, Beach Width (BW)) and dependent
variables at 0.05 significance............................. ................................................ 165

H-6. St Johns County Spearman Rank analyses, Dune Height (DH) and ) and dependent
variables at 0.05 significance..................................................... .......... ............ 166

H-7. St Johns County Spearman Rank analyses, Monument to Dune Height (MDH)) and
dependent variables at 0.05 significance ............................. ................ .............. 167

H-8. St Johns County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW) ) and dependent variables at 0.05 significance ................................................ 168

H-9. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Beach Width (BW) and ) and dependent variables at 0.05
significance ............... ........................................ 169

H-10. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Dune Height (DH)) and dependent variables at 0.05
significance....................... .......... ... .. ................................................................... 170

H-11. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Monument to Dune Height (MDH)) and dependent
variables at 0.05 significance................................. .. ...... .............. .......... 171

H-12. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Maximum Dune Height to NGVD (DHBW)) at 0.05
significance.............. ........ ....... ................................... ... ........................ 172

H-13. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140
to 198), Beach Width (BW)) and dependent variables at 0.05 significance..................... 173

H-14. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Dune Height (DH)) and dependent variables at 0.05 significance........................ 174

H-15. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Monument to Dune Height (MDH)) and dependent variables at 0.05
significance................................. ....... ........ ..................................................... 175

H-16. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Maximum Dune Height to NGVD (DHBW)) and dependent variables at 0.05
significance............................ .. .................................................................. 176

J-l. Hectares of commercial development (C 3), St. Johns County, 1997.............................. 184

J-2. Future land use density (FLUDi), Brevard County, 1972................................................ 185

J-3. Future land use units (FLU 3), Brevard County, 1997....................... .................... 185

J-4. Future land use units (FLU ,3) Brevard County, 1997..................... ....................186

J-5. Potential residential density, 1979 Comprehensive plan (FLUD1) St. Johns County .........186



xi









J-6. Percent impervious area (PIM 3) Brevard County, 1997 ........................... ...................... 187

J-7. Future land use units (FLU,3) Brevard County, 1997.......................................................... 187

J-8. Future land use units (FLU 3) St. Johns County south, Monument 141 to
M onum ent 198, 1999.............................................................. ............................ 188

J-9. Future land use density (FLUDo) St. Johns County south, Monument 141 to
M onum ent 198, 1999............................................................................................... 188

J-10. Future land use density (FLUDtu) (also hypothesis Ib) Brevard County, 1972................ 89

J-l 1. Potential residential density, 1979 Comprehensive plan (FLUDI) (also
hypothesis Ib) St. Johns County.......................................................... ........................ 189

J-12. St. Future land use density (FLUDl) Johns County north, Monument I to
M onum ent 120, 1972.............................................................................................. 190









































xii
















LIST OF FIGURES

Figure page

2-1. Study areas: Brevard and St. Johns counties, Florida............................ .......................3

3-1. Coastal municipalities and geomorphic characteristics, Brevard County, Florida ................32

3-2. Coastal municipalities and geomorphic characteristics, St. Johns County, Florida...............35

3-3. Urbanization at monument 32, Brevard County. A) 1974. B) 1986.....................................39

3-4. Urbanization at monument 32, Brevard County, 1997....................... ......... ............. 40

4-1. Beach profile and geomorphic variables..................................................45

4-4. Calculation of long-term shoreline change, end point and least square fit methods............. 54

4-5. Calculation of long-term shoreline change, rate-averaging method......................................54

4-6. Determination of highway location (ROAD) variable........................... ........................60

4-7. Beach width dynamic geomorphology variable.................................... ........................ 61

4-9. Profile revision diagram, monument moved landward (to west)........................................... 62

4-10. Profile revision diagram, monument moved seaward (to east)...........................................63

4-11. Determination of total units (UN) in 9-ha sample area...................... ......... .............. 67

4-12. Determination of total impervious area (IMP) in 9-ha sample area .....................................69

4-13. Determination of future land use total units (FLU) in 9-ha sample area............................71

4-14. Determination of future land use density of units (FLUD) in 9-ha sample area...................71

5-1. St. Johns County beach width variations, 1972-1999, (BWI, BW2, BW,3)........................ 82

5-2. Brevard County beach width variations, with trend 1972-1997, (BWI, BWa, BW3).......... 83

5-3. Brevard County maximum dune height variations, 1972-1997 (DH,I, DHt, DHo)..............85

5-4. St. Johns County maximum dune height variations with trend, 1972-1999 (DH,-, DH12, DH,)86

5-5. Brevard County total units, 1972-1997, with potential units (UNo,, UNa, UN13, FLU,3).......96



xiii









5-6. St. Johns County total units, 1972 to 1999, with potential units (UNt, UN,, UNt3, FLUo,).97

6-1. Monument to maximum dune height hypotheses revision........................................... 126

D-l: Use of aerial photography and exclusion of areas unavailable for development................. 138

1-1. Brevard County Monument to highest point variations with trend, 1972-1997 (MDHu, MDH
2, M DH,) ....................... .. .. .............. ............... ...................... 178

1-2. Brevard County maximum height to NGVD with trend, 1972-1997 (DHBW,I, DHBWtI,
D H B W ) ...................... .... ................................................................... 179

1-3. Brevard County hectares of impervious area with trend, 1972-1997 (IMP,, IMP,1, IMP,1)180

1-4. St. Johns County Monument to highest point variations, 1972-1999 (MDHI, MDH MDH
3)........................................... ............ ............................... ........ ............. ............ 18 1

1-5. St. Johns County maximum height to NGVD variations, 1972-1999 (DHBW,I, DHBW,2,
DHBW t) ....................... ........... .................. ..... ....... ...................... 182

1-6. St. Johns County impervious area variations, 1972-1999 (IMP,,, IMP,, IMP,3)................ 183




































xiv
















Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy

SPATIAL AND TEMPORAL GEOMORPHIC VARIABILITY AND COASTAL
LAND USE PLANNING, NORTHEAST FLORIDA
By

Heidi J. L. Lannon

May 2005

Chair: Joann Mossa
Major Department: Geography

The research quantified the influence of local geomorphology of coastal areas

on the suitability of existing development patterns and future land use plans. Brevard

and St. Johns County (located on the east coast of Florida) were studied from 1972 to

1999. The State of Florida requirement for comprehensive plans containing future land

use designations provided base data for development of a policy-evaluation model.

Impacts of the physical characteristics of the coastline on the number and

density of dwelling units, impervious area, and development potential were evaluated at

1 km intervals. Geomorphic variables (beach width, maximum dune height, crest

position, and shoreline change) interact with development patterns and future land use

designations, and are determined by location. The net and total change are measures of

the dynamic characteristics used to evaluate temporal variations.

Results supported the anticipated relationships among wider beach width, higher

levels of impervious area, density, commercial hectares, and future land use. However,

development levels are more intense in areas with lower maximum dune heights,

suggesting that low dunes are a preferential condition for development. The position of



xv









the dune crest height was used as a proxy for the condition of the dune field. A low

distance from the crest to a fixed point on the profile represents a stable local

environment. The research showed this to be inconsistent with the data, and concludes

that movement of the crest position seaward represents dune field progradation.

Analyses at the county level showed contrasting approaches to future land use

designations and coastal development. Beach width was a determining variable in St.

Johns County, whereas dune height was more important in Brevard County. The

intensity of development is consistent with the long-term change in both jurisdictions.

This work broadens understanding of the interaction of the physical environment and

human occupation in the coastal zone. Determining relationships between the physical

parameters and types of development provides tools to help coastal managers,

geomorphologists, land use planners, and public officials to maximize access, while

minimizing unintended impacts in coastal areas.






























xvi














CHAPTER 1
INTRODUCTION

the historical dimension of geomorphology prevents it from being 'reduced to physics', and
secondly, the key role that human activities (which defy all rationality) play in modifying
the Earth's surface ensures a unique place among the sciences.
John D. Jansen, Gemorphlist, May 2002

Historically, the natural and physical features of the locale have influenced settlements.

Ancient cities were sited at river confluences, in flat areas of mountainous terrain and at strategic

defensive locations. Early coastal development began inland of passes giving settlers access to

the ocean. Although barrier islands were not the areas of choice for settlement because of their

isolation and lack of access, bridge construction allowed development of barrier islands. The

coastal zone is recognized as a dynamic environment, and extensive fluctuation of this

environment may make it inappropriate for intense development.

Development along the coastal barriers has been driven by a variety of issues. This

research investigates the level to which development is permitted and occurs in preferentially

safer, or more stable areas (with higher dunes or wider beaches). The work retrospectively

examined the interaction between natural and physical features (specifically the geomorphology)

and land use changes. The research evaluated the extent to which characteristics of the

immediate area (dune height, and beach width) influenced patterns of development. Aerial

photography and Geographic Information Systems are used in the evaluation of the dynamics of

the local environment and the impact on past, current, and future land use patterns in two counties

in coastal Florida.

The main goal was to determine the extent to which the local geomorphology of the coastal

environment shapes existing and future patterns of development. Dolan (1976, pp. 76) said that

"planners and decision-makers responsible for the management of the shoreline resources must



1






2


have a basic understanding of the nature of the inshore zone." This work explores the extent to

which the understanding of the local geomorphology has policy direction and resulting

infrastructure and development. The existing concentrations and projected influx of coastal

residents make these patterns of development an important focus for geomorphologists, land

planners and coastal managers.

Florida has the longest shoreline in the coterminous United States, and it is fringed by

barrier islands. Florida has 1,176 km of coastal barriers (U. S. Department of Interior, 1983); 741

km (63 %) was developed in 1983. The coast of the United States has 295 barriers (Reesman,

1994) and Florida has 80 barrier islands containing 189,000 hectares of land (Leatherman, 1982).

Coastal development in Florida varies from the high-rise condominium canyons of

southeast Florida, to the 1950s beach shacks of the panhandle. Traditionally coastal development

began inland of passes giving settlers access to the ocean. Barrier islands were not the areas of

choice for settlement because they were isolated and lacked access. Once bridges were built

development progressed onto and along the barrier islands. The influence of the geomorphology

of the locale is important for coastlines containing a mix of single-family homes, multi-family

condominium and small commercial areas. The coastal geomorphology and development

patterns of two coastal areas (Brevard county in central Florida and St. Johns County in northeast

Florida) are investigated during three time periods. The two coastal areas investigated are long

inhabited and historically significant.

Use of the coast has evolved over time. This brief review of ancient development and

coastal habitation provides historical background for the 27-year study period (1972 to 1999).

Lencek and Bosker (1998) chronicled the evolution of coastal use, characterizing it as the

transformation of the beach from an alien inaccessible, and hostile wilderness devoted to
conquest, commerce and exploration, and the primal customs of tribal cultures, into a
thriving, civilized, pleasure- and recreation-oriented outpost of Western life. Lencek and
Bosker, 1998, pp. xx.






3

Anthropologists have investigated prehistoric barrier island settlement in Georgia, South

Carolina and Florida (McMichael, 1977; Miller, 1980). Settlement patterns show a preference for

elevated sites on the relict Pleistocene sand ridges, particularly in areas where intertidal creeks

provided access to the back barrier lagoons and marshes in the interior (McMichael, 1977). In St.

Johns county occupation of coastal areas may have been seasonal and short-term (Miller, 1980),

and determined by the productivity of the lagoon and adjacent environments. There is no

evidence of ancient settlement, on the seaward side of barrier islands (Miller, 1980).


Georgia

St Johns
Big Bed COunty
Area
Atlantic Ocean

GulfofMexico
Brevard
County






0 100 200 Kilometers


Florida Keys




Figure 2-1. Study areas: Brevard and St. Johns counties, Florida


After World War 11, the automobile made the shoreline increasingly accessible. Until

1950, coastal development had existed in the form of exclusive resorts and coastal areas adjacent

to large metropolitan areas that were accessible by locomotive. Traveling to the coast by camper






4


afforded convenience and economy, and became so popular that trailer parks along the shore

proliferated. In 1940, there were 3,500 trailer camps in the US (Lencek and Bosker, 1998). In

1972, both Brevard and St. Johns counties had mobile home and recreational-vehicle parks;

evidence that the coast was once considered a temporary venue. Ultimately it was not the

locomotive, automobile or affluence that opened the Florida coast to year-round vacationing and

permanent dwelling; it was the advent of air conditioning use. Air conditioning was available in

the 1930s, but was not in widespread use until the mid 1950s.

Research Purpose

Pressure is increasing between those who want to live on the coast and those who think it

should be preserved in its natural state (Ullmann et al, 2000). Most studies on human and coastal

interaction focus on human influence on natural systems rather than on the geomorphology's

influence in humans. This work considers the possibility that local land use policy and human

development variables are influenced by the coastal environment, or geomorphology. This

research quantifies the way in which coastal development has been influenced by the

geomorphology along the barrier shorelines of St. Johns County in northeast Florida and Brevard

County in east central Florida, over 27 years. Four hypotheses are considered.

1. Local geomorphology at each time interval impacts human variables at the same interval

2. The dynamic geomorphology impacts human variables

3. There are temporally lagged relationships between the actual and dynamic

geomorphology variables and the human variables.

4. The dependent variables will have different relationships with the independent variables

in the two separate study areas.














CHAPTER 2
LITERATURE REVIEW

The influences of anthropogenic activities are integral to coastal geomorphology (Malone,

2003, Sherman and Bauer, 1993). However, coastal research has predominately focused on

human impacts on the coastal zone, rather than the influence of the physical environment. Human

impact has been reviewed at the macro scale (Brown and McLachlan, 2002; Clark, 1976; Clark,

1997; Phillips, 1988; Phillips, 1997; Viles and Goudie, 2003; Viles and Spencer, 1995) and micro

levels (Conway and Nordstrom, 2003; Gares, 1987; Nordstrom, 1994; Nordstrom et al., 2002;

Sherman and Bauer, 1993). Nordstrom (1994) recognizes human activity as an integral part of

the coastal system. He discusses the lack of literature specific to human altered coasts. "Natural

landscapes are a myth, that human agency is not an intrusion in the coastal environment so much

as it is now part of the coastal environment." (Nordstrom, 1994, pp. 508) Others contend that the

natural system must be understood before human influences can be evaluated (Sherman and

Bauer, 1993). The interaction between physical and human geography has been also been

described as a form of landscape geography, bridging the systematic and regional geography

approaches (Lundberg and Handegard, 1996).

The natural or physical environment is influenced by, and also influences human factors.

This research evaluated the weight of the physical environment as a factor affecting human

variables. Lundberg and Handegard (1996) investigated coastal agricultural uses to evaluate how

humans have adapted to the use of the environment over time. Adjacent agricultural practices

may be dissimilar in identical environmental conditions, suggesting that a variety of feedback

loops influence the spatial patterns. Lundberg and Handegard (1996) state that the "landscape is

a reflection of environmental, and social conditions and processes in society" (pp. 168). In New

Zealand, geomorphology has been used to determine the potential uses of areas (Hails, 1977).


5






6


Areas were divided into those suitable for high-intensity activity and areas that should be

maintained in a natural state. Similarly, North Carolina has used zoning restrictions for hazard-

mitigation purposes (Bush et al., 1999). The geomorphology provided the basis of land use

restrictions that were enforced through zoning controls.

Use of Spatial and Temporal Data in Geomorphology

The field of geomorphology was originally characterized by landscape evaluation using

fieldwork. Later, modeling processes and laboratory simulations became important (Hooke,

1999). For each stage of geomorphological research the importance of the data has been

paramount. Perfect data would be spatially and temporally precise, accurate, readily available,

and calibrated. The shortfalls of data must be acknowledged and accommodated in successful

research. There are four categories of data; in-situ, remotely sensed, secondary data, and

simulated data (Lucas, 1996). This research used predominately secondary data collected by the

State of Florida, remote data (aerial photography) and simulated data collected from county

comprehensive plans. Field research or in-situ investigations augment the data. These data are

combined and analyzed using Geographic Information Systems (GIS). Geomorphological

research has progressed from simple one-dimensional analyses to the complex spatial capabilities

afforded by digital media (Vitek at al., 1996). The research considered spatial detail alongshore

and temporal scales by decade. Geomorphological research occurs at micro to macro scales

(Table 2-1) and temporal periods of days to decades.

The evaluation of time in geomorphic analyses in crucial to the validity of any conclusions.

As Schumm (1992, pp. 39) states," the period of record must be adequate to describe the

phenomena of concern." The length of time over which phenomena should be studied is not a

simple deduction (Pilkey, 2003). Physical processes occur over a variety of time scales, and the

time period used must be adequate to describe the process (Viles and Goudie, 2003). The

temporal analysis of coastal evolution cannot be neatly divided into short and long-term

components. Emphasis on large scale coastal behavior (LSCB) (Carter and Woodroffe, 1994is






7


needed to determine the extent of coastal evolution. Responses of the shorelines of the world

would be simpler to evaluate if there were some "observable and straightforward explanation for

most changes" (Carter and Woodroffe, 1994, pp. 2).

Table 2-1. Importance of scale in spatial and temporal research
Macro scale Brown and McLachlan, 2002; Clark, 1976; Clark,
1997; Phillips, 1988; Phillips, 1997; Viles and Goudie,
2003; Viles and Spencer, 1995.
Micro scale Abumere, 1980; Conway and Nordstrom, 2003; Gares,
1987; Nordstrom et al., 1999; Nordstrom et al., 2002;
Sherman and Bauer, 1993.
Long Term Carter, 1988; Dean, 1999; Dolan et al., 1991; Foster,
1992; Foster and Savage, 1989; Nordstrom, 1996;
Pilkey, 2003; Schumm, 1991; Van Der Wal, 2004;
Viles and Goudie, 2003.
More immediate Bymes et al., 1995; Dolan et al., 1991; Gares, 1990;
Haggett et al., 1977; Phillips, 1997; Phillips, 2005;
Schwartz, 1971; Shideler and Smith, 1984.
Multiple Causality Butler And Walsh, 1998; Phillips, 2005; Phillips,
1997; Schwartz, 1971; Walsh et al., 1998.

Caution is important in extrapolating results before determining landscape behavior over

time, because the landform may not be responding to a single input into the system. The

importance of time in evaluating coastal systems cannot be overstated. In evaluating of coastal

variables, selecting the wrong study period for the process can cause totally inaccurate results

(Dean, 1999; Dolan et al., 1991; Foster, 1992; Foster and Savage, 1989). In Australia initial 4-

week study of longshore drift (Schumm, 1992) produced results that were inconsistent with the

local coastal features. By extending the study period, longshore drift in the opposite direction

was also noted. Similarly Nordstrom (1994) notes that the historically multidirectional drift

pattern along the coastline of New Jersey has been rendered unidirectional by the impacts of

human development. Those studying the New Jersey coastline over short periods of time (not

considering the pre-1935 shoreline) conclude that the drift system is to the south only, being

unaware that the choice of time period influences the conclusions. Evaluation of the impacts and

longevity of renourished shorelines requires extensive temporal investigation. Van Der Wal






8


(2004) used a 15-year horizon over which he evaluated the impact of renourishment on beach

profiles of the Dutch coast.

This research considered the time period of accelerated coastal development in Florida. In

St. Johns County access was not available to Anastasia Island until the 1950s (Olsen, 1974). The

proposed period from 1972 to 1999 represents the timeframe for much of the development in the

two counties (Figure 2-1) (Bodge and Savage, 1989; Brevard County, 1989; Long, 1968; St.

Johns County, 1979, 1993, 2002; Toth, 1988). Impacts of physical characteristics on

development can only be determined for time in which development had occurred. Beginning in

the 1970s ensures that the baseline development already present was low density. Change in those

areas, and the development of formerly vacant areas, will illustrate the impacts of the physical

environment. Similarly the legislation requiring state-coordinated planning was initiated in 1972,

and local comprehensive plans was required in 1975. This importance of land use controls on

settlement patterns along the coast is discussed later in this section.

The importance of time lag should also be mentioned, particularly because response in the

coastal zone is not necessarily linear. Any analysis of the coast should consider lagged effects.

In longshore drift, the impact ofjetties, for example, is not immediate (Nordstrom, 1996; U. S.

Army Corps of Engineers, 1993). A cyclical pattern of shoreline positions over time, analyzed

using a linear regression, may appear stable (Nordstrom, 1994). The use of the dynamic

geomorphology variables, described in the methodology will address these issues.

Few processes or landforms in geomorphology are isolated in space. It is important to

consider each research area part of a complex spatial system. Findings from one scale cannot

necessarily be extrapolated, because with increased scale, there is increased complexity in the

system. Conclusions about specific landforms cannot be extended to others that appear similar,

but vary in size (Phillips, 1988; Phillips, 1997). Haggett and others (1977) describe the scales of

geographic inquiry and suggest caution when inferring characteristics from one level to another.

This research used the same scale, spacing, and frequency of data for both study areas.






9


Scale of investigation is as important as time period when analyzing of the coastal

environment. A small portion of a barrier island cannot be considered in isolation, any more than

a single barrier island can be considered without those adjacent to it (Schwartz, 1971; Shideler

and Smith 1984). Davis (1997) showed varied in shoreline dynamics along the Gulf of Mexico

coast. If only a small portion was considered the extrapolated results would have been erroneous.

Dolan and others (1991) showed the need to consider erosion rates when selecting an area. Gares

(1990) considered the whole coast of New Jersey, rather than a small area. This research was

used to mitigated conclusions about specific areas that may have been generalized or too specific.

Many of the geomorphic data used in this research are secondary, collected by the State of

Florida, and the importance of field evaluation cannot be underestimated (Lucas 1996). Aerial

photography and field verification are crucial to understanding local dynamics not reflected in

mere data analyses (Foster and Savage, 1989). The use of secondary data necessitates vigilance.

Users must investigate the suitability of the data for the interpretations made. In this research the

secondary data are considered robust because the organization that compiles the data (the Florida

Department of Community Affairs) is constant over time. Variation in data by local jurisdiction

is one factor affecting local responses to geomorphology; this variation may be an appealing

dynamic of the research.

Techniques and Data; GIS and Aerial Photography

Geographic Information Systems (GIS) are "tools that enhance and broaden the

opportunities of geomorphology and together with field studies offer a robust synergistic design

to explore a host of research questions associated with landscape characterization and the linkage

of scale, pattern and process" (Butler and Walsh, 1998, pp. 179.) GIS can be used to assess

landscape units spatially, to evaluate geomorphic patterns and spatial interactions, and to illustrate

spatial relationships among variables (Kriesel and Harvard, 2001). GIS coverages incorporating

remotely sensed and aerial data have expanded the geographic capacity for analyses in both

spatial and temporal contexts. Lucas (1996) describes coastal data as being "four dimensional:"






10


with components of length, width, height/depth and time. GIS has expanded the potential for

evaluating "landscape conditions through the interrelationship of scale, pattern and process"

(Walsh et al., 1998, pp. 183). However, GIS techniques should not be used in isolation without

the integration of fieldwork (Walsh et al., 1998). GIS has traditionally been used to illustrate

spatial relationships. This research used temporal and spatial data to analyze relationships among

the planned and built environment and the geomorphic characteristics of the coast.

An important aspect of GIS in geomorphology is the ability to show topography. The

coastal domain of Florida, however, has no extreme (elevations ranging from 0 to 10 meters). El-

Raey and Nasr (1996) also note the difficulty of vertical or "z "scale in low-lying coastal areas

and the difficulty of interpolating topography information for use on coastal scales with low "z"

values. GIS was used to evaluate the relationship of the human variables, land-cover, and

topography. El-Raey and Nasr (1996) used an average elevation for each land-cover category in

an attempt to quantify losses due to sea-level rise. In this research dune height represents the

topographic measure. GIS have practical applications in addition to its importance in coastal

research. In New Jersey investment in GIS were crucial to the coordination of coastal zone

management (Neuman, 1999). The State Planning Commission was funded to use GIS in a

multi-agency level dialogue, with input from state and local agencies, citizens and private

interests.

A crucial aspect of using GIS in spatial and temporal research is its ability to use a wide

variety of data types, such as maps, aerial, or remotely sensed images, survey data, and land use

coverages. This research has some limitations for GIS applications. The research data comprise

points and lines in vector form. Each data transect is separate in space. Interpolation of the

characteristics of the shore-normal profile from one area to the next is possible, using one of the

many methods of interpolation. The combination of types of planform and profile data allow the

user to produce a three-dimensional representation of the shoreline. Coastal research could






11


produce cell coverages suitable for raster manipulation. However, the spacing of these data

(more than 300m apart) is not conducive to interpolation.

Information sources for investigating coastal changes in planform include navigational

maps, USGS 1:24,000 topographic maps, NOS "t" sheets, aerial photography, and remotely

sensed images. Spatially using aerial photography is one way to evaluate the coast (Table 2-2).

However, caution is needed when interpreting data. Theiler and Danforth (1994) give a

comprehensive methodology for preparing a control network, resolving distortions and

inaccuracies, before inputting the information into a mapping program. Other considerations in

evaluating of data accuracy are map shrinkage, defects, projection, and age (Crowell et al., 1999).

The age of the photography, tilt, relief displacement, radial lens distortion, position of the tidal

datum, fiduciary points (known points on overlapping photographs), photograph overlap and

control points available for triangulation, film buckling, humidity, and type of paper, must all be

considered in assessing the accuracy of the aerial photography (Theiler and Danforth, 1994).

GIS has increasingly been used in conjunction with aerial photography in coastal areas.

The scales of coverages and extent of coastline investigated vary from individual dune systems to

broad analyses of entire coastal reaches. Bush and others (1999) consider aerial photography

suitable for coastal evaluation at the regional, local and site-specific scale. El-Raey and Nasr

(1996) used 1:25,000 scale photography for regional evaluations and 1:2000 photographs on a

local scale to investigate the impacts of sea-level rise on land use, population and land value

along the north coast of Egypt. Stanczuk (1975) used aerial photography with profile data to

evaluate the impacts of development of coastal characteristics.

Aerial photography has been used in coastal areas to show changes over time (Carter and

Woodroffe, 1994; Hails, 1977). Nordstrom evaluated the effects of engineering structures on four

inlets in New Jersey, and determined the planform changes over time. He found that a formerly

unidirectional drift system had been altered, and that shoreline mobility had been reduced after

1935. Two areas of rapidly expanding urbanization along the Australian coast were evaluated to






12


determine the sequence of development between 1947 and 1994 (Essex and Brown, 1997).

Originally low-density development spread along the coastal strip (suburban style) in the 1980s.

Photography was combined with planning documentation and field evaluations.

Table 2-2. Use of aerial photography in coastal geomorphology
Geomorphic changes Crowell et al., 1999; Davis, 1997; Dean and
Malakar, 1999; Dolan et al., 1991; Kaufman and
Pilkey, 1983; Stanczuk, 1975; Theiler and
Danforth, 1992.
Human impacts Carter and Woodroffe, 1994; Hails, 1977;
Nordstrom, 1996; Essex and Brown, 1997; Dean
and Donohue, 1998
Measurement of EI-Raey and Nasr, 1996; Essex and Brown, 1997;
urbanization Hart, 2000;Vernberg et al., 1996.

Beach Profiles and Applicability

Beach profile data may be used for various purposes, from descriptive (Stone et al., 1985;

Stone and Salmon, 1988) to highly quantitative analyses (Chiu, 1986; Guan-Hong et al., 1995;

Hesp, 1988). The profile shape and form indicates the stability of the coastal area and its potential

suitability for development. Combining aerial photography and beach profiles provides a

valuable combination ofcross-sectional and planform perspectives (Al Bakri, 1996; Stanczuk,

1975; Wright, 1991). The stability of the beach profile depends on wave and wind conditions,

sediment size and beach slope, in the short term; and depends on sea level, sediment supply,

littoral transport, and storm frequency in the long term (Reesman, 1994). Table 2-3 shows the

geomorphic and human variables evaluated as components of beach profile characteristics.

Beach profile data have been used to evaluate the impacts of human changes to the coast at

various scales. Wright's (1991) work at the large scale (spanning the states of New Jersey, North

Carolina and South Carolina) measured the dry beach width from surveyed profiles and used it as

a proxy for the portion of the beach that is continuously available for recreational use. It

quantified the value society puts on the recreational amenity, and used dry beach width to

compare the impacts of stabilized shorelines. He determined that the dry beach width was






13


consistently narrower where the shore was stabilized, except where groins and renourishment

occurred.

Stanczuk (1975), Al Bakri (1996), Bush and others (1999), and Rahn (2001) evaluated the

influence of development on beach profile changes at smaller scales. Stanczuk (1975) evaluated

36 profiles over a 4-month period on Bogue Banks, North Carolina. He noted that on a small

scale developed areas updrift prevented sediment movement, caused changes in profile width and

gradient, and prevented the profile from recovering from the impacts of seasonal changes and

storms. Bush and others (1999) used beach width, slope, and elevation derived from profile data

to develop qualitative geoindicators. These indicators were expanded for use along the North

Carolina coast for risk assessment and hazard mitigation. Rahn (2001) compared the beach

profiles in developed and undeveloped sites in two areas of the Florida panhandle.

The major shortcomings of beach profile data are the spatial and temporal frequency of

data collection. Temporal frequency is a concern because of the dynamic nature of the coast.

Profile data give specific information only for the time period during which they were collected.

The data provide no indication of historical or seasonal changes, nor can they be used to predict

the future (Stanczuk, 1975). The beach profiles Stanczuk's study are a snapshot of the beach

morphology at a specific time. This is a problem because beach profiles are extremely dynamic

and sensitive to storm or seasonal conditions. Similarly the coarse scale alongshore will not

reflect a continuous surface. The data cannot be used to interpolation shore-normal topography at

this scale. The individual profiles are used in conjunction with development variables recorded in

the adjacent sample areas at the transect. Using profile data over the study period to determine

dynamic geomorphology variables reduces the influence of outlying values. The Department of

Environmental Protection conducts data collection for evaluating beach conditions during the fall

and spring, at times when storm activity has been minimal.

Seasonal variations reflected in the profile data taken at different times of year may also

lead to inconsistencies or errors. Wright (1991) used dry-beach width during summer, to






14


minimize the effect of storm influences. Seasonal variations include profile shape, which may

vary significantly in winter months when high wave energy may cause the development of

longshore bars with sediment that would otherwise be part of the terrestrial profile (Foster and

Savage, 1989). The prevailing philosophy is that winter waves denude (and summer waves

restore) the beach profile in a natural system (Carter, 1988; Guan-Hong et al., 1995). Al Bakri

(1996) analyzed beach profiles in Kuwait and noted the tendency for the profile volume to

increase in summer and decrease in winter. The volume of material in the profile is not used as a

variable in this research. It was considered that the volume varies seasonally on shorter

timeframes than data by decade can reflect. The profile data timescales were considered too

coarse to provide a useful measure of volume. Additionally, Rahn (2001) found no relationships

between subaerial volume variations in developed or undeveloped areas.

Table 2-3. Beach-profile research; geomorphic and human variables
Variable Study

Beach width Clark, 1999; Rahn, 2001; Shideler and Smith, 1984;
Stanczuk, 1975; Wright, 1991.
Dune height Gares, 1987; Nordstrom et al., 1990; Rahn, 2001;
Shideler and Smith, 1984; Stanczuk, 1975.
Profile gradient Allen, 1991: Meesenburg, 1996.
Position of dune crest Allen, 1991; Gares, 1987; Olivier and Garland, 3003;
Rahn, 2001; Stanczuk, 1975.
Profile volume Al Bakri, 1996; Allen, 1991; Gares, 1987; Rahn, 2001.
Barrier island width Stanczuk, 1975; Stone et al., 1985; Stone and Salmon,
1988.
Impacts of erosion and flooding Balsillie, 1985; Clark, 1999; Dean and Malakar, 1999;
Fenster and Dolan, 1996; Gares, 1990.
Seasonality Dolan, 1976; Stanczuk, 1975.
Storms Webb et al., 1997; Meesenburg, 1996.
Long-term shoreline change Bodge, 1992; Foster, 1992; Foster, 2002; Foster et al.,
1989; Foster at al., 2000; Olsen, 2003.
Human data Bellomo et al., 1999; Finkl and Charlier, 2003; Foster,
1992; Foster et al., 1989;
Coastal Development Al Bakri, 1996; Bush et al., 1999; Rahn, 2001; Smith,
1994; Stanczuk, 1975.
Foredune grading Hails, 1977.
Sand mining Carter, 1988; Davis and Barnard, 2000; Hails, 1977.
Structures Collier et al., 1977
Vehicular traffic, trampling, Carter, 1988; Viles and Spencer, 1995.
vegetation, and fences






15


Dolan (1976) considers seasonal beach profile variations are of minor significance because

the change is confined to the shoreface. Unless significant winter storms breach the primary dune,

the area of wave runup is the dynamic portion of the profile, constrained by the first topographic

berm structure. During high-energy storms, erosion will cause the beach width to increase

providing a larger area over which wave energy can dissipate. A barrier island with no

obstructions to sediment transference can withstand periodic storms (Meesenburg, 1996). Another

shortcoming of profile data is that the profile may not extend far enough to incorporate all aspects

of the sediment budget. Sediment loss from aeolian forces that extend inland beyond the profile

will not be accounted for. Similarly sediment that is transported beyond the beach face offshore

may be considered lost to the system.

Population and the Coast

Having established the physical environment in which this research occurs, it is important

to review the policy direction and ultimate development of the human environment in coastal

reaches. Fifty percent of the world's population lives within 1 kilometer of the coast (Goldberg,

1994), 75 percent of the United States population lives within one hour's drive of the coast and in

Florida 80 percent of the population lives in the coastal counties (Finkl, 1996). Coastal counties

comprise 20 percent of the nation's land area, contain almost half the population and by 2010 will

contain more than 127 million people (H. John Heinz Center, 2000). Lins (1980) determined that

even in the mid 1970's 37 percent of the Atlantic and Gulf coasts of the Untied States contained

development and by 1983 741 kilometers or approximately 63 percent of the Florida coastline

was developed (U. S. Department of Interior, 1983).

Patterns of development are measures of spatial arrangement. Locations with the same

population density may not have the same spatial arrangement of land uses (Vemberg et al.,

1996). The distinction between the size, nature, and arrangement of settlements and the specific

pattern of the community is important. The location of a community in relation to the

environment, and on a smaller level, the specific layout of a community, represents spatial






16


patterns at contrasting scales. This work concentrates on the influence of geomorphology on the

"macrosettlement" or location within the confines of the physical environment.

In coastal areas settlement patterns do not necessarily conform to established settlement

norms. The physical environment and transportation access supplies a set of limitations or

controls. Coastal development of barrier beaches reflects a recognized style that is limited by

topography (Kostof, 1991). Montreal has a linear pattern determined by the location of the river

and Reps (1965, pp. 68) states "the general form of this city a narrow linear pattern was

strongly influenced by topography." Coastal development is similarly influenced by topography

and patterns also conform to the linear pattern recognized by Reps.

Contemporary Coastal Settlement Patterns

Spatial patterns are particularly relevant in coastal areas because although population

densities may not be increasing, urbanization of land is occurring (Davidson-Amott and

Kreutzwiser, 1985). The transition from industrial to post-industrial cities, and from modernism

to post-modernism has caused urban form to decentralize. Polynucleated areas with amorphous

suburbs have eclipsed the former metropolitan concentrations driven by industrial growth.

Distinct patterns oftourist-driven growth have been identified (Meyer-Arendt, 1990)

Verberg and others (1996) identify the predominant pattern of coastal development in the

southeastern United States to be urban concentrations with adjacent low-density areas. The

population density of an area many not change even when the settlement patterns vary. Over the

last 30 years the number of metropolitan areas nationally has increased, while the average density

has decreased (Verberg et al., 1996). A study of coastal counties in the southeastern United

States using aerial photography and satellite images showed that sparsely populated counties were

becoming populated with low density residential developments (Verberg et al., 1996). Thus,

more land is consumed and the urban area expands without a change in the population density.

In coastal areas, the segments of population that are expanding most rapidly are whites and the

elderly (Vernberg et al., 1996). Vernberg states "low-density residential use along the shoreline






17


is occurring as small family units of older people having large lots and second home commuters

from the nearby metropolitan areas" (pp. 11). Similarly, along the north coast of new South

Wales, Australia, 35 percent of second homebuyers purchased homes for retirement destinations

(Essex and Brown, 1997).

The economic prosperity of the late 1990's and the new century has contributed to

residential development and the second home market in coastal areas (Overberg, 2000).

However, research in Australia indicates that the economy may not be the most important factor

in coastal location. Walmsley and others (1998) found that "pull" factors, such as the physical

environment, climate and lifestyle influence development more than "push" factors, such as

employment prospects and salaries. Polling 150 households that moved to the north coast of New

South Wales, he concluded that migrants to the coast were influenced by image and quality of

life, rather than employment opportunities, pay and working conditions.

Legislated Incentives for Development

Development of Florida's barrier islands has been as a result of the interaction of many

forces. A measure of the importance of the physical amenity of the coastal zone, available

access, local restrictions or incentives is captured in this research, while Federal and State tax

advantages are not. In this research the influence of politics in the study area, or at county level

and the State and National level are also a component of what is reflected in the settlement

patterns. The influence of legislation as an incentive or disincentive for development on the coast

is likely to be equally if not more important, than the physical characteristics.

Several provisions in the Federal tax code have influenced coastal residential development

(Beatley et al, 1994). Deductions for home mortgages on personal income tax returns were

intended to assist home ownership. Second home mortgages can also be deducted providing

additional tax incentives for those affluent enough to afford them. The use of residences for a

commercial enterprise, such as rental property is also subsidized by the tax code (Thom, 2004).

Losses incurred for lack of rental income, or deductions to improve the property are permitted.






18


Individuals can therefore purchase or construct residences, speculate on rental income, and use

them as tax deductions if they are unsuccessful. Revisions to the federal tax code permitting the

one-time exemption of capital gains for homeowners over 55 may have also encouraged retirees

to relocate to coastal areas (Vemberg et al., 1996).

The National Flood Insurance Program was enacted by the National Flood Insurance Act

(Table 2-4) of 1968 (Von der Osten, 1993) provides flood insurance to property owners in areas

where the local government has adopted and enforces floodplain management standards to reduce

potential flood damage (Bellomo et al., 1999). Local governments may use zoning restrictions,

subdivision regulations, building code compliance and minimum elevations to mitigate potential

flood damage. Although it has been argued that the restrictions required to be adopted by local

governments to participate in the NFIP increase the cost of development in the coastal zone, the

availability of flood insurance serves to enable development that would otherwise be too costly to

insure (Von der Osten, 1993). In Florida, insurance under the National Flood Insurance Program

is a requirement for eligibility to request public disaster assistance funds (South Florida Regional

Planning Council, 1989)

The Coastal Construction Control Line (CCCL) is set to reduce the potential for structural

damage and beach erosion (Von der Osten, 1993). The CCCL are adopted on a county-by-county

basis, and state permits are required from the Florida Department of Environmental Protection

(DEP) for construction or excavation seaward of the line. The line is calculated by elevation in

relation to storm and hurricane tides, predicted maximum wave up rush, contours (including

offshore), vegetation, erosion trends, dune line, and existing development. There are also

exemptions to permits, most relevant to this research are the structures completed before the

establishment of the first line in 1972 (Von der Osten, 1993). Any changes to structures must be

contained within the original footprint. Structures that are justified to DEP and seaward of the

CCCL must be designed to withstand a 100-year storm event, wind velocity of 95.5 km/hr.

Structures must also be elevated above the calculated breaking wave crests or wave uprush of a






19


100-year storm and anchored to a pile foundation. Excavation seaward of the CCCL is not

recommended but may be permitted.

Table 2-4. Coastal and growth management legislation that impacts the Florida coast
Year Name Legislation
1968 (Federal) The National Flood Insurance Insures structures from hazards with
Act backing of the Federal Government
1972 (State) The Coastal Construction Established to reduce the potential for
Control Line (CCCL) structural damage and beach erosion
1972 (State) State Comprehensive First Statewide growth management
Planning Act legislation
1972 (Federal) Coastal Zone Management Establishment of national coastal
Act management coordination and
funding for State coastal program
1974 (Federal) The Disaster Relief Act Federal disaster assistance
administered by the Federal
Emergency Management Agency.
1978 (State) The Florida Coastal Zone Resolution of conflicts between
Management Act agencies concerning coastal land and
water
1982 (Federal) The Coastal Barrier Prohibits federal assistance on
Resources Act (CBRA) designated undeveloped coastal
barriers that comprise the Coastal
Barrier Resource System
1985 (State) The Florida Coastal Zone Building regulations in coastal areas.
Protection Act Structures must be designed to
withstand 100-year storm wind
speeds and erosion impacts.
1985 (State) Local Government Comp. Requires Florida cities and counties to
Planning and Land develop comprehensive plans and
Development Regulation Act land development regulations
1991 (State) Florida Beach and Shore Requires all construction,
Preservation Act reconstruction or shoreline protection
to have a coastal construction permit
from DEP with a 15.25m setback line
from mean high water, the average
high of high waters over 18 years.
1999 (State) The Coastal Construction Authority of individual counties to
Control Line (CCCL) permit structures and erosion controls
Sources: Bellomo et al., 1999; South Florida Regional Planning Council, 1989; Vernberg et al.,
1996; Von der Osten, 1993

As noted in Table 2-4 the Coastal Barrier Resources Act (CBRA) prohibits federal

assistance on designated undeveloped coastal barriers that comprise the Coastal Barrier Resource

System. Private property rights are still in effect and development can occur, but without Federal

subsidies for transportation networks, and flood insurance. Existing jetties and channels, road






20


repair and the operation, maintenance and construction of military facilities are exempted. In

Southern Brevard County between monuments 157 and 164 there is a CBRA designated area.

Coastal management at all levels is complicated by the conflicting mandates of the various

agencies. Nationally the Corps of Engineers permits dredge and fill and coastal structures, while

the Environmental Protection Agency protects wetlands. Neuman (1999) illustrates the

complications using an example of barrier island bridge construction. The construction may be

warranted by traffic counts by the Department of Transportation, encouraged by tourism goals of

the Department of Commerce and the local jurisdiction, and permitted for construction by the

Corps of Engineers. The Department of Environmental Protection may deny the project because

of endangered species protection. States have a variety of ways of controlling the coastal zone,

while remaining consistent with the Coastal Zone Management Act. North Carolina and

California have Commissions authorized to enact coastal legislation. New Jersey manages the

coast through the executive branch and uses a process of "cross acceptance" (Neuman, 1999).

Coastal zone management is integrated so that planners, politicians, academics, and citizens

develop policy collaboratively. Regional programs, such as for the Chesapeake Bay are also used

to manage specific resources.

In Florida, as in many other states and at the Federal level, coastal zone management is

decentralized. In 1992 the Department of Community Affairs, created a Coastal Zone

Management Office within the Secretary's Office. This was to address "the "fringe" nature of

coastal management in the realm of state government" (Berd-Cohen et al., 1993, pp. 41).

Previously the Florida Coastal Management Program had been located in Department of

Environmental Protection (Bernd-Cohen et al., 1993). The State Department of Community

Affairs is the Department charged with land use and resource planning and enforcement of the

State's growth management plan. The move realigned coastal management in Florida with the

policy, land use and development activities, rather than environmental and data collection

functions of the Department of Environmental Protection. In this way the enforcement of growth






21


management could be extended to coastal issues. Coordination ofmulti-jurisdictional coastal

issues, or the designation under the Areas of Critical State Concern legislation (Tin, 1976) can be

facilitated at the state level.

Land use authority in Florida is delegated to the County and municipal level and as a

consequence interactions between development and the coast occur at the local level. In this way

the use of county jurisdictional boundaries makes sense for the human variables. "Although

much federal and state legislation has been enacted to assist the management and regulation of

coastal development and redevelopment, local government regulatory tools and programs provide

the most significant opportunities..." (South Florida Regional Planning Council, 1989, pp. 65).

In Florida, homestead exemption, which exempts the first $25,000 of value from ad

valorem taxation, is available for primary residences. In rare cases, such as mobile homes on

small lots with taxable values of less than $25,000, there is no assessment of taxes. In the past,

before appreciation of the value of coastal property this form of development was prevalent to

northeast Florida. In St. Johns County the changes in land use from the 1970's to the 1980's

shows several examples of trailer park conversions to large commercial endeavors. In 1997 the

Save Our Homes Amendment was enacted. This amendment has important attributes that impact

residential development, particularly in coastal areas. The constitution of the State of Florida was

amended after residents in southwest Florida objected to rapid property tax increases as coastal

property appreciated. Statewide, property that is owner occupied and with residents claiming a

homestead exemption, is limited to 3 percent increases in ad valorem taxes annually. When

property transactions occur the residual property taxes are levied. This has made analyses of

taxable value as an indicator of property appreciation inappropriate.

Land Use Planning in Florida

Settlement patterns are influenced by the market and government regulations, such as

zoning, transportation and tax policy. Growth management legislation throughout the country

struggles with the degree to which public policy should restrict the free market through land use






22


(Hart, 2000). The value of a parcel of land may be reduced by environmental restrictions, for

example. The recognition that coastal areas are highly desirable for development forces local

jurisdictions to address the competing needs of development pressures, preservation of traditional

uses (such as fishing), protection of the environment, and maintenance of the coast for public

recreational use. Such delegated authority to the local level has inherent problems. Each

proposal is reviewed individually and the cumulative impacts of coastal development may be

overlooked.

Managing growth in Florida has been a dilemma since the introduction air conditioning,

the Space Program in Brevard County and the selection of Florida by the Disney Corporation for

the location of their second theme park. In 1972 the first requirements for comprehensive

planning were enacted by the Legislature in the State Comprehensive Planning Act. In 1985 the

Local Government Comprehensive Planning and Land Development Regulation Act (Chapter

163, Florida Statues) specified the requirements of Florida cities and counties to develop

comprehensive plans and land development regulations. These plans had requirements specific to

the coast, such as protection of coastal resources, control of water dependent uses, limiting of

developments in high hazard areas and the provision of public access (South Florida Regional

Planning Council, 1989). Section 9J-5 of the Florida Administrative Code specifies the minimum

criteria for coastal zone management elements of the comprehensive plan. Communities must

inventory, analyze and project the impacts of future land use and its impact on hurricane

evacuation. Each local jurisdiction must develop post-disaster plans for high hazard areas and

attempt to minimize future exposure of development, infrastructure and individuals to coastal

hazards.

Determinations of countywide existing and future land use designations, by local

jurisdictions were required after the 1972 State Comprehensive Planning Act and the 1985 Local

Government Comprehensive Planning and Land Development Regulation Act. The first

Comprehensive Plan submitted to the Department of Community Affairs under the 1985






23


requirements was made by Brevard County in 1988. Each Comprehensive Plan must be updated

every 10 years. Therefore, the study areas have plans from three time periods, the 1970's, late

1980's and late 1990's. Each plan delimits the existing last use and proposed future land use

restrictions at a parcel level. Use of parcel data provides the ability to use detailed information

and to combine it to consider cumulative impacts on the coast (Hart, 2000). The public policy of

the local jurisdiction, illustrated by the existing adopted future land use restrictions are

investigated in this research.

Research Hypotheses

Schumm (1991) uses examples to illustrate the potential errors that can be made when

attempting to extrapolate from the present to the future, or past in earth sciences. Schumm

maintains that the use of multiple hypotheses will eliminate problems with interpretation of

natural systems. He notes multiple hypotheses assist with "specific procedural problems that may

be encountered in the development of explanations of phenomena and the extrapolation of

research finding to analogous and homologous situations" (Schumm, 1992, pp. 34). There are

four main hypotheses investigated in this research.

Hypothesis 1: Local geomorphology at each time interval impacts human variables at the same

interval

Hypothesis la: The local geomorphology influences the actual development. This

hypothesis is illustrated by a relationship between actual geomorphology, and the human

variables at that time (Conway and Nordstrom, 2003). An example of this is the impact of the

beach width on the number of units. A wider beach indicates a more stable coastal area that may

be suitable for more units, than an area with a narrow foreshore.

Hypothesis Ib: The local geomorphology influences the land use control decision-making.

This hypothesis proposes that future land use plans are developed by considering

geomorphological conditions, such as the suitability of land use for development noted by Hails

(1977). An example of this hypothesis is an area with large dunes being designated as suitable






24


for higher adopted future land use densities, so the higher the maximum dune height, the higher

the proposed number of units permitted in the future planning horizon.

Hypothesis 2: The dynamic aeomorpholovg impacts human variables

Hypothesis 2a: The dynamic geomorphology indicators influence the actual human

variables. A dune height that varied over decades indicating dynamic local coastal

geomorphology would be negatively correlated to human variables such as the number of

dwelling units and impervious area. The more height variation the more dynamic the

environment and the less suitable it is for development. Thus the area would have a lower the

number of units, and smaller impervious areas indicating that the physical environment had

impacted the development characteristics. Lundberg and Handegard (1996) noted the adaptation

of agricultural uses to the environment, and McMichael (1977) and Miller (1980) noted the

preference of higher ground inland of the barrier island for settlement.

Hypothesis 2b: The dynamic geomorphology indicators influence the land use control

decision-making. An example of this hypothesis is a beach width changed over time in any

direction that would indicate a dynamic coastal area. Such an area would not be suitable for the

establishment of high proposed future land use densities. The more beach width increased and

decreased over time the less suitable the area for development. Thus the area should have a lower

planned future land use density. Bush et al., (1999) detail zoning restrictions used for hazard

mitigation in North Carolina. This hypothesis proposes the reverse, with zoning outcomes as the

result of the characteristics of the physical environment.

Hypothesis 3: There are temporally lagged relationships between the actual and dynamic

geomorphology variables and the human variables. This hypothesis contemplates that

geomorphology in one time period will influence human variables in later time periods. For

example, the wider the beach width the more stable the coastal environment and therefore the

more suitable for greater impervious area percentage in the later time period. Nordstrom (1987)

noted that the impact ofjetties on the coastal system was delayed and could not be evaluated on






25


an immediate timescale without inaccurate conclusions. Van Der Wal (2004) used a 15-year

evaluation of renourishment to determine delayed impacts of the activity.

Hypothesis 4: The dependent variables will have different relationships with the

independent variables in the two separate study areas.

The explanatory power of the individual variables will be different in each county. For

example, the influence of the shoreline orientation, drift direction and storm history in each

county will make the local geomorphology less significant due to the larger scale and longer-term

impacts. The regression coefficients and significant variables for each county will be different.

Schwartz (1971) and Shideler and Smith (1984) show that areas cannot be evaluated without

those adjacent. In this research the two counties are not adjacent, and governed by different

policy-making bodies. Thus conclusions about the two counties are likely to be dissimilar. Davis

(1997) used research along the Gulf of Mexico coast and demonstrated the alongshore variability.















CHAPTER 3
STUDY AREA

The two areas investigated are long inhabited and historically significant. Brevard County

was originally an important agricultural area and large producer of citrus crops. The coastal

development was initiated in the 1940's and boosted by the choice of the Cape Canaveral area for

the location of the National Aeronautic and Space Administration (NASA) facilities. The areas

are characterized by low-density development and incorporate a mix of single family homes,

multi-family condominia and commercial areas that were settled predominantly in the last thirty

to fifty years. Allen (1991) considers the Brevard County and adjacent areas the least intensively

studied in Florida. The northeast Florida region contains St. Augustine, the longest inhabited city

in the United States (Fernald and Purdum, 1992). Human habitation has continued from the rule

of the Spanish to the recently developed golf course communities of the Ponte Vedra area. Both

Brevard and St. Johns counties are located on the east coast of Florida, and although separated by

the false cape of the Cape Canaveral National seashore, a similar orientation to winds, waves and

tides exists from Nassau County to Jupiter Inlet. The two study areas are in this area and exist

with similar large-scale geomorphic conditions.

The story of South Florida's evolution from a crocodile and mosquito infested swamp to a
sybarites Shangri-la by the 1950s is a story of ambition, hype, and technological wizardry
pressed into service for the pleasure principle the saga of creating paradise from silt and
scratch. Lencek and Bosker, 1998, pp. 234.

In 1907 yellow fever was eradicated, providing a milestone for the colonization of Florida.

In 1927 the density of Florida was 1 person per 10 ha (Florida Department of Agriculture, 1928).

Large population centers at that time were Orlando, Jacksonville, Pensacola, Tampa and Miami.

The coast was considered a resource for the function of ports. Many of the settlements,

accessible only by water had origins as fishing villages. However, Tampa and Miami had their



26






27


origins in the export of citrus products. St. Augustine was a minor port. The channel and harbor

in St. Augustine were reported to be 1.8 to 2.4 m deep. Cape Canaveral was predicted to become

a port of importance because of rail connections, the protection afforded and the piers and

availability of land for terminals. Agriculture, forestry and expansion of the cement and fruit

exporting industries were identified as the goals for the future of Florida (Florida Department of

Agriculture, 1928).

The main attractions of Florida were described as climate and scenery (Florida Department

of Agriculture, 1928). Tourism was identified in terms of hunting and fishing, ironically only for

men. One of the unique features of the state was identified as the beaches. They were considered

unique because they contained rare metallic minerals. The fact that beaches were flat and hard

and suitable for vehicular traffic was recognized as a novelty. The indication that a small number

of coastal areas had made preparations for tourism at in the 1920's was illustrated through the

increase in hotels and rooming houses and the number of golf courses. It was recognized that

"winter visitors will come here, and in gradually increasing numbers" (Florida Department of

Agriculture, 1928, pp. 161). In contrast, in 1981 eighty six percent of tourists visiting Florida

participated in coastal-related activities (South Florida Regional Planning Council, 1989).

Geomorphological Characteristics of the Florida Coast and Study Area

Beaches and sand dunes are vital for tourism and recreation in Florida. These areas are

also vital for dissipation of wave energy, protection from coastal storms and storage of sediments.

The coastline of Florida varies from narrow sandy spits to coral reefs, and from remote wildlife

sanctuaries to thriving urban areas. The 1,900 km of coastline in Florida is the longest in the

coterminous United States. Florida's wide continental shelf, sediment supply and wave energy

contribute to a coastline fringed with barrier islands and tidal inlets. The area inland of the barrier

island, is composed of tidal lagoons, linked together, and deepened by dredging to form a

navigable route, the intracoastal waterway, around the entire state. There are 1,250 km of sandy






28


beaches in Florida (Foster, 1992) representing over 25 percent of the sandy shores in the United

States (Morgan and Stone, 1985).

The most dominant feature along Florida coast is the presence of barrier islands (Davis et

al., 1992). Pilkey and Dixon (1996) identify four conditions that must exist for barrier island

formation. These are sea level rise, gently sloping coasts, a source of sediment, and a wave

regime suitable for transporting sand. The favorable factors for barrier island development are

present in Florida and explain the dominance this feature. The only areas of Florida that do not

have barrier islands are the Florida Keys and the Big Bend area (Figure 2-1), which lacks

sufficient wave energy and an adequate sediment supply (Lannon and Mossa, 1997).

Barrier Islands

Barrier island shapes are determined by coastal conditions. The coast of Florida has been

classified from moderate to zero energy environments (Tanner, 1960), and the study areas are

microtidal (Davis and Fox, 1980; Davis, 1994; Davis 1997). Typical of microtidal wave

dominated conditions, the barriers are long and narrow with few inlets and have smooth

uninterrupted shorelines. Inlets are traditionally unstable with large flood deltas and are prone to

migration and closure if not stabilized. Dunes, and in areas that are prograding, dune ridges, are

usually present (Davis, 1994a). The barrier island system of Florida has developed in the last

3000 years (Davis, 1994b). Florida was a large carbonate platform covered with shallow seas

100 million years ago. Sediments from the southern Appalachians were carried along both coasts

of Florida during the Pleistocene. There are minimal terrigeous sediments entering the system

and the sediment from rivers is trapped within estuaries. Therefore, barrier islands are formed

from the reworking of old sediments enabled by the slow rate of sea level rise.

Sea level rise during the Holocene, along with wave and tide climates influenced the

formation of barrier islands. Sea level rise has continued from 15 to 18,000 BP to present. The

rise was most rapid until 7,000 BP, when the rate slowed. There are a variety of scenarios

proposed on sea level rise rates, and the rate and change in sea level rise is dependent on






29


geographic area (Aubrey, 1993). For the past 3,000 years the rates have varied with some authors

favoring fluctuations while others recognize a steady rise in sea level (French et al., 1995; Pirkle

et al., 1970). It is generally accepted that sea level rise over the last 3,000 years has been between

1 and 5 mm annually (Davis, 1994a).

There are two theories that dominate research on barrier island formation (Field and

Duane, 1975). The coastal barrier beach of St. Johns County, north of St. Augustine inlet is a spit

extension. Gilbert (1885) and Fisher (1968) contend that spits, or thin strips of sediment, extend

from headlands in the direction of prevailing longshore drift. As sediment is pushed along the

coast by wave energy it elongates into spits that may eventually become detached if sediment

supply slows or if they are breached by storm waves. The detached spits will become vegetated

trapping additional sediment, building dune systems and stabilizing a barrier island. Anastasia

Island in St. Johns County is described as a barrier beach (FDEP, 2004a) and has several

alternative theories of origin. Otvos (1970) favors the notion of emergence of shoals from

underwater. There is some evidence that this occurs along the low energy Gulf Coast of Florida,

but is unlikely to be responsible in other cases, such as Anastasia Island or in Brevard County.

High wave energies along the eastern United States, for example, make it difficult to imagine

how this process would form barrier islands under those conditions.

Transgression, or drowning in-situ (Hoyt, 1967) hypothesizes that coastal ridges or sand

dunes formed, and were flooded as sea level rose after glacial melting. The ridges of sediment

then move onshore as sea level rises producing a lagoon behind the sediment. It seems unlikely

that any one theory is completely applicable for all conditions. The prevailing theory of barrier

island formation is multiple causality, or many causes that may be inter-related (Schwartz, 1971).

In parts of Florida, such as the Brevard County there are two series of barriers further suggesting

multiple causality. The earlier barrier is the Merritt Island system, which is fronted by the current

barrier islands and separated by Mosquito Lagoon, Banana River and Indian River Lagoon. This

series reflects two transgressions of sea level. However, the Brevard County barrier system is






30


also unusual near the False Cape area, where a clear inflection point occurs. The barriers in the

Brevard County areas have been classified as perched by Tanner (1960). That means that the

sediment that is at the surface covers an original barrier from a previous geologic age.

Sediments

Coastal sediments in Florida are composed of quartz and calcium carbonate. The calcium

carbonate is from shell fragments and oolite, or granular limestone grains (Johnson and Barbour,

1990). On the Atlantic Coast of Florida the amount of shell fragments, derived from coquina, or

rock formed from shells, increases towards south Florida. The calcium carbonate volume

increases from less than 10 percent in the Jacksonville area, to over 40 percent in Miami (Giles

and Pilkey, 1965). However, the areas of central Atlantic Florida have also been found to have

sediment variations. Sediment in Brevard County is described as having a composite mean grain

size between 0.13 to 0.25mm, and 0.19 mm on average (U. S. Army Corps of Engineers, 1992).

Stapor and May (1982) found that Jacksonville Beach, Anastasia Island, and False Cape, in

Brevard County are composed of fine grained quartz sand, compared to the coarser sand with

larger amounts of shell material in the intervening areas (Buckingham and Olsen, 1989). Foster

et al. (2000) describe the sediment north of St. Augustine Inlet and south of Matanzas Inlet as

"crushed shell hash," the source of which is nearshore coquina rock. The source of the

noncalcareous coastal sediments is from rivers draining areas above the coastal plain, not local

rivers (Giles and Pilkey, 1965). Swift (1975) has determined that the sediments were deposited

offshore and were transformed during sea level rise, forming the origins oftoday's beaches and

barrier islands. Sediments come from the erosion of coastal deposits in Virginia and North

Carolina (Tanner, 1960).

Dunes

Dunes are elevated areas of unconsolidated sediment that are formed and maintained by

wind transportation of sand. Dunes need four criteria to form and flourish: a sediment source;

strong onshore winds; a gentle beach gradient; and, low humidity (which Florida does not






31


exhibit) and precipitation (Carter, 1988). The study areas experience winds strong enough to

sustain the coastal dunes. This wind regime is conducive to dune stability. The beach gradient is

gentle and suitable for both barrier island formation and dune formation. Dunes throughout

Florida have formed as wind transports sand from the beach face inland. Vegetation traps sand

by causing the wind speed to drop and deposit the wind blown or aeolian sand movement. In

Florida sea oats are present along the coast. Sea oats are protected by law and cannot be removed

(Florida Statutes, Chapter 370.041). The intent of this requirement is to recognize the importance

of this hardy dune plant in establishing, and more importantly stabilizing Florida's dune system,

which provides the first line of defense from storm and hurricane conditions. Webb et al. (1997)

attribute dune removal to increased destruction of buildings along the panhandle of Florida during

Hurricane Opal in 1995. Dune height and gradient is a function of sediment. Foster et al. (2000)

attribute the gentle gradients on Anastasia Island to the fine quartz, compared to the relatively

steep dunes in northern St. Johns County that are comprised of sand and shell particles (Mossa,

1993).

The broader barrier islands of the Florida coasts exhibit beach ridges. Beach ridges are a

series of parallel ridges and swales. Ridges represent progradation seaward or parallel to the

coast (Johnson and Barbour, 1990) and may be truncated or eroded by more recent events. There

are four areas exhibiting beach ridges on the Florida Gulf coast (Schwartz and Bird, 1985) and

beach ridges are present at Cape Canaveral and on Anastasia Island in St. Johns County (Stapor

and May, 1982). Field (1974) estimates that Cape Canaveral beach ridge deposition took place

30,000 to 35,000 years BP.

Tide, Wave and Longshore Drift Characteristics

Tides in the study area are semidiurnal. The mean tidal range is 1.4 m (Foster et al., 2000)

and the spring tidal range is 1.6 m. The average wave height at the Melbourne Beach wave gauge

in Brevard County is 1.01 m, with an average wave period of 6.3 seconds. The prevailing wave

direction is east-northeast (Olsen, 2003). In St. Johns County the mean significant wave height is






32


1.1 to 1.2 m. The prevailing wave and wind approach is from the northeast (Foster et al., 2000),

although during the summer the wave direction is from the southeast with smaller waves.


I Coastal Structures

ort Canaveral Inlet Eroding Area
onment Renourishment Area

20 CANAVERAL ** Access Point
12 Monument
COCOA BEACH
Longshore drift
Patrick Air direction (FDEP,
S Patrick Air 2004a)
Force Base

75 ATLANTIC
OCEAN
SATELLITE
BEACH
105



MELBOURNE
BEACH

Spessard A
Holland Park
150
CBRA
rea Semidiurnal tide of 1.4m

Net longshore drift to south
38,000 to 76,000 m3/yr
(FDEP, 2004a)



Sebastian Inlet
INDIAN RIVER
Kilometers COUNTY
Figure 3-1. Coastal municipalities and geomorphic characteristics, Brevard County, Florida






33


The littoral drift on the east coast of Florida is predominantly north to south (Reesman,

1994). In Brevard County drift of approximately 38,000 to 76,000 m'/yr is to the south (FDEP

2004a). However, Stapor and May (1983) have noted several littoral cells on the Northeast coast

and describe Anastasia Island as an area of convergence and the area between Vilano Beach and

Ponte Vedra as an area of divergence (Figure 3-2). Drift, predominantly during the summer, is to

the north on Anastasia Island (Stapor and May, 1983). In St Johns County the prevailing drift

direction is to the south and reported rates vary from 112,000 to 336,000 m3/yr (Foster et al.,

2000). Anecdotal evidence reports pulses of sediment along Ponte Vedra beach. This may be

due to renourishment activities to the north (Foster et al., 2000). Femandina beach was

renourished in 1978. The Fort Clinch area in northern Nassau County was renourished in 1996.

The dredging of St. Mary's inlet to accommodate the US Navy has resulted in the placement of

material on Amelia Island (Reesman, 1994). On Anastasia Island the rate is lower at 152,000 to

228,000 m'/yr to the south (FDEP 2004a).

Storms

The impact of storm activity is considered a long term and macroscale variable (Davis and

Dolan, 1993). It is obvious that hurricane and storm activity impacts settlement decisions

although the extent to which this impact influences settlement cannot be easily evaluated within a

30-year timeframe.

"The hurricane that hit in 1885 discouraged further settlement. The storm pushed the

ocean waves over the barrier island (elevation 10 feet [3.2m]) flooding out the homesteaders.

The beach near Canaveral Lighthouse was severely eroded prompting President Cleveland and

the Congress to allot money for an effort to move the tower 1 mile [1.61 km] west" (Rabac, 1986,

page vii)

The hurricane history of the two study areas is different in the long-term and over the 30-

year study period. The record of hurricanes from 1872 to present shows that the east central






34


coast of Florida has experienced more direct storm activity than the northeast coast of Florida

(Appendix A).

Table 3-1. Hurricane and tropical storm activity in the study areas
County/Area Hurricane/ Hurricane/ Exiting Offshore
Tropical Storm Tropical Storm Hurricane Hurricane
Landfalls within Historical Record Historical Historical
100 km since Record Record
1970
Brevard (east
central Florida) 4/2 8/2 6 7

St. Johns
(northeast 0/2 2/2 6 4
Florida)

The distinction between hurricanes and tropical storms was not made before 1890. The

pattern of hurricane activity in Florida shows that storm intensities and numbers have varied.

From 1931 to 1940 there were only six hurricanes. "1941-1950 [was] the most devastating

decade in Florida's history since records were kept" (Williams & Duedall, 1997, pp. 18). There

were 12 hurricanes that made landfall during that period compared to only three from 1951 to

1960 (U. S. Army Corps of Engineers, 1992). Brevard County has the distinction of extending

further into the Atlantic than St. Johns County. The cuspate shape of the foreland renders it more

vulnerable than the more embayed St. Johns County. Hurricane David was the first hurricane to

strike the Brevard County area since the storm in 1928. The eye of the hurricane passed over the

coast and moved back offshore, eventually making landfall in northeast. Hurricane Erin, which

later impacted the panhandle of Florida, hit east central Florida in 1994 as a Category I hurricane.

There have been two tropical storms that made landfall during the study period, in 1983 and

1994. This area also experiences indirect impacts of offshore hurricanes. For example, Hurricane

Floyd in 1999 threatened the northeast Florida coast but remained offshore and eventually made

landfall in North Carolina. The documented history back to 1872 shows that the region of

northeast Florida experienced only two direct hurricane landfalls in 1880 and 1964. Hurricane

Dora and the storm of 1880 are the only storms to have hit the northeast coast of Florida directly.






35





DUVALCOUNTY Monument Coastal Structures
0 5 10 4
0 Eroding Area
Kilometers
Renourishment Area

Access Point

12 Monument

Longshore drift
direction (Stapor and
Guana May, 1983).
River
State
Park

ATLANTIC
\ OCEAN

VILANO
REACH
121
St Au stine Pass
Anastasia State
Recreation Area

AUGUSTINE
BEACH

CRESCENT
EACH





nlet Semidiumal tide of 1.4m
209 Net longshore drift to south
112,000 to 336,000 m3/yr
FLAGLER COUNTY (Foster at al., 2000)

Figure 3-2. Coastal municipalities and geomorphic characteristics, St. Johns County, Florida






36


Hurricanes impacts in northeast Florida have been largely indirect with limited activity

from storms traveling from the Gulf of Mexico over the peninsula and back into the Atlantic.

Hurricane conditions were experienced in 1964, when hurricane Donna passed over north central

Florida. This hurricane was exiting Florida and moving offshore having passed over Florida's

north central peninsular area. In addition to direct hits and winter storms, Northeast Florida is

prone to indirect storm impacts. The recognized recurve pattern of storm paths up the

southeastern United States impacts the area. In northeast Florida indirect hurricane conditions

have caused flooding of infrastructure, storm surge and dune erosion and wind damage

(Reesman, 1994). Storms during the 1990's have caused local erosion along the northeast coast.

Hurricane Floyd in 1999 threatened the northeast Florida coast but remained offshore and

eventually made landfall in North Carolina. The northeast Florida study area has not experienced

any direct hurricane landfall during the 27-year research.

The most recent 2004 storm history is after to the data used in this research. However, it is

important to note that three storms impacted the study areas. Brevard County experienced

hurricane conditions from Hurricanes Frances and Jeanne. Both these storms also produced

tropical storm conditions in St. Johns County. The impacts on the St. Johns County

renourishment projects are discussed in the results section. Hurricane Charley also exited south

of St. Johns County, in the vicinity of Daytona Beach.

Winter Storms

Winter storms or Nor'easters are extratropical storms that impact the coast from October to

April. Although they may not have the extreme wind speeds associated with hurricanes they

affect wider swaths of the coast because they are larger and may stall over coastal areas. These

storms can be over 1,000 km wide and cause surges of over 4.5 m. Prolonged wave activity

enhances the destructive capacity of a winter storm. Nor'easters derive their names from the

prevailing wind direction. These storms rotate counterclockwise and travel north along the east

coast of the United States (Davis and Dolan, 1993). The low-pressure core is accentuated by high






37


jet stream winds. The position of the jet stream each season affects the number and type of

winter storms (Davis and Dolan, 1993). The Department of Environmental Protection surveying

patterns show that winter storms have impacted the study areas. DEP performs post-storm

condition surveys and from these records there have been storms that impacted the

geomorphology sufficiently that resurveying was performed, usually in small segments of a

county. In Brevard County winter post-storm resurveying was carried out in 1973, 1981, and

1985. The DEP records indicate winter storm activity in 1981 and 1984 in northeast Florida.

Reesman (1994) notes that winter storms impacted the northeast Florida region in 1932, 1947,

1962 and 1973. The U. S. Army Corps on Engineers (1992) lists 28 storms that impacted St.

Johns County between 1977 and 1993. It should be noted that the resurveying of areas is also a

function of the state budget. State funding inconsistencies necessitate caution in concluding that

geomorphic impacts occurred only during these events.

Development History

The land uses in Brevard County have evolved from citrus production to high-density

residential and commercial uses. Figures 3-3 and 3-4 show the development patterns at the same

position in Brevard County. In 1950 Cocoa Beach was approximately half built out and in 1972

was 75 percent built out (Bodge, 1992). The 1972 aerial photography shows there was no

development adjacent to the Port Canaveral Inlet jetty. In the City of Cape Canaveral roads are

perpendicular to the shore and residential and multifamily development was present. In 1985,

95 percent of the Cocoa Beach was built out (Bodge, 1992). Between Cape Canaveral and the

residential area in south Cocoa Beach high-rise residential, commercial and large impervious

parking areas were present. Residential lot sizes in Cocoa Beach are small and development is

dense. There were large structures and areas of impervious surface, such as the Pam Am world

headquarters, which had been redeveloped into high-density condominia by 1997. Patrick Air

Force Base was renovated between 1986 and 1997 and the base housing was redeveloped at

higher densities. South of the Base infill and development on vacant lots has occurred. Brevard






38


County south of monument 118 has similar characteristics to northern St. Johns County with a

single shore parallel access and large low-density single-family development. The Coastal

Barrier Resources Act covers the section between monuments 157 to 164, so that development is

this area cannot receive federal assistance for flood insurance or roadway construction.

Development in the barrier islands of northeast Florida has occurred predominantly since

Hurricane Dora in 1964 (Reesman, 1994). The coast of St. Johns County is 66.5 km from Duval

to Flagler County to the south (FDEP, 2004b). Figure 3-2 shows the locations of the inlet, coastal

municipalities and parks referred to in this research. In 1972 St. Johns County was not intensely

developed. There are several sample 9-hectare plots with no development at all. The

development that existed was sparse single family, mobile home and small commercial. To the

north at Ponte Vedra at monument 2 the Ponte Vedra Golf Club was constructed. However, it is

clear for the lack of residential development surrounding that area that the influences of

Jacksonville as a metropolitan area did not extend to northern St. Johns County. Along Anastasia

Island in 1972 there are large undeveloped areas. Highway AIA is routed away from the coast

leaving large areas with potential for development. In 1972 there were 3 large trailer or RV

developments. These consisted of a concrete pads and utility connections. Large-scale

condominia, hotels and motels were not present except at St. Augustine Beach. South of

Matanzas Inlet there was development immediately adjacent to the inlet, and none on the spit

between the Matanzas River and the Atlantic.

In 1986 single-family development had expanded. Large homes had been constructed in

the Ponte Vedra Area and Vilano Beach was beginning to develop with smaller single-family

homes. The Ponte Vedra commercial area had expanded. The construction of homes further

south on AIA was occurring. Just north of St. Augustine Pass, in the area protected by rocks, a

single-family neighborhood had developed by 1986.






39







Atlantic
Avenue

Motel Pool




Monument
32



Gas Station 4
4th Street N

1974
1 12667





Atlantic
Avenue

Motel Pool





32




Gas Station -th Street N
NFigure 3-3. Urbanization at monument 32, Brevard County. A) 1974. B) 1986.



Figure 3-3. Urbanization at monument 32, Brevard County. A) 1974. B) 1986.






40







Atlantic
Avenue


Motel Pool





32



Gas Station
4h Street N




Figure 3-4. Urbanization at monument 32, Brevard County, 1997


On Anastasia Island large condominia and hotels were beginning to be constructed on

previously vacant tracts. Single-family homes were also removed for these projects and two of

the three travel trailer parks were replaced with multi-story residential structures and associated

parking and amenities, such as pools and tennis courts. South of Matanzas Inlet homes were built

on the spit. By 1999 northern St. Johns County was developed with single-family homes, and the

influence of the Jacksonville metropolitan area is evident. Homes in this area are large and

smaller homes have been enlarged or replaced.

Inlets

Brevard County has two inlets, Port Canaveral to the north of the study area and Sebastian

Inlet that marks the boundary with Indian River County (Figure 3-1). Sebastian Inlet is man-

made and has been maintained since 1948 by dredging and the installation ofjetties (Wang and

Lin, 1992). The Port Canaveral Inlet was stabilized in the 1940's. It has been theorized that the






41


stabilization of the inlet impacted stabilization of the foreshore in Coca Beach. However it is

unlikely that any influence downdrift extends beyond 0.62 km (Bodge, 1992). Port Canaveral

Inlet is dredged to a depth of 13 m, although during Hurricane Frances in 2004 shoaling

decreased the depth to 8 m (FDEP, 2004a). Dredge material is too fine for beach placement and

is disposed offshore (FDEP, 2000a). Subsequent to this study period the Department of

Environmental Protection adopted an inlet management plan to bypass beach-compatible sand to

nearshore-disposal areas adjacent to monuments 1 to 14 (FDEP, 2000a)

Figure 3-2 shows the two inlets in St. Johns County, St. Augustine Pass south of Vilano

Beach and north of Anastasia State Recreation Area, and Matanzas Inlet between Anastasia

Island and Summer Haven (FDEP, 2000b). St. Augustine Pass was dredged initially in 1940.

The inlet has jetties on the north built in 1941, and south, built in 1958 (McBride, 1987) and is

maintained by U. S. Army Corps of Engineers (Foster et al., 2000). At Matanzas Inlet a

revetment and bridge abutment, initially constructed in 1925, reinforces the south shore. This

inlet is not dredged. South of Matanzas Inlet the coast is protected by structures and designated

an area of critical erosion (Clark, 1999).

Coastal Structures

Structures will impede the transfer of sediment from the foreshore to the dune system

(Carter 1988, Gares, 1987, Nordstrum, 1994). Coastal armoring in the form of parallel structures

has been shown to increase scour and hasten the removal of sand in the foreshore (Beatley, et al.,

1994, Carter 1988, Pilkey and Dixon, 1996, Pilkey, and Clayton, 1989). Therefore, the presence

of structures may impact the beach width, by steepening the beach. Coastal structures are present

in St. Johns and Brevard Counties (Figure 3-1 and 3-2). Brevard County has an extensive length

of shoreline in Cocoa Beach that has a seawall. In 1950 there was about 300m of bulkhead at

Cocoa Beach (Bodge, 1992). In 1972 over 20 percent of the coast had bulkheads compared to 7

percent in 1950. By 1985, 95 percent of the Cocoa Beach area was built out and 48 percent had

bulkheads. Brevard County has many formal and informal (individual resident initiated)






42


shoreline protection structures. St. Johns County contains two areas with shore-parallel structures

in Ponte Vedra and St. Augustine Beach (St. Johns County, 2002). At St. Augustine Beach, piles

of rock stabilize the point at which Highway AIA turns west (monument 141). Previously

Highway AIA continued further north on Anastasia Island until it was threatened by erosion

during hurricane Dora. There are no extensive bulkheads or seawalls from Ponte Vedra to

Vilano Beach, although individual homeowners have made small-scale private attempts (St.

Johns County, 2002).

Renourishment of the Shoreface

Brevard County has had several renourishment projects during the study period, which are

shown in the Table 3-2. Brevard County has 115.2 km of coastline (including the Cape

Canaveral National Seashore, that is not part of this research) and 16.7 km has been renourished

(Esteves, 1997). There are also instances where individual homeowners have attempted informal

and unpermitted shoreline protection methods. Localized small-scale protection, sand fencing or

netting, and planting of dune vegetation are not considered coastal structures and not included in

this variable.

Table 3-2. Renourishment projects in Brevard County during 1972 to 1997 study period
Monument/ Alongshore Date Volume (m3)
Location Distance (km)
(Not in research area) Unknown 1972 152,900
1 to 33 Approx 3 1974-75 2,075,889
119-134 Approx 4.5 1980-81 412,938
50-76 Approx 6 1985 550,512
City of Cocoa Beach Unknown 1986 30,580
City of Cape Unknown 1992 99,398
Canaveral/Cocoa Beach
City of Cape Unknown 1993 152,920
Canaveral/Cocoa Beach
City of Cape Unknown 1995 567,333
Canaveral/Cocoa Beach
Source: Brevard County Comprehensive Plan, 1988, Sudar et al., 1995. Esteves, 1997,
Pilkey and Clayton, 1997.

There has been no large-scale renourishment activity in the portion of St. Johns County

examined during the study period (Pilkey and Clayton, 1997). However, of the 66.1 km of






43


coastline, 2.8 km have been renourished (Esteves, 1997) in Anastasia State Recreation Area. The

park was renourished in 1963 when 38,230 m3 of sediment was added (Dean and Donohue,

1998). In 2000 renourishment began at St Augustine Beach (monuments 140 to 147) and in 2001

at Summer Haven (monuments 200 to 207). Renourishment using sediment dredged from St.

Augustine Inlet was carried out in Anastasia State Park in 2002 (Dean and Donohue, 1998).

While Anastasia State Park is not included in the study area because it is excluded from

development as a State Park, sediment from renourishment projects enters the coastal system on

Anastasia Island, downdrift of the park.


Table 3-3. Recent renourishment projects, Brevard County.
Monument Alongshore Date Volume
Location Distance (km) (mM)
3-54.5 15.13 Oct. 2000-April 2001 2,435,720
53-60 4.99 Dec. 2000-April 2001 454,670
122.5-139 4.86 Feb-April 2002 899,000
118.3-123.5 1.51 March-April 2003 175,840
Source: Olsen (2003)

Table 3-4. Recent renourishment projects, St. Johns County.
Monument Distance (km) Date Volume (m3)*
Location
140-147 St Unknown 2000 Unknown
Augustine Beach
132-152 6.12 Sept. 2001-Jan 848,930
2003
Summer Haven Unknown 2001 Unknown
*Excludes Anastasia State Recreation Area.
Source: FDEP (2004a), Dean and Donohue (1998).














CHAPTER 4
METHODOLOGY

This research is divided into two areas of inquiry; the influence of the actual

geomorphology and the impact of geomorphic variability, on planned and actual coastal

development in two regions of Florida over a 27-year period. The actual geomorphology affords

temporal analyses of impacts. Geomorphic variability enables spatial distributions and patterns to

be investigated along the shore. The two regions investigated have experienced different storm

and hurricane influences (Appendix A) and are governed by separate policy making entities.

The availability of geomorphology data obtained from the State of Florida, Department of

Environmental Protection (FDEP) is shown in Table 4-1. From these data the variables shown in

Table 4-2 and Appendix B are derived. The maximum dune height (DH), distance of maximum

dune height from National Geodetic Vertical Datum (NGVD) (DHBW), beach width index (BW),

the distance from the monument to the maximum dune height (MDH), are shown in Figure 4-1.

Long-term shoreline change (LT), shoreline orientation (OR) the presence of reinforcement

structures (SW), the erosion status (ER) and past renourishment activities (RN) are also included

in the analyses as independent variables. These variables characterize the time-specific

conditions.

Development variables include land use from local comprehensive plans (FLU), the future

land use plan densities (FLUD), the number of residential dwelling units (UN) (of 8 or less

dwelling units per structure), units per hectare (UH), percentage impervious area (PIM), and

hectares of commercial land use (C). The distance to the nearest access point to the coastal area

by causeway or major highway (ACC) and distances incorporating a direction component

(DACC), the position of the shore parallel highway (ROAD) and the geographic location (POS)

are also included in the analyses as dependent variables.


44






45


All development variables use primary data sources and are derived for this research from

maps and photography. Each of the geomorphic variables are collected at monuments located

approximately 300m apart along the entire coast of Florida, excluding the Big Bend area and

Florida Keys. Development, or human variables are collected in sample areas adjacent to the

monument. Sample areas were selected to maximize analyses coverage. Sample areas were

designed to extend an equal distance wither side of the monument by 150m. The 300m

dimension alongshore and inland results in a 9-ha square sample area. The sample area is

oriented parallel to the shore and perpendicular to the meridian (Appendix D). The seaward

extent of the 9-ha sample area is defined by the extent of the digital land use coverage from the

DOQQ's.

The influence of beach width, maximum dune height, distance to maximum dune height,

distance from the monument to the maximum dune height and long term shoreline change on the

actual and future land use, number of dwelling units, impervious area and development potential

is evaluated at each time period.



Maximum
dune height
Monument National
Geodetic
.. Vertical Datum
(NGVD)
Monument
to maximun
dune height


Distance to maximum dune height
Shoreline
change (1872
Beach width index (NGVD to monument) to 2000)

Figure 4-1. Beach profile and geomorphic variables






46




Actual Geomorphology Variables

The coastline of Florida has been surveyed by the Division of Beaches and Shores, State

Department of Environmental Protection (FDEP) since the early 1970s (Clark, 1999).

Monuments are situated along the coastal counties of Florida approximately every 300 m and are

typically set within the dunes. The FDEP collects data for a variety of reasons, such as to assess

local conditions, evaluate the coastal construction control line and for special purposes.

Complete data sets are available in each decade of the research (Table 4.1). Partial data sets for

counties are collected for post-storm evaluation, and pre- and post-construction. Data from

contracted surveys are also included on the FDEP website, but are not used in this research. An

example of the format of the raw data is shown in Appendix C.

Beach Width Index (BW)

Beach width variations reflect areas along a barrier island that are more dynamic, those that erode

and recover more than adjacent areas. This variable has been used by Davidson-Arnott (1988)

and Gares (1988). Beach width is an important variable in the selection of locations for

development. During Hurricane Hugo beaches of over 30 m wide afforded greater protection to

structures, and 84 percent of coastal structures that were destroyed had a beach width of 15 m or

less (Bush et al., 1999). The FDEP beach profile data are modified to represent beach width

(BW). The distance from the survey monument to the water (using the National Geodetic

Vertical Datum, NGVD) is calculated. NGVD is defined as the National Geodetic Vertical

Datum, as established by the National Ocean Survey in Chapter 62 of the Florida Administrative

Code'. NGVD provides a suitable zero point for this research because NGVD is used as a


' In the United States 75,159 km of leveling was standardized in 1929. A fixed elevation was
assigned to 26 points on a network that defined elevations in the United States and Canada as the
mean sea level datum of 1929. This was commonly referred to as "mean sea level" and was
confused with "mean water level" until 1979. It was renamed the National Geodetic Vertical
Datum of 1929.






47


baseline for the FDEP surveys and is consistent throughout the two study areas and the entire

study period.

Table 4-1. Geomorphic data availability by study area
Study Area Data Availability
Brevard County 1972, 1983-, 1986, 1993-, 1997
St. Johns County 1972, 1984-, 1986, 1993-, 1999
~ Data are incomplete or only available every 3 monuments

Table 4-2. Independent (geomorphic) variable details
Independent Variables Name
Beach Width Index BW
Maximum Dune Height DH
Monument to Maximum Dune Height MDH
Beach Width to Maximum Height DHBW
Long-term Shoreline Change LT
Geographic Location POS
Orientation OR
Distance to Access Point ACC
Distance and Direction to Access Point DACC
Presence of Structures SW
Renourishment RN
Dune Renourishment (Brevard County RND
only)
Temporal Scale Name
Actual
1972 tl
1986 t2
1999 (1997 Brevard) t3
Dynamic
Change from 1972 to 1986 t2-1
Change from 1986 to 1999(1997 Brevard) t3-2
Change from 1972 to 1986(1997 Brevard) t3-l
Total Change (Absolute Value) tot
Change Factor (Ratio Net to Total) f
Appendix A contains source and measurement data for each variable.

The monument is a fixed position on the profile. The monument location varies in certain

instances. When a monument is lost it is replaced by the State of Florida. If the monument was

lost as a result of storm activity or erosion the replacement may be in a new location. The beach

width index from the monument to the NGVD is a measure of relative beach width, and is

measured in meters. The beach width index variable illustrates the changes in width over time.






48


Table 4-3. Profile measurement metadata, monuments I to 200, Brevard County
Brevard County-1972 Brevard County-1986 Cont.
Date Monument Number Date Monument Number
Range Range
9/13/72 1-40 12/19/85 68-86
9/20/72 41-79 1/7/86 123-126
9/21/72 80-95 1/8/86 121, 122
9/26/72 96-107 1/9/86 97-120
10/3/72 108-120 2/4/86 136-155
10/26/72 121 -128 2/5/86 127-135
11/8/72 129-134,151-162 2/6/86 156-172
11/7/72 135-150 2/19/86 174-186,201,204,205
11/9/72 163-195 2/20/86 187-193, 194-200
11/16/72 196-211 2/21/86 173,202,203
11/27/72 212-219 3/5/86 209-218
3/6/86 193, 206-208
3/7/86 219

Brevard County-1986 Brevard County-1997
Date Monument Number Date Monument Number
Range Range
8/27/85 1-13 10/97 1-219
8/28/85 14-23
8/29/85 24-46
12/4/85 52-67
12/5/85 47-51
12/18/85 87-96


Maximum Dune Height (DH) and Distance to Maximum Height (DHBW)

Dune Height (DH) and the Distance to Maximum Dune Height (DHBW) are important

site-specific variables that are strong determinants of susceptibility to inundation (Bush et al.,

1999; Fisher, 1984; Gares, 1988). Maximum dune height is defined as the highest point on the

profile that is recorded seaward of the monument. By considering the point seaward of the

monument, variations due to the extent of the profile inland are controlled. The Distance to the

Maximum Height variable is the distance from NGVD to the maximum height. This variable

gives an indication of the position of the highest point on the profile to the shoreline, rather than

the fixed point of the monument. The importance of the interaction between sediment on the

foreshore and supply to the dunes reflected by the Distance to the Maximum Dune Height has

been discussed by Davidson-Arnott (1988). The distance to maximum height variable gives an






49


indication how the dune field characteristics have altered over time and reflects the importance of

the interaction of the foreshore and dune systems (Psuty, 1988).

Monument to Maximum Dune Height (MDH)

The Distance to Maximum Height is a measure from one geomorphic

characteristic, Maximum Dune Height to NGVD. The Monument to Maximum Height

measures a static point on the profile, the monument, to a dynamic geomorphic feature,

the Maximum Dune Height. Psuty and others (1988) found that the position of the dune

is less dynamic than other geomorphic features. They also showed that the inland

movement of dunes does necessarily exhibit a direct relationship with the dynamics of

the beach, so that landward migration of the dune may not necessarily indicate that the

foreshore is eroding. This variable is particularly important where the Beach Width

Index and NGVD to Maximum Dune height are impacted by structures. In locations

where shore-parallel structures are present, geomorphic changes in the profile seaward

of the structure will be impacted. On such profiles the Monument to Maximum Dune

Height may represent the part of the profile where sediment movement is occurring.

Long Term Shoreline Change (LT)

Historical shoreline change has been calculated at each monument by the State of Florida

and is intended to be used to "assist in growth management and regulatory programs" (Foster and

Savage, 1989, pp. 4434). Long-term shoreline change is influenced by longshore sediment

transport, sand supply, wave climate, geographic features such as estuaries and man-made

structures and nearshore reefs. The FDEP, using the end point, least squares, and rate averaging

methods, calculates long-term shoreline change between 1872 and 2000 (Foster et al., 1999,

Foster et al., 2000). These data were available for St. Johns County (Figure 4-2). Long-term

change rates for Brevard County were calculated using rate averaging and end point rates (Figure

4-4).






50


The end point rate is the difference between the first record and the last record divided by

the entire time period. The end point rates are calculated similarly to net change variable for the

profile data. However, the data are taken from historical maps, shore normal profile data, and

digitized historical shorelines from the U. S. Coastal and Geodetic Survey, the National Ocean

Survey (NOS) and the U. S. Geologic Survey. The least squares method models the slope of the

best-fit line when shoreline width and time are plotted. The rate averaging method is the average

long-term rate of change using a combination of rates over the time periods. The magnitude of the

end point methodology determines which records are used. If the end point methodology shows a

small amount ofchange, it should take a longer time between observations to detect significant

shoreline changes. The FDEP also conducts rate comparison, sensitivity and digitizing variability

tests to determine the points to be included. The time period for each data point collected is

calculated. Data obtained from maps verses surveyed profiles will have different degrees of

accuracy and different minimum time span requirement. Rate combinations over a time period

shorter than the data type minimum are excluded as not reflecting long-term trends. In this way,

short time segments do not influence the calculated rates unduly. All three methods are compared

to demonstrate specific sensitivity to any of the methods.

Each methodology has potential for errors. Each of the records has a level of accuracy

determined by the source information. The end point data gives a net effect that is useful in areas

where there have been continuous changes, such as the impact of beach renourishment (Houston,

1995) that would influence the results of the other methodologies. Using this methodology data

irregularities are dampened. The least squares fit method is sensitive to clusters of records

(Figure 4-4). In the case of shoreline information the data are sparse in the earlier time periods

and more comprehensive in the recent past. The least squares method does not afford a weighting

system to increase the emphasis on more accurate data.






51



Table 4-4. Profile measurement metadata, monuments 1 to 209, St. Johns County

St. Johns County-1972 St. Johns County-1999
Date Monument Number Date Monument Number
Range Range
8/1/72 182-209 2/25/99 1-3,7-13
8/2/72 155-181 2/26/99 4-6, 14-21
8/3/72 141-154 3/16/99 22-36, 58-68
8/15/72 123-140 3/17/99 37-57, 69-80
8/28/72 103-122 3/18/99 81-93, 109-121
8/30/72 63-102 3/19/99 94-121
8/31/72 41-62 3/30/99 122-123
9/5/72 33-40 3/31/99 124-125
9/6/72 1-32 4/1/99 126-134
4/2/99 135-137
St. Johns County-1986 4/13/99 138-141, 147,151-
Date Monument Number 154
Range 4/14/99 142-146, 148-150,
7/15/86 1-7 155-158
7/16/86 8-16 4/15/99 159-166
7/17/86 18-26 4/16/99 167-170
7/18/86 17 4/27/99 171-185
7/28/86 27-30 4/28/99 186-191
7/30/86 31-32,36 4/28/99 192-196, 197A, 198
7/31/86 37-40, 44, 45 4/30/99 197, 199-207
8/1/86 33-35, 41-43, 46-50
8/12/86 51, 52, 91-98
8/13/86 54-56
8/14/86 57-60
8/15/86 61,62
8/19/86 63,99-106
8/20/86 64-66
8/26/86 67-76
8/27/86 77-90
9/9/86 107-109, 123-125
9/1086 110-117, 126-135
9/11/86 118-122, 136-143
9/12/86 200-209
9/20/86 143A
9/23/86 144-153
9/24/86 154-166
9/25/86 167-171
10/10/86 172-178
10/23/86 179-188
11/4/86 189-199














4-


2- _--IO
Ponte Vedra

Gn0 R.- -- Anastasia Island
SGuana River lno
State Park Beach
O -2 Beach _"


I-1
O-4 _
o bt.
Augustine
-6 -- --- Beaceh--


-8 mm
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
Monument Number
Long Term Change (Foster at al,. 2000)

Figure 4-2. Long-term shoreline change, St. Johns County, 1872 to 2000




53










Cape Canaveral
2
E 2 ... -_
Cocoa Beach Melbourne
0m Beach
SSatellite Beach
1 Patrick AFB Beach




o
0 -
S 0)0 0 )


-2



Monument Number

0 Long Term Change (End Point and Rate Average with rolling average)





Figure 4-3. Long-term shoreline change, Brevard County, with data ranges from 1877 to 2001






54


The rate calculation method (figure 4-5), which averages all the long-term rates of change,

reduces the influence of random profile variability, seasonal influences and measurement error

inherent in the different data types. The rate averaging calculation is considered the most

accurate of the methods (Foster and Savage, 1989) although the comparative methodology using

all three produces long-term shoreline change rates less influenced by extreme values derived

from a specific methodology.




Last
rcrord End Point Rate
Shoreline 3 -
position
from 2 Least Squares Fit
monument
(m) 1

First record I I
1872 2000
Time
Shoreline position record

Figure 4-4. Calculation of long-term shoreline change, end point and least square fit methods




--End Point
3 Rate
Shoreline 3 Rate
position 2 "Rate Averaging
from Method
monument 1 -
(m)

1872 2000
Time

Rates determined to be long-
Shoreline position record tr i term by DEP

Figure 4-5. Calculation of long-term shoreline change, rate-averaging method






55



Foster and Savage (1989) suggest that the averaging of shoreline change rates between

adjacent profiles, or longshore averaging, minimizes errors. The length of the segment of

coastline included in the longshore average is important. A segment that is too long will

oversimplify and obscure local conditions. A segment that is too short may be impacted by an

individual profile that is not reflective of the segment. The number of points selected is also

determined by local conditions, such as the extent of coastal structures and the presence of inlets.

Projections of shoreline change are made in light of the current conditions. It is reasonable to

assume that a single storm event in the future could render the estimates invalid. Similarly areas

experiencing substantial changes may reach equilibrium and the rate of change will slow. In

locations where coastal structures are present, rate of change may temporarily cease when the

structure is reached (Wright, 1991).

This methodology does not accommodate the influence of sea level rise, land subsidence or

emergence. Foster (1992) does not consider these to be significant factors in Florida for the

calculation of long-term (greater than 100 year) shoreline change. He concludes that the impacts

of sea level rise are obscured by the variability in tides, storms and longshore sediment

transportation. The impact of shoreline protection structures and beach renourishment are also

random (Foster, 1992). Data frequencies used in this research area also insufficient to illustrate

such short-term impacts as seasonal changes and the influences of wave and tidal climates. The

timeframe considered in this research is insufficient for sea level impacts to be quantified and

infrequent enough for short-term influences with records only each decade. However, while the

timeframe is unsuitable for these scales it is well suited for the analysis of development and plans

for development. A longer spectrum would take the research beyond the development horizon

and required future land use planning documentation.

Long-term change evaluation Brevard County has not been conducted to by the FDEP.

However, long-term shoreline change rates are derived using the "Historical Shoreline Position






56


Database" (http://hightide.bcs.tlh.fl.us/counties/HSSD/readme/read.mel) and published long term

change rates (Olsen and Buckingham, 1989) and are shown in Appendix F. The Shoreline

Position Database directory contains 150 years of shoreline data for each county. For Brevard

County the earliest records are shown below. Where a span of years was indicated the latest

record was used. The end point method noted above was used to determine the long-term change

rates for Brevard County (Figure 4-3) and the extent of the record eliminates the extremes of

variability from the more recent data (McBride and Byrnes, 1997; Esteves, 1997).

The shoreline position from the monument to the mean high water (MHW) level is

indicated, which is a similar measure to the beach width variable in this research. The MHW

position has been determined by FDEP from USGS topographic maps, photography and FDEP

profile surveys. Inaccuracies noted include high wave activity (specifically in the 1980 data) and

sun glare that would influence aerial photo interpretation. Aerial photography is the basis of

maps since 1920. Before 1920 plane table surveying was used (Foster, 1996). The data from

1970 is not recommended for use in Brevard County without aerial verification. Not

withstanding the limitations, the extent of the long-term data are useful and the only known

source of long-term data (Galgano and Leatherman, 1991).

Olsen and Buckingham (1989) prepared rate averages from the earliest Brevard County

record to 1986. The rate average and end point rates for all points in Brevard County vary from

each other by 3 cm. The average value of the derived end point rate and rate average value was

determined. This value for each monument was averaged with the rates immediately to the north

and south, if available, as recommended by Foster and others (2000).

Coastal Structures (SW) and Renourishment Projects (RN, RND)

Each monument location is reviewed for the presences of shoreline protection structures

(St. Johns County, 2002; Bodge and Savage, 1989). Structures will impede the transfer of

sediment from the foreshore to the dune system (Carter 1988; Gares, 1987; Nordstrom, 1994) and

prevent the Dune Height variable from reflecting geomorphic processes. The presence of






57


structures may impact the Beach Width Index, by steepening the beach and reducing the distance

to NGVD. This variable is recorded categorically as structures present or absent only.

Table 4-5. Brevard County shoreline position records
Monument Range Earliest Record Most Recent record

1-77 1877 2001

82-84,94 1877 1999

78-81, 85-93, 95-108 1877 1997

116-120, 147, 157, 164, 169 1878 1999

108-114, 122-143, 148-154, 1878 1997

156, 162-163, 165

159 1878 1993

155, 158, 160-161, 170 1878 1986

182,186,198 1879 1999

171,172, 174-180, 183-185, 1879 1997

188-197, 199,200

Source: http://hightide.bcs.tlh.fl.us/counties/HSSD/readme/read.mel

Renourishment of the coast during the study period will affect geomorphic variables, but is

initiated and made necessary by human presence on the coast. This variable is recorded

categorically as renourished or not (RN) and areas of renourishment are outlined in Chapter 3.

Brevard County has practiced dune renourishment (Olsen, 1989; Brevard County Comprehensive

Plan, 1988; Foster et al., 2000), which is recorded as a separate variable, RND.

Geographic Location (POS) and Orientation (OR)

The geographic location variable is a measure of the position of the center of the 9-ha

sample area from of the monument, along the coast. A smaller number indicates a location

further north in the respective county. This variable in conjunction with the analyses of data by

geomorphic unit provides spatial context the statistical analyses. In Brevard County the






58


dependent variable data are not available for Patrick Air Force base. Brevard County data were

considered as two separate areas; Cape Canaveral to the north point of PAFB, (monuments 1 to

71); and, south of PAFB to Sebastian Inlet (monuments 75 to 200). In St. Johns County

dependent and independent variables for the entire county are considered together and in separate

arrays representing the area north of St. Augustine pass (monuments 1 to 122) and Anastasia

Island (monuments 141 to 195). Using ArcGIS the orientation (OR) of the shoreline was digitally

obtained. Each 9-ha sample area was centered on the monument, using the meridian described

earlier. The axis of the meridian was oriented at right angles to the shoreline, determined from

the extent of the GIS land use coverage. Using the angle command the orientation of the leading

edge of the 9-ha sample was determined.

Distance (ACC), Direction (DACC) and Location (ROAD) of Access

The distance of the 9-ha sample area to the nearest access point to the mainland was

considered a potential determinant of development sequencing or geographic weighting, in that

sample areas closer to bridges or access point are likely to have developed before sample areas

further from access. The exact location of the monument was used to derive the distance to

access. In each county the location of causeways and access points was determined using GIS.

The DACC variable adds a direction component to the measurement of distance to the nearest

access point. A positive value represents that the nearest access is to the south and negative, to

the north of the monument.

In Brevard County there are five causeways. State Road 528 reaches the coast at Bennet

Causeway in Cape Canaveral, adjacent to monument 1. State Road 520 accesses the barrier

island between monuments 20 and 21. Pineda Causeway carries State Road 404 and reaches the

coast between monument 75 and 76. State Road 518 crosses the Indian River on Eau Gallie

Causeway at monument 105. The southernmost access to the barrier island in Brevard County is

US 192 at monument 123. In St. Johns County, monument 1 is considered the closest monument

to access to the north. At monument 35, Mikler Avenue also provides direct access to the west.






59


The bridge north of St. Augustine Pass provides access at monument 121 on US AIA. St.

Augustine Beach is provided access by the Bridge of Lions (State Road 214) and the State Road

312 bridge that reaches the coast at monument 140. State Road 206 provides access to Anastasia

Island at Crescent Beach at monument 174.

ROAD, or location of access in the 9-ha sample areas, was recorded using the DOQQ's in

the T3 period. The location of the shoreline parallel access is a measure of the potential for

development locations. This variable was weighted from a value of 1 to 4 using the location of

the shore-parallel access, shown in Figure 4-6. Location of the road in the seaward third, or first

100 m of the 9-ha sample area was designated a 3. The exception to the diagram below was the

presence of more than one shore parallel highway, which was designated as a 4.

Dynamic Geomorphology Variables

The dynamic geomorphology variables are a measure of the amount of change each

variable has experienced over the study period. Beach width is used to illustrate the concept the

net (BW,3.1) and total change (BW,o) variables (Figure 4-7). The calculated beach width for each

profile, for each time period is used to determine the net and total beach width changes. The net

change is calculated by subtracting first recorded width (BWI) from the most recent beach width

(BW,). A positive value over the study period indicates net accretion, or increase in the distance

to NGVD from the monument. The net change provides a measure that is an important indicator

of the 27-year pattern. This is the same method used to calculate the end point rate, a component

in the Long Term Shoreline change variable. In areas where continuous changes have occurred,

the net change shows the net effects regardless of the series of events, storm impacts or variation

in the times of year the data was collected. Using this variable, data anomalies are smoothed.

Beach width variations reflect areas along a barrier island that are more dynamic, those that erode

and recover more than adjacent areas. The total beach width change variable represents the total

changes in beach width for the entire time period.






60




Monument
Coastline
100m.
ROAD = 3



ROAD = 2



ROAD = 1

9-hectare sample area
Figure 4-6. Determination of highway location (ROAD) variable

Figure 4-7 shows the calculation of total beach width change. The net change from 1972

to 1997 (BW3.1) is 20 m for both examples, and is the total change for a. However, the total

change (BW,,,) is 40 m for profile b. Total change is the cumulative change from the initial data

year to the final year. The total beach width change value is always positive (or zero) because the

value is the sum of the change in the shoreline position of the edge of the beach each year.

Profiles that experience both erosion and accretion will have a much larger total beach width

change than net beach width change. The net variation and total variation in maximum dune

height is also calculated using the same methodology. Variations in the distance from the point

of maximum height to NGVD are also used as an indicator of a geomorphically dynamic area.

A factor for each of the geomorphic variables is developed using the Total and Net

changes. The factor is a ratio of the Net change to Total change. The Total change is an absolute

value, whereas the Net change value can be positive or negative. The Factor maximum value is

1.0 and minimum is -1.0. A Beach Width Factor (BWf) of 1.0 represents a beach width that has

accreted from the first measurement to the last (Figure 4-6a). A negative Beach Width Factor

indicates that the shoreline has retreated during the time period. In both Figure 4-8 a) and b) the

Net Beach Width (from the 1972 to 1997) is 20 m. The Total change is 20 m for a) and 40 for b).






61


The Beach Width Factor for situation a) is 1.0 indicating continuing accretion. In situation b) the

Beach Width Factor is 0.5. The positive value indicates net but not continual, accretion. A

negative Beach Width Factor indicates the Net change has been negative. A Beach Width Factor

of-l.0 indicates an eroding shoreline.

LAND
a) b)
Scale 1986
10m986

1972 1972

Total Total
1986 Beach Beach
Change Change
20 m 40m
1997 1997

OCEAN
Figure 4-7. Beach width dynamic geomorphology variable

Compilation of Data

Data from the FDEP website are used in raw form to avoid rounding, aggregation and

other errors. These data require considerable manipulation to render them suitable for analysis.

Data from each county must be reviewed for completeness of record. Data sets that contained

information only at 1,000-meter intervals or for a localized range of monument for each county

were not used. Data were imported and converted so that the geomorphic variables could be

extracted. Each monument placement was reviewed and adjusted in instances where the

monument was relocated. Using the methodology proposed by Rahn (2001) any monument that

had been moved in excess of 3m north or south of the original position was excluded. The 3m

dimension assumes that the profile continues to reflect the local topography. Monuments using

the same azimuth that were relocated landward were suitable for use, but only the portion of the

profile present in the earlier positioning of the monument was used.






62



Maximum
; dune height

1972 National
Geodetic
1 79 Vertical Datum
(NGVD)
Monument (NGVD)

maximum
dune height


(a) Distance to maximum dune height

(b)
WEST Beach width index (NGVD to monument) EAST

Figure 4-9. Profile revision diagram, monument moved landward (to west)

In the case where the revised monument position is west of the original position the profile,

data recorded after the repositioning are adjusted (Figure 4-9). Relocation landward results from

monument destruction from storms, coastal erosion, profile changes and construction at the

original monument location (Foster 2002, personal communication). Profile data recorded are

amended to reduce the monument to maximum dune height (a), and the beach width index

(NGVD to monument) (b), for consistency amongst all the data sets. The standard of 3m in

north-south variation is assumed not to necessitate amendments in dune height variables (Rahn,

2001). In cases where the maximum dune height occurs at the landward of the original

monument position, the maximum dune height recorded at or seaward of the original position is

used.

In the case where the revised monument position is seaward or east of the original position

the profile data recorded before the repositioning are adjusted (Figure 4-10). Relocation

landward occurs due to construction at the position of the monument and road realignments

(Foster 2002, personal communication). Profile data recorded before the repositioning of the

monument are amended to reduce the monument to maximum dune height (a) and the beach






63


width index (NGVD to monument) (b) for consistency amongst all the data sets. The standard of

3 m in north south variation is assumed not to necessitate amendments in dune height variables

(Rahn, 2001). However, in cases where the maximum dune height occurs at the monument, the

maximum dune height recorded at or seaward of the new position is used and the maximum

height to NGVD is amended.


Table 4-6. Sample data changes for landward (west) relocation of monument
1972 | 1972 data are unchanged

1979-Monument relocated landward (west) 10 m in 1979

Amend: (a) Monument to maximum dune height reduced 10
1986 m
Beach width index (NGVD to monument) reduced 10 m
Maximum dune height revised to the Maximum height at or
seaward of the original monument position

Amend: (a) Monument to maximum dune height reduced 10
1999 m
(b) Beach width index (NGVD to monument) reduced 10 m
(c) Maximum dune height revised to the Maximum height
at or seaward of the original monument position



Maximum
dun1 height
National
1979 Geodetic
SVertical Datum



maximum
dune height
-------- _----------_
(a) Distance to maximum dune height

(b)
Beach width index (NGVD to monument)
WEST EAST
Figure 4-10. Profile revision diagram, monument moved seaward (to east)






64




Table 4-7. Sample data changes for seaward (east) relocation of monument
1972 Amend:
Monument to maximum dune height reduced 10 m
Beach width index (NGVD to monument) reduced 10 m
Maximum dune height revised to the maximum height
seaward of the repositioned monument position


1979-Monument relocated seaward (east) 10 m

1986 1986 data are unchanged
1999 1999 data are unchanged


Monument data are provided in State Plane NAD 29 and was converted to NAD 83 to be

consistent with the projections of the DOQQ's and land use data in the GIS. Appendix E shows

the Brevard and St. Johns County monument position and profile details.

Development Variables

The future land use, units per hectare and percent of impervious areas adjacent to the

profiles are obtained using aerial photography and GIS. The exact location of the monument and

Northing and Easting State Plane coordinates are plotted on the aerials for each site. The

photographs show 400 m inland on average, and where the barrier island is narrow, this inland

extent will also show the sound or river. A 9-ha area centered at the monument is used to

determine the uses and impervious areas immediately adjacent to the monument. The centerline,

or meridian of the 9-ha sample area is centered at the monument.

The physical extent of development, defined as any building or impervious area, defines

the seaward extent of the sample area. For example, if buildings exist closer to the beach than the

monument is located, the sample area is aligned with the seaward extent of development. This

may be the case when the monument is located in the dunes beyond and landward of

development. The seaward extent of the sample area may extend beyond the monument. This

extent is determined by the most recent time period. The 9-ha square has dimensions of 300 m

inland from the monument and 150 m either side of the monument. The appropriateness of






65


adjacent areas to point or discrete data has been noted in Rahn (2001) and Mossa and McLean

(1997). In situations where monuments are placed precisely, the development variables in the 9-

ha sample areas will encompass the entire county coastline. However, the irregular spacing and

replacement of monuments causes the sample areas to be noncontiguous.

The areas unavailable for development and retained in their natural state, such as the areas

west of AIA in Guana River State Park, are excluded in the calculation of units per hectare and

percentage impervious area. The Intracoastal Waterway, canals or water bodies are also excluded

(Appendix D). Digital orthophotography was used for the Brevard and St. Johns counties in 1997

and 1999 and in the 1970s and 1980s variables were extracted from the 1:1200 aerial

photography. This photography and future land use data are analyzed in conjunction with the

monument locations using GIS.

Dwelling Units (UN) and Dwelling Units per Hectare (UH)

The number of units variable (UN) and the number of residential dwelling units per hectare

(UH) are derived for each monument with a continuous geomorphic record. These variables

include units of mobile homes, and multifamily units up to 8 units per building. The number of

units is determined from the aerial photography and field investigations. The number of hotel

rooms cannot be determined from the photography. Hotels, motels and condominiums are not

included in the calculation of units. These structures are included as commercial acreage in the

calculation by use. The number of units per hectare does not include any measure of commercial

activity.

Figure 4-11 shows that 18 units, in this example single-family residential, were recorded in

the 9-ha sample area for a UN of 18. The density is the number of units per hectares of

residential land. In this case if there are 3 hectares of residential land the 18 units in 3 ha

represents a UH of 6 units per hectare.






66


Table 4-8. Dependent (human/development) variable details
Dependent Variables Name
Total Number of Dwelling Units UN
Density of Dwelling Units per Hectare UH
Hectares of Impervious Area IMP
Percentage Impervious Area PIM
Hectares of Commercial Development C
(includes Hotels, multi-family over 6
units per structure, offices, port related)
Total Potential Units Adopted in Future FLU
Land Use Plan
Total Residential Density Adopted in FLUD
Future Land Use Plan
Total Potential Hectares of Commercial FLUC
Development Adopted in Future Land
Use Plan
Temporal Scale Name
Actual
1972 tl
1986 t2
1999 (1997 Brevard) t3
Dynamic
Change from 1972 to 1986 t2-1
Change from 1986 to 1999(1997 Brevard) t3-2
Change from 1972 to 1986(1997 Brevard) t3-1
Appendix A contains source and measurement data for each variable.

Impervious Area (IMP) and Percentage Impervious Area (PIM)

The impervious area and percentage impervious area are more complete measures of actual

development. Impervious areas impact the ability of the dune to act as a sediment store and

aeolian transport (Nordstrom, 1994; Nordstrum and McCluskey, 1985) and prevent the

absorption of water in storm events (Hall and Halsey, 1991). This research uses an adopted

impervious area assumptions for single-family homes. Stormwater runoff at the coast is a major

contributor to non-point source pollution and stormwater permits are required of all development

except single-family residential. The permits, issued by the St. Johns River Water Management

District in both Brevard County and St. Johns require that runoff be stored on site (Von der

Osten, 1993). Local county and municipal regulations mirror the requirement. The standard is

that the first 2.5 cm must be retained on site and the volume of runoff from a site must be no

greater than the runoff before development. The area of each structure and associated






67


impervious area, such as parking facilities, is calculated from the aerial photography using GIS.

The number of single-family units is converted to a standard impervious area. Florida

Stormwater Management professionals recognize 213.7 m2 per unit and 92.9 m2 per mobile

home as an estimate of impervious area, including buildings and driveways in the calculation of

fees (Sumwashe, 2000). In Brevard County the established Stormwater Management Utility

uses 232.3 m2 as a proxy for the impervious area for each single-family unit. The total recorded

impervious (IMP) area is converted to a percentage of the 9-ha area available for development

(PIM) adjacent to each monument.




































Figure 4-11. Determination of total units (UN) in 9-ha sample area






68


The use of the Stormwater management accepted single-family impervious area is

evaluated using GIS. The total area for each 9-ha sample area was compared to the amount of

impervious are that was estimated using the impervious area factor to evaluate the validity of the

estimated impervious area for single-family home sizes. In Ponte Vedra, in St. Johns County, it is

noted that original single-family structures present in the 1972 photography have been expanded

or replaced, resulting in an enlarged impervious area footprint. Conversely structures constructed

since the establishment of the Federal Emergency Management Agency FIRM maps in

designated "V" zones, must be elevated. The increased cost of construction for elevation of

structures also limits the impervious footprint. In Brevard County the existing single-family lot

sizes in Cocoa Beach west of Highway AIA, are small (less that 0.1 ha) and expansion of

residential structures, when constrained by lot size will be vertical and not impact the total

impervious area.

Future Land Use (FLU, FLUD, FLUC)

Land use designations are available from the adopted county Comprehensive Plans. The

comprehensive plans for each time period contain future land use designations for the entire

County. The amount of each land use category in the area immediately adjacent to the monument

is determined using the existing land use maps and GIS and converted to units per hectare for

each 9-ha area.

Table 4-9. Land use data availability by study area
Study Area Data Availability
Brevard County 1972 (adopted 1981)(FLUDI), 1989 (not available)
2000 (2010 horizon) (FLU3, FLUDo, FLUCo)
St. Johns County 1979 (FLUD,|), 1989 (FLUa, FLUDa, FLUCa)
2001 (2015 horizon) (FLU3, FLUD3, FLUCo)

The future land use designations in the first comprehensive plans adopted in the 1970's are

general and did not specify future land uses in sufficient detail for distinctions along the coast. In

1972 Brevard County adopted an open space plan (Brevard County Planning Department, 1972)

through a 1995 planning horizon, that was incorporated in the 1981 general future land use maps





69

for Brevard County (Brevard County Board of County Commissioners. 1981). Brevard County

has five incorporated coastal municipalities and Patrick Air Force Base. The 1981

Comprehensive plan included land use designations for all incorporated areas and was used to

determine the FLUDu Digital land use data from the 1988 plan (Brevard County Comprehensive

Planning Division, 1989) was not available for Brevard County. Digital information for the most

recent comprehensive plans was obtained from Brevard County, Cape Canaveral, Cocoa Beach,

Satellite Beach and Melbourne (FLU,, FLUDO and FLUC,). Indiatlantic is a small coastal

municipality and data were not obtained because it contained no monuments with continuous

geomorphic data.








i a 1r





Impervious
Footprint 1.4














Figure 4-12. Determination of total impervious area (IMP) in 9-ha sample area






70


The 1979 plan for St. Johns County contained detail from which a density (FLUDI) was

determined. Recent adopted plans have land use assigned to each parcel of property. In St. Johns

County digital existing land use was produced digitally in 1996 and contained less than 8.1

hectares of land on the coast with a revised land use designations from the 1990 Comprehensive

plan (Tim Brown, St. Johns County Planner, personal communication, 2001). These data were

used to determine the FLU2, FLUDO and FLUCa. In St. Johns County there is one incorporated

coastal municipality, St. Augustine Beach. Digital data were obtained for the 2001

comprehensive plan. The individual areas of future land use categories are calculated using

GIS. A range of units is traditionally provided for planning residential land use categories. The

midpoint of residential land use densities is used for this research. Commercial uses included

offices, tourist related uses, hotels, port commercial and retail. Public facilities uses were not

included in the commercial designation. Areas designated for future open space, recreation or

conservation used were not included as developable and removed from the total hectares

available. Figure 4-13 shows 5.49 hectares of low/medium residential land use and 0.36 hectares

of high-density residential land use. The mid point of the low/medium residential density is 4

du/ha allowing 22 potential units. The mid point of the high residential density land use is 10

du/ha, which results in 4 potential units, for a sample area total of 26 units. When divided by the

total residential hectares, the resulting density is 26 units in 5.9 hectares, or 4.4 du/ha (Figure 4-

14)

Application of Variables in Hypotheses

Hypothesis 1: Local geomorphologv impacts human variables at the same interval

Hypothesis la: The local geomorphology influences the actual development. This

hypothesis is illustrated by a relationship between actual geomorphology, and the human

variables at that time (Conway and Nordstrom, 2003; McMichael, 1977; Miller, 1980). Examples

of the hypothetical relationships between the 1972 geomorphology and the 1972 human variables

are shown below. The hypotheses would be the same for the two other discrete time periods.





71


COMMERCIAL
HIGH DENSITY Low/Med
RESIDENTIAL Residential 5.49
INSTITUTIONAL
S.LOW\MEDIUM
RESIDENTIAL
.,,;RIGHTS-OF-WAY
::: VACANT
i: : WATER

Permitted
Density (mid-
range)*Area=
26 Potential
Residential
Units

Figure 4-13. Determination of future land use total units (FLU) in 9-ha sample area


COMMERCIAL w/M
LowlMed
HIGH DENSITY
RESIDENTIAL Residential 5.49
RESIDENTIAL .




.. RIGHTS-OF-W.AY
SVACANT
W ATER

TOTAL UNITS
RESIDENTIAL "
HECTARES .
=4.4 Units per ...
hectare


Figure 4-14. Determination of future land use density of units (FLUD) in 9-ha sample area






72


Table 4-10. Hypothesis la, actual geomorphic and human variable relationships.
Actual Geomorphology Hypothetical Human Variable
(Each Time Period) Relationship (Same Time Period)
1972 1972
Beach Width Index (BW,1); Positive Impervious Area, (IMPt,),
Dune Height (DHi); Percent Impervious Area (PIM,i)
Distance Monument to Maximum Number of Dwelling Units
Dune Height (MDHi); (UN,), Dwelling Units per
Distance NGVD to Maximum Hectare (UH 1), Commercial
Dune Height (DHBWI) Hectares (C ,)
Long Term Shoreline Change (LT) Positive Impervious Area, (IMP,1-IMPt),
Percent Impervious Area (PIM,I-
PIMo) Number of Dwelling
Units (UNo- UNo), Dwelling
Units per Hectare (UH,1- UHo),
Commercial Hectares (C ,- C3)

Hypothesis lb: The local geomorphology influences the land use control decision-making.

This hypothesis proposes that future land use plans are developed by considering

geomorphological conditions (Hails, 1977). The hypothetical relationships between the 1999

geomorphology in St. Johns County and the 2001 proposed future land uses for the 2015 horizon

are shown below. The hypotheses would be the same for the two other discrete time periods.

Table 4-11. Hypothesis Ib, actual geomorphic and future land use variable relationships.
Actual Geomorphology Hypothetical Land Use Control Variable
(Each Time Period) Relationship (Adopted For Each Time
Period)
1999 2001
Beach Width Index (BWo); Positive Future Land Use total units
Dune Height (DHo); and density (2015 horizon)
Distance Monument to Maximum (FLUt), (FLUDo)
Dune Height (MDHo);
Distance NGVD to Maximum Dune
Height (DHBWo)
Long Term Shoreline Change (LT) Positive Future Land Use Density
(FLUt2, FLUo), (FLUDt,-
FLUDG)

Hypothesis 2: The dynamic geomorphologv impacts human variables

Hypothesis 2a: The dynamic geomorphology indicators influence the actual human

variables. Local coastal geomorphology that varied over decades indicating a dynamic area

would be negatively correlated to human variables (Lundberg and Handegard, 1996; McMichael,






73


1977; Miller, 1980). The example below shows that the smaller the change in geomorphic

variable from one time period to another, the more suitable for higher levels of human

development or hypothetically a positive relationship. Also the larger the geomorphological

factor variable the more suitable for more intense human development (number of dwelling units,

impervious area). A low factor value represents a large difference in the net and total change and

so a dynamic area. A negative factor value indicates a lower dune or decreasing beach width, for

example.

Table 4-12. Hypothesis 2a, dynamic geomorphic and human variable relationships.
Dynamic Hypothetical Human Variable
Geomorphology Relationship (Change Over Period)
(Over Entire Period)
Change in Beach Width Index (BWa.1, Impervious Area, (IMPI-
BW,3-2,BWt., BW,,); Negative IMPt), Percent Impervious
Change in Dune Height (DHa.1, DH,3.2, Area (PIMI-PIMt3) Number of
DH3-.1 DH,,); Dwelling Units (UN,|- UN,),
Change in Distance Monument to Dwelling Units per Hectare
Maximum Dune Height (MDHt2-1, (UHt,- Uht), Commercial
MDH t3-2, MDH3.1 MDHt,o); Hectares (C11- C,3)
Change in Distance NGVD to
Maximum Dune Height (DHBWa.
I, DHBWt3. 2DHBW3-1, DHBW,,);
Factor Variable Positive Impervious Area, (IMPi-
Beach Width Index Factor, (BWf); IMP,3), Percent Impervious
Dune Height Factor, (DHf); Area (PIMI-PIM3) Number of
Distance Monument to Maximum Dwelling Units (UN,1- UN,3),
Dune Height Factor (MDHf); Dwelling Units per Hectare
Distance NGVD to Maximum Dune (UHt,- UH,3), Commercial
Height Factor (DHBWf) Hectares (C,- C,3)

Hypothesis 2b: The dynamic geomorphology indicators influence the land use control

decision-making. This hypothesis proposes an adaptation of Bush and others (1999) with future

land use outcomes as the result of the characteristics of the physical environment. The example

below shows that the smaller the change in geomorphic variable from one time period to another,

the more suitable for higher adopted future total units and densities. Also the larger the

geomorphological factor variable the more suitable for higher adopted future total units and

densities.






74


Table 4-13. Hypothesis 2b, dynamic geomorphic and future land use relationships.
Dynamic Hypothetical
Geomorphology Relationship Land Use Control Variable
(Over Entire Period)
Change in Beach Width Index Negative Future Land Use Density
(BW2.1, BW,3.2,BW,3.1 BW,ot); (FLUt, FLU,3), (FLUD,i-
Change in Dune Height (DH2.1, FLUD,)
DH,3.2, DH,3- DH,,,);
Change in Distance Monument to
Maximum Dune Height (MDH2-
i, MDH .-2 MDH3.- MDHto,);
Change in Distance NGVD to
Maximum Dune Height
(DHBW2.1, DHBWot.2 DHBW3.
1. DHBWt,,);
Factor Variable Future Land Use Density
Beach Width Index Factor, (BWf); Positive (FLUD,1- FLUD,3)
Dune Height Factor, (DHf);
Distance Monument to Maximum
Dune Height Factor (MDHf);
Distance NGVD to Maximum Dune
Height Factor (DHIBWf)


Hypothesis 3: There are temporally lagged relationships between the actual and dynamic

Reomorphologv variables and the human variables. This hypothesis contemplates that

geomorphology in one time period will influence human variables in later time periods

(Nordstrom, 1987; Van Der Wal, 2004). The example below shows a positive relationship

between the dune height in 1972 and the human variables in later time periods. The second

example shows the wider the beach width in 1986 the more stable the coastal environment and

therefore the more suitable for greater a impervious area and dwelling units in the later time

period.

Hypothesis 4: The dependent variables will have different relationships with the independent

variables in the two separate study areas. The explanatory power of the individual variables will

be different in each part of the coastline (Byrnes et al., 1995). For example, the dune height in

Brevard County will not have the same relationships with the human variables are the dune height

in St. Johns County. The regression coefficients and significant variables for each county will be

different.






75


Table 4-14. Hypothesis 3, lagged geomorphic and human variable relationships.
Actual Geomorphology Hypothetical Lagged Land Use Control Variable
(For 3 Time Periods) Relationship
1972 Dune Height (DH,|) Relationship with 2015 Future Land Use Density
variable in later time (FLUt, FLUDo), 1986 and 1999
period Impervious Area, (IMPa, IMP,),
1986 and 1999 Percent Impervious
Area (PIMa, P1Mt3,) 1986 and
1999 Number of Dwelling Units
(UN2, UN3), 1986 and 1999
Dwelling Units per Hectare (UHt2
UHo), 1986 and 1999 Commercial
Hectares (C,2 C,3)
1986 Beach Width Index Relationship with 1999 Impervious Area, (IMPo),
(BWa) variable in later time 1999 Percent Impervious Area
period (PIMo) 1999 Number of Dwelling
Units (UNo), 1999 Dwelling Units
per Hectare (UH,3), 1999
Commercial Hectares (Co)


Table 4-15. Hypothesis 4, variable interactions by jurisdiction
Actual Geomorphology Hypothetical Land Use Control Variable of that
(For 3 Time Periods) Relationship County
Brevard County Dune Height Varies-different from Brevard County Future Land Use
(DHt2_-DHo.)t St. Johns County Density (FLUa. FLUo), (FLUDI-
FLUD,3) Brevard County Impervious
Area, (IMPf,-IMP,3), Brevard County
Percent Impervious Area (PIM,,-PIM3)
Brevard County Number of Dwelling
Units (UN,i- UNo), Brevard County
Dwelling Units per Hectare (UHI-
UH,), Brevard County Commercial
Hectares (C,I.Co)
St. Johns County Dune Varies-different from St. Johns County Future Land Use
Height (DHt-I-DHt3.i) Brevard County Density (FLUa. FLU3,), (FLUD,,-
FLUDo) St. Johns County Impervious
Area, (IMP,,-IMP3), St. Johns County
Percent Impervious Area (PIMI-PIMo)
St. Johns County Number of Dwelling
Units (UN,i- UNo), St. Johns County
Dwelling Units per Hectare (UH,I-
UHo), St. Johns County Commercial
Hectares (Cn,.C,3)


Data Analyses

The 34 dependent and 43 independent variables were assembled in a database for analyses.

Statistical analyses were performed using the NCSS statistical package. Descriptive statistics for






76


each variable, for both Brevard and St Johns counties, were developed. The lack of normality

noted in the independent geomorphic variables prompted further analysis by geomorphic unit.

Brevard County was divided north and south of Patrick Air Force Base, and by orientation. St.

Johns County data were divided by geomorphic unit. The county was divided into two areas -

Ponte Vedra to Vilano Beach, and Anastasia Island (St. Augustine Beach to Matanzas Inlet). The

Summer Haven monuments (199 to 208) south of Matanzas inlet were not included.

The importance of spatial variation of variables along the coast is captured utilizing spatial

location of the 9-ha sample areas. The statistical inferences determined by the variables cannot

be isolated without consideration of the spatial implications (Burt and Barber, 1996;

Fotheringham and Brunsdon, 2004). The variables ACC, DACC, and POS serve as a proxy for

location. The variable POS is the distance along the coast from north to south. The influence of

the spatial dimension is further expanded by the distance to access (ACC) and direction and

distance to access (DACC) variables. These variables are weighted forms of location of the

sample area. ACC is a linear measure of the distance north or south, to the closest access or

bridge to the barrier island. In northern St. Johns County access is north into the adjacent county.

There is no access to the west between the county boundary and the Vilano Beach bridge at St.

Augustine Pass. In Brevard County access is limited to causeways to the barrier islands. The

DACC variable adds a direction component to the distance to the access point. A negative

DACC value represents that the nearest access point is to the south of the monument. The

orientation of the seaward axis of the 9-ha sample area to north (OR) is a further spatial derivative

to enhance the statistical analyses. St. Johns County is also divided by geomorphic unit into two

parts to recognize the importance of separate analyses for geographically distinct areas.

Geographically weighted regression can also be considered for the evaluation of variables at

varied spatial scales, from global, regional and local (Mei et al., 2004). This research does not

consider what has been defined as mixed geographically weighted regression.






77


Row-wise Spearman Rank Correlations were performed for both St. Johns and Brevard

County. This methodology was selected to evaluate the continuous and discrete data. Nominal

data includes that presence of renourishment (RN), dune renourishment in Brevard County

(RND), structures (SW) and State erosion designation (ER). The Spearman Rank correlation is an

indicator of a simple relationship by rank order, so that a positive relationship between variables

shows that the highest measure of the independent variable is associated with the highest measure

of the dependent variable. This indicator of monotonocity does not distinguish linear from non-

linear relationships because the ranked data provide a directional indicator of the variable

association but not an indicator of distance between variables. All dependent and independent

variables were analyzed.

The non-parametric statistics provide general bivariate comparisons for the direction of

variable association. Multiple regression analyses are used to evaluate the multiple interactions

of variables and to measure and model the dimensions of the impacts of variables. Independent

variables were transformed and integrated (Appendix B). The categorical data, such as the

presence of absence of structures and the designation of erosion concern (ER) determined by the

Clark (1999) were used as dummy variables for analyses (Appendix B). Other dummy variables

include the presence of renourishment (RN), dune renourishment (RND, Brevard County only),

and structures (SW). This portion of the data analyses enables the use of the ordinal variables to

be evaluated for interaction with other variables more appropriately than in the non-parametric

statistical analyses. A stepwise analysis of each dependent variable was performed. Once the

relevant variables were isolated, multiple regression analyses were performed for all the Brevard

County sample areas, the entire St. Johns County data and the St. Johns County data by

geomorphic area.

Methodology Implications

Both the number of units and density changes are sensitive if the numbers (UN, UH) and

available hectares are small. For example in St. Johns County at monument 184 there was a






78


decrease of 4 units (UN), from 1972 to 1997 with a corresponding increase in impervious area

(PIM) increase of over 90 percent. This was due to the small area available for development and

the sensitivity of using the percentage of available area. Similarly the methodology is sensitive to

data misclassification. When redevelopment occurs and residential areas are converted to other

uses, the decrease in units (UN, UH) will be replaced by increased impervious area (IMP, PIM)

and hectares of commercial (C). In St. Johns County monument (187) was revised in 1986 after

GIS investigation of the percent impervious (PIM), which was over 100, and further GIS

investigations showed miscoding of impervious area. This served as a methodological check. In

Brevard County at monuments 21 and 35 the PIM was over 100, by less than 1 percent. Further

review indicated that in this area small lots with two story single-family structures and the

standard residential hectare estimate had overestimated residential impervious area. These areas

were adjusted to reflect a limit at 100 percent.














CHAPTER 5
ANALYSES AND RESULTS

The descriptive statistics of the independent and dependent variables for each County are

provided in Appendix G. The results of the non-parametric statistical analyses are shown in

Appendix H. St. Johns County variable plots of beach width (Figure 5-1) and the variation in

long-term shoreline change and independent variables (Appendix I) illustrate the potential for

variables to be more appropriately analyzed by smaller geographic unit. St. Johns County was

divided into two areas Ponte Vedra to Vilano Beach, and Anastasia Island (St Augustine Beach

to Matanzas Inlet). Appendix I includes the graphic representation of variables by county that are

not included in this chapter. The regression analyses and results are shown in Appendix J.

Independent Variable Characteristics

Appendix G contains the independent geomorphic variable descriptive statistic summary.

Brevard County data were from 1972 (,1), 1986 (2) and 1997 (o). St Johns County data were

collected for 1972 (,), 1986 (2) and 1999 (,). The variables are time specific (tl, t2, t3) and

dynamic (t2-l, t3-2, and t3-0).

Beach Width (BW)

The Brevard County beach width values of the 9-ha sample areas are normally distributed

in 1972 and 1997. The number of monuments with data decreases from 147 points in 1972 to

140 in 1997 indicating monument replacement. The beach is wider between Satellite Beach and

Indiatlantic (monuments 110 to 120), in the area south of Cocoa Beach and in southern Brevard

County (Table 5-1). Changes in beach width over time are more extreme in northern Brevard

County, north of monument 60, particularly adjacent to the Port Canaveral Inlet, where the jetties

have influenced accretion. The average beach width is highest in 1986 at 108.5m, but in the same

year a minimum beach width of 35.7m was also recorded. The maximum beach width increases


79






80


over time from 108.5m in 1986 to 227.2m in 1997. The negative value for mean beach width

from 1986 to 1997 of-3.4m illustrates that the beach width on average decreased from 1986 to

1997. The absolute change (BWo,) has a mean of 28.0 m. However the range of BWot is large,

from just over a meter to over 300m. The negative values for the minimum beach width indicate

that there are areas where the beach width decreased in each of the time periods. The BW

descriptive statistics in Brevard County indicate that there is no simple trend in the geomorphic

variable. North of Patrick Air Force Base (monument 60), Brevard County is more dynamic,

with more extreme temporal change. The beach is consistently wider in 1986 in Brevard County,

south of Patrick Air Force Base. The BW variation, indicated by the range in values, increases

over time.

Beaches in St. Johns County (Figure 5-1) are widest and show more variation from 1972 to

1999 on Anastasia Island. Trends are similar to Brevard County, with accretion in 1986 north of

St. Augustine Pass. In the Vilano Beach area the 1999 beach width is the most narrow. Beach

width rapidly increased at monument 121at the north jetty at St. Augustine pass. Matanzas Inlet

has rock revetments adjacent to A1A, but no jetties. The sample areas south of Matanzas Inlet

have the narrowest beaches in St. Johns County. The rocks that were adjacent to monument 141

in St. Augustine Beach in 1999 were exposed. In St Johns County BW accretion north of St

Augustine Inlet from 1972 to 1986, is similar to Brevard County.

Maximum Dune Height (DH)

The highest point recorded on each of the coastal profiles is the maximum dune height

(DH), and this may occur at the monument. In Brevard County the maximum dune height

increases southward (Figure 5-2). South of Port Canaveral Inlet in Cocoa Beach the maximum

dune height is 3 to 4m, compared to over 6m south of monument 150. The dune heights are most

dynamic at Cocoa Beach and Patrick Air Force Base. The average dune height increases from

5.0m in 1972 to 5.1m at 1997 and the DHRI and DH0 are normally distributed (Table 5-2).






81


Table 5-1. Descriptive statistics, beach width (BW)
Standard Kolmogorov-
Count Mean Deviation Min. Max. Smirnov 0.05 Normality
Beach Width (Brevard County)
BWt, 147 98.8 27.6 41.4 149.9 0.0399 0.073 Accept
BWa 141 103.6 28.9 35.7 198.7 0.0833 0.074 Reject
BWt 140 101.8 31.9 40.6 267.8 0.0651 0.075 Accept
BWa.i 142 5.5 24.1 -149.9 126.6 0.1947 0.074 Reject
BW,3-2 138 -3.4 28.4 -163.8 155.3 0.1968 0.075 Reject
BW,3.i 143 2.2 29.2 -148.5 196.7 0.2090 0.074 Reject
BW,, 138 28.0 39.7 1.2 305.1 0.2589 0.075 Reject
BWf 138 0.1 0.7 -1 1 0.1200 0.075 Reject
Beach Width (St. Johns, Entire County)
BW,| 165 79.7 19.6 35.4 140.6 0.1784 0.069 Reject
BWt2 167 95.4 34.8 30.4 202.8 0.2011 0.068 Reject
BW3 165 86.3 37.6 30.9 198.5 0.2247 0.069 Reject
BWt2.1 164 15.4 20.1 -17.1 80.1 0.1141 0.069 Reject
BWt3.2 165 -9.7 14.8 -65.1 45.4 0.0761 0.069 Reject
BWt3.1 163 5.3 23.0 -55.7 76.1 0.1572 0.069 Reject
BWot 162 32.8 21.4 2.8 133.2 0.1386 0.069 Reject
BWf 162 0.01 0.7 -1.0 1.0 0.0966 0.069 Reject
Beach Width (St. Johns, North 1 to 121)
BW,, 111 71.8 8.3 49.0 99.1 0.0851 0.084 Reject
BWe 110 81.4 117 58.3 139.5 0.0680 0.084 Accept
BW, 110 68.7 12.6 44.9 132.7 0.1008 0.084 Reject
BWt2. 110 9.7 12.5 -17.1 68.0 0.0809 0.084 Accept
BW3.2 110 -12.7 13.4 -65.1 45.4 0.1303 0.084 Reject
BW,.1 110 -2.9 12.6 -29.4 35.2 0.0870 0.084 Reject
BW,, 110 27.8 17.7 2.8 133.2 0.1282 0.084 Reject
BWf 110 -0.2 0.6 -1.0 1.0 0.0833 0.084 Accept
Beach Width (St. Johns, Anastasia Island, 141 to 195)
BWt, 43 106.1 16.2 62.7 140.6 0.0759 0.134 Accept
BW, 46 140.4 31.5 49.4 202.8 0.0645 0.129 Accept
BW, 46 136.6 32.5 63.9 198.5 0.0645 0.129 Accept
BWt2- 43 35.9 22.2 -10.7 80.1 0.0634 0.134 Accept
BWt3-2 46 -3.8 17.2 -50.5 36.0 0.0862 0.129 Accept
BW,3.- 43 31.2 24.8 -42.3 76.1 0.0996 0.134 Accept
BWto 43 49.7 22.0 11.7 102.2 0.0940 0.134 Accept
BWf 43 0.6 0.5 -1.0 1.0 0.2310 0.134 Reject












200 -0




150 .- .. --
Monument 121


.1 100 3 .







Beach Beach Anastasia Island
M X








5 10 15 20 25 30 35 40 45 50 55 60 65 70
50 --- -
St. Monument 141






Monument 1 Distance Alongshore from Monument I (km) Monument 198

X 1972 Beach width 0 1986 Beach width 1999 Beach width

Figure 5-1. St. Johns County beach width variations, 1972-1999, (BW,I, BWa, BW3)




3J





300
Monument
immediately adjacent Although beach width varies
250 to Cape Canaveral .. alongshore, the variation between-the
has experienced 1972, 1986 and 1997 points at each
-accretion monument, indicates a dynamic area
200

Melboume
S150 atrick AFB Beach
150 .


100 1 .



Cocoa Satellite
Beach Beach Indialantic


10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
Monument Number

X 1972 Beach width n 1986 Beach width 1997 Beach width


Figure 5-2. Brevard County beach width variations, with trend 1972-1997, (BWI, BWa, BW3)






84




Table 5-2. Descriptive Statistics, maximum dune height (DH)
Standard Kolmogorov-
Count Mean Deviation Min. Max. Smirnov 0.05 Normality
Maximum Dune Height (Brevard County)
DHI 136 5.0 1.0 2.6 7.2 0.0623 0.076 Accept
DH, 131 5.0 1.0 3.0 7.3 0.0559 0.077 Accept
DHU 131 5.1 0.9 3.0 7.4 0.0781 0.077 Reject
DHu.1 129 0.01 0.7 -5.6 3.3 0.1874 0.078 Reject
DH,3-2 128 0.2 1.0 -2.3 6.8 0.2959 0.078 Reject
DHt., 125 0.1 0.4 -1.4 1.4 0.0875 0.079 Reject
DHto 125 0.7 1.2 0 10.9 0.2851 0.079 Reject
DHf 121 0.2 0.7 -1 1 0.1625 0.079 Reject
Maximum Dune Height (St. Johns, Entire County)
DH,, 170 5.5 2.0 2.6 10.3 0.0922 0.068 Reject
DHe 169 5.6 1.8 3.0 10.2 0.1172 0.068 Reject
DHO3 169 5.8 2.0 3.0 10.2 0.0998 0.068 Reject
DHa-. 170 0.1 1.3 -6.35 8.1 0.2879 0.068 Reject
DHt3-2 170 0.2 1.1 -5.00 9.1 0.2569 0.068 Reject
DH.-i 170 0.3 1.6 -6.4 9.1 0.2572 0.068 Reject
DH,,, 170 0.9 1.5 0.02 9.1 0.2731 0.068 Reject
DHf 170 0.1 0.8 -1.0 1.0 0.1816 0.068 Reject
Maximum Dune Height (St. Johns, North, I to 121)
DHt1 111 5.8 1.8 3.3 10.3 0.1017 0.084 Reject
DHa 110 5.8 1.8 3.3 10.2 0.1324 0.084 Reject
DH,3 110 5.9 2.0 3.2 10.2 0.1451 0.084 Reject
DHa.- 111 -0.03 0.7 -6.4 1.8 0.3150 0.084 Reject
DHt3.2 111 0.2 0.9 -1.0 9.1 0.2898 0.084 Reject
DHot3- 111 0.1 1.2 -6.4 9.1 0.2729 0.084 Reject
DHto, 111 0.5 1.1 0.02 9.1 0.3152 0.084 Reject
DHf 111 0.0 0.8 -1.0 1.0 0.1728 0.084 Reject


Table 5-3. Descriptive Statistics, maximum dune height (DH), Anastasia Island
Standard Kolmogorov-
Count Mean Deviation Min. Max. Smimov 0.05 Normality
Maximum Dune Height (St. Johns, Anastasia Island, 141 to 195)
DHe 48 5.1 2.4 2.6 9.6 0.1078 0.127 Accept
DH, 48 5.5 1.8 3.0 9.5 0.0906 0.127 Accept
DH3 48 5.9 1.7 3.0 9.5 0.0764 0.127 Accept
DH.a- 48 0.4 2.1 -5.0 8.1 0.2930 0.127 Reject
DH3-2 48 0.4 0.9 -2.7 2.4 0.1630 0.127 Reject
DH-3. 48 0.8 2.1 -5.0 6.9 0.1670 0.127 Reject
DHt 48 1.7 2.0 0.1 9.5 0.1848 0.127 Reject
DHf 48 0.3 0.8 -1.0 1.0 0.1961 0.127 Reject




Full Text
31
exhibit) and precipitation (Carter, 1988). The study areas experience winds strong enough to
sustain the coastal dunes. This wind regime is conducive to dune stability. The beach gradient is
gentle and suitable for both barrier island formation and dune formation. Dunes throughout
Florida have formed as wind transports sand from the beach face inland. Vegetation traps sand
by causing the wind speed to drop and deposit the wind blown or aeolian sand movement. In
Florida sea oats are present along the coast. Sea oats are protected by law and cannot be removed
(Florida Statutes, Chapter 370.041). The intent of this requirement is to recognize the importance
of this hardy dune plant in establishing, and more importantly stabilizing Floridas dune system,
which provides the first line of defense from storm and hurricane conditions. Webb et al. (1997)
attribute dune removal to increased destruction of buildings along the panhandle of Florida during
Hurricane Opal in 1995. Dune height and gradient is a function of sediment. Foster et al. (2000)
attribute the gentle gradients on Anastasia Island to the fine quartz, compared to the relatively
steep dunes in northern St. Johns County that are comprised of sand and shell particles (Mossa,
1993).
The broader barrier islands of the Florida coasts exhibit beach ridges. Beach ridges are a
series of parallel ridges and swales. Ridges represent progradation seaward or parallel to the
coast (Johnson and Barbour, 1990) and may be truncated or eroded by more recent events. There
are four areas exhibiting beach ridges on the Florida Gulf coast (Schwartz and Bird, 1985) and
beach ridges are present at Cape Canaveral and on Anastasia Island in St. Johns County (Stapor
and May, 1982). Field (1974) estimates that Cape Canaveral beach ridge deposition took place
30,000 to 35,000 years BP.
Tide, Wave and Longshore Drift Characteristics
Tides in the study area are semidiurnal. The mean tidal range is 1.4 m (Foster et al., 2000)
and the spring tidal range is 1.6 m. The average wave height at the Melbourne Beach wave gauge
in Brevard County is 1.01 m, with an average wave period of 6.3 seconds. The prevailing wave
direction is east-northeast (Olsen, 2003). In St. Johns County the mean significant wave height is


196
GILES, R. T., and PILKEY, O. H. Sr., 1965. Atlantic beach and dunes sediments of the
southeastern United States. Journal of Sedimentary Petrology, vol. 35 pp. 900-910.
* GOLDBERG, E. D., 1994. Coastal Zone Space. Prelude to Conflict? UNESCO Publishing,
Paris, 138 pp.
GUAN-HONG, L., NICHOLLS, R. J., and BIRKEMEIER, W. A., 1995. A conceptual
fairweather-storm model of beach nearshore profile evolution at Duck, North Carolina,
USA. Journal of Coastal Research, vol. 11, no. 4, pp. 1157-1166.
HAGGETT, P., & CLIFF, A. D., & FREY, A., 1977. Locational Analysis in Human Geography.
Edward Arnold Publishers Ltd., London, 339 pp.
HAILS, J. R., 1977. Applied geomorphology in coastal zone planning and management, pp. 317-
365, in Hails, J. R., eds., Applied Geomorphology, Springer-Verlag, Berlin, 372 pp.
HART, D., 2000. Acquisition and integration of digital parcel mapping to support coastal
management along the Lake Michigan coast of Wisconsin. University of Wisconsin Sea
Grant Institute, Madison, WI. 43pp.
HESP, P., 1988. Surfzone, beach, and foredune interactions on the Australian south east coast.
Journal of Coastal Research, vol. 3, pp. 15-25.
H. JOHN HEINZ CENTER, 2000. The Hidden Costs of Coastal Hazards. Island Press,
Washington DC., 220 pp.
HOOKE, J. M. 1999. Decades of change: contributions of geomorphology to fluvial and coastal
engineering and management. Geomorphology, vol. 33, pp. 373-389.
HOUSTON, J. R., 1995. Beach Nourishment. Shore and Beach, January, pp. 21-24.
HOYT, J. H., 1967. Barrier island formation. Geol. Soc. of America Bulletin, vol. 78, pp. 1125-
1136
JACOBS, M. A., 1993. Tropical cyclones, hurricanes and the North Atlantic Oscillation NAO: A
historical and spatial survey. Masters Thesis, University of Florida, 145 pp.
KAUFMAN, W., and PILKEY, O., Jr., 1983. The Beaches are Moving: the Drowning of
Americas Shoreline. Duke University Press, Durham, N. C., 336 pp.
KOSTOF, S., 1991. The City Shaped, Urban Patterns and Meaning through History. Thames and
Hudson, London, 352 pp.
KRIESEL, W., and HARVARD, J., 2001. The role of GIS in estimating coastal hazard impacts
on real estate markets: results of a nation-wide survey. Proceedings of the 2nd Biennial
Coastal GeoTools Conference, Charleston, SC.
LANNON, H. J. L., and MOSSA, J., 1997. Coastal Geography of Central Atlantic Florida.
National Council for Geographic Education, In Growth, Technology and Geographic
Education in Central Florida: Images and Encounters, Oldakowski, R., Molina, L., and
Purdum, B., Editors, pp. 97-110.


12
determine the sequence of development between 1947 and 1994 (Essex and Brown, 1997).
Originally low-density development spread along the coastal strip (suburban style) in the 1980s.
Photography was combined with planning documentation and field evaluations.
Table 2-2. Use of aerial photography in coastal geomorphology
Geomorphic changes
Crowell et al., 1999; Davis, 1997; Dean and
Malakar, 1999; Dolan et al., 1991; Kaufman and
Pilkey, 1983; Stanczuk, 1975; Theiler and
Danforth, 1992.
Human impacts
Carter and Woodroffe, 1994; Hails, 1977;
Nordstrom, 1996; Essex and Brown, 1997; Dean
and Donohue, 1998
Measurement of
urbanization
El-Raey and Nasr, 1996; Essex and Brown, 1997;
Hart, 2000;Vernberg et al., 1996.
Beach Profiles and Applicability
Beach profile data may be used for various purposes, from descriptive (Stone et al., 1985;
Stone and Salmon, 1988) to highly quantitative analyses (Chiu, 1986; Guan-Hong et al., 1995;
Hesp, 1988). The profile shape and form indicates the stability of the coastal area and its potential
suitability for development. Combining aerial photography and beach profiles provides a
valuable combination of cross-sectional and planform perspectives (Al Bakri, 1996; Stanczuk,
1975; Wright, 1991). The stability of the beach profile depends on wave and wind conditions,
sediment size and beach slope, in the short term; and depends on sea level, sediment supply,
littoral transport, and storm frequency in the long term (Reesman, 1994). Table 2-3 shows the
geomorphic and human variables evaluated as components of beach profile characteristics.
Beach profile data have been used to evaluate the impacts of human changes to the coast at
various scales. Wrights (1991) work at the large scale (spanning the states of New Jersey, North
Carolina and South Carolina) measured the dry beach width from surveyed profiles and used it as
a proxy for the portion of the beach that is continuously available for recreational use. It
quantified the value society puts on the recreational amenity, and used dry beach width to
compare the impacts of stabilized shorelines. He determined that the dry beach width was


LIST OF TABLES
Table page
2-1. Importance of scale in spatial and temporal research 7
2-2. Use of aerial photography in coastal geomorphology 12
2-3. Beach-profile research; geomorphic and human variables 14
2-4. Coastal and growth management legislation that impacts the Florida coast 19
3-1. Hurricane and tropical storm activity in the study areas 34
3-2. Renourishment projects in Brevard County during 1972 to 1997 study period 42
3-3. Recent renourishment projects, Brevard County 43
3-4. Recent renourishment projects, St. Johns County 43
4-1. Geomorphic data availability by study area 47
4-2. Independent (geomorphic) variable details 47
4-3. Profile measurement metadata, monuments 1 to 200, Brevard County 48
4-4. Profile measurement metadata, monuments 1 to 209, St. Johns County 51
4-5. Brevard County shoreline position records 57
4-6. Sample data changes for landward (west) relocation of monument 63
4-7. Sample data changes for seaward (east) relocation of monument 64
4-8. Dependent (human/development) variable details 66
4-9. Land use data availability by study area 68
4-10. Hypothesis la, actual geomorphic and human variable relationships 72
4-11. Hypothesis lb, actual geomorphic and future land use variable relationships 72
4-12. Hypothesis 2a, dynamic geomorphic and human variable relationships 73
4-13. Hypothesis 2b, dynamic geomorphic and future land use relationships 74
viii


172
Table H-12. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach, Monument
1 to 120), Maximum Dune Height to NGVD (DHBW)) at 0.05 significance
DHBW,,
DHBWa
DHBWa
DHBWa.,
DHBWaa
DHBWa.,
DHBWlo,
DHBWf
UN
-
-
0.3591
-
-
0.3510
-
-
UNa
-
-
0.3191
-
-
0.3507
-
0.0248
UN,3
-
-
-
-
-
-
-
-
UNa.,
-0.3048
-0.2725
-
-
-
-
-
UNaj
-
-
-0.3720
-
-
-
-
-
UN, 3.,
-0.3023
-0.3344
-0.3945
-
-
-
-
-
UH
-
-
-
-
-
-
-
-
UHq
-
-
-
-
-
-
-
-
UH,3
-
-
-
-
-
-0.2549
-
-0.2466
UHq.,
-
-
-
-
-
-
-
-
UH.2
-
-
-0.4306
-
-
-0.3922
-
-0.3813
UH,3.,
-
-
-0.4148
-
-
-0.4004
-
-0.3872
IMP,,
-
-
0.3673
-
0.2511
0.3667
-
0.2763
IMPe
-
-
0.3617
-
-
0.3432
-
0.3958
IMP,,
-
-
-
-
-
-
-
0.2862
imp12.,
-
-
-
-
-
_
-
_
IMPa.:
-
-
-
-
-
-
-
-
IMPo.,
-0.2455
-
-
-
-
-
-
-
PIM
-
-
0.2827
-
-
-
-
-
PIMa
-
-
-
-
-
-
_
-
PIMa
-
-
-
-
-
_
_
_
PIMa.,
-
-
-
-
-
-
-
-
PIMa.2
-
-
-0.2466
-
-
-
-
-
PIMa-i
-
-
-
-
-
-
-
-
ACC
-
-
-
-
-
-0.3653
-
-0.4091
DACC
-
-
-
-
-
-
-
-
POS
-
-
-0.5142
-0.2427
-0.3763
-0.6256
-
-0.6202
Q,
-
-
0.2976
-
-
0.3316
-
0.3053
Ca
-
-
-
-
-
-
-
0.2571
Ca
-
-
-
-
-
-
-
0.2604
02-1
-
-
-
-
-
-
-
-
Ct3-2
-0.2505
-
-
-
-
0.2549
-
0.2781
Q3-I
-
-
-
-
-
-
-
-
FLUD
-
-
-0.3207
-
-0.2841
-0.4695
-
-0.4652
FLUa
-
-
-
-
-
-
_
_
FLUDa
-
-
-
-
-
_
_
_
FLUCq
-
-
-
-
-
-
-
_
FLUa
-
-
-
-
-
-
-
_
FLUDa
-
-
-0.2543
-
-
-0.3764
-
-0.3288
FLUCa
-
-
-
-
-
-
-0.2457
-


38
County south of monument 118 has similar characteristics to northern St. Johns County with a
single shore parallel access and large low-density single-family development. The Coastal
Barrier Resources Act covers the section between monuments 157 to 164, so that development is
this area cannot receive federal assistance for flood insurance or roadway construction.
Development in the barrier islands of northeast Florida has occurred predominantly since
Hurricane Dora in 1964 (Reesman, 1994). The coast of St. Johns County is 66.5 km from Duval
to Flagler County to the south (FDEP, 2004b). Figure 3-2 shows the locations of the inlet, coastal
municipalities and parks referred to in this research. In 1972 St. Johns County was not intensely
developed. There are several sample 9-hectare plots with no development at all. The
development that existed was sparse single family, mobile home and small commercial. To the
north at Ponte Vedra at monument 2 the Ponte Vedra Golf Club was constructed. However, it is
clear for the lack of residential development surrounding that area that the influences of
Jacksonville as a metropolitan area did not extend to northern St. Johns County. Along Anastasia
Island in 1972 there are large undeveloped areas. Highway AIA is routed away from the coast
leaving large areas with potential for development. In 1972 there were 3 large trailer or RV
developments. These consisted of a concrete pads and utility connections. Large-scale
condominia, hotels and motels were not present except at St. Augustine Beach. South of
Matanzas Inlet there was development immediately adjacent to the inlet, and none on the spit
between the Matanzas River and the Atlantic.
In 1986 single-family development had expanded. Large homes had been constructed in
the Ponte Vedra Area and Vilano Beach was beginning to develop with smaller single-family
homes. The Ponte Vedra commercial area had expanded. The construction of homes further
south on AIA was occurring. Just north of St. Augustine Pass, in the area protected by rocks, a
single-family neighborhood had developed by 1986.


147
Table E-2. Continued
Monument Date Northing Northing
Number Set (position 2)
NS EW
Change Easting Easting change
(in m) (position 2) (in m)
1 2
120
121
122
123
124
'125
'126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
157
158
Jun-72
Jun-72
1999
1995
Jan-79
1995
Jan-79
Feb-84
Jan-79
Jan-79
Jan-79
1998
Jan-79
Feb-84
1998
Feb-84
Feb-84
1998
Jan-79
Feb-95
Feb-95
Jun-72
1995
Oct-83
2031034.98
2030032.20
2028981.33
407363.87
407769.34
408117.83
Monument replaced > 3m from original
Monument replaced > 3 m from original
2024401.27 2024401.27 0.00 410287.51 410287.51
2023529.80 2023529.80 0.00 411383.60 411383.60
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
Monument replaced > 3m from original
2011540.80 2011542.48 -0.51 414680.19 414685.08
Monument replaced > 3m from original
Monument replaced > 3m from original
2008862.42 415279.70
Monument replaced > 3m from original
Monument replaced > 3m from original
146 Feb-95 Monument replaced > 3m from original
147 Jan-84 Monument replaced > 3m from original
148 1997 Monument replaced > 3m from original
149 1999 Monument replaced > 3m from original
150
1999
1999839.03 1999839.25
-0.07
416059.47
151
Jun-72
1998834.38
416040.56
152
Jun-72
1997849.50
416108.85
153
Jun-72
1996847.12
416185.94
154
Jun-72
1995858.34
416223.93
155
Jun-72
1994860.73
416335.43
156
Jan-79
1993857.83 1993857.83
0.00
416393.22
Jan-79
Jun-72
1991867.33
Monument replaced > 3m from original
416507.20
0.00
0.00
-1.49
143 A
1973
200663.24
200663.24
0.00
200663.24
200663.24
0.00
144
Oct-83
2005831.25
2005831.27
-0.01
415575.23
415575.23
0.00
145
1999
2004805.12
2004803.95
0.36
415600.61
415598.00
0.80
-0.81
0.00


6
Areas were divided into those suitable for high-intensity activity and areas that should be
maintained in a natural state. Similarly, North Carolina has used zoning restrictions for hazard-
mitigation purposes (Bush et al., 1999). The geomorphology provided the basis of land use
restrictions that were enforced through zoning controls.
Use of Spatial and Temporal Data in Geomorphology
The field of geomorphology was originally characterized by landscape evaluation using
fieldwork. Later, modeling processes and laboratory simulations became important (Hooke,
1999). For each stage of geomorphological research the importance of the data has been
paramount. Perfect data would be spatially and temporally precise, accurate, readily available,
and calibrated. The shortfalls of data must be acknowledged and accommodated in successful
research. There are four categories of data; in-situ, remotely sensed, secondary data, and
simulated data (Lucas, 1996). This research used predominately secondary data collected by the
State of Florida, remote data (aerial photography) and simulated data collected from county
comprehensive plans. Field research or in-situ investigations augment the data. These data are
combined and analyzed using Geographic Information Systems (GIS). Geomorphological
research has progressed from simple one-dimensional analyses to the complex spatial capabilities
afforded by digital media (Vitek at al., 1996). The research considered spatial detail alongshore
and temporal scales by decade. Geomorphological research occurs at micro to macro scales
(Table 2-1) and temporal periods of days to decades.
The evaluation of time in geomorphic analyses in crucial to the validity of any conclusions.
As Schumm (1992, pp. 39) states, the period of record must be adequate to describe the
phenomena of concern. The length of time over which phenomena should be studied is not a
simple deduction (Pilkey, 2003). Physical processes occur over a variety of time scales, and the
time period used must be adequate to describe the process (Viles and Goudie, 2003). The
temporal analysis of coastal evolution cannot be neatly divided into short and long-term
components. Emphasis on large scale coastal behavior (LSCB) (Carter and Woodroffe, 1994is


48
Table 4-3. Profile measurement metadata, monuments 1 to 200, Brevard County
Brevard County-1972 Brevard County-1986 Cont.
Date
Monument Number
Date
Monument Number
Range
Range
9/13/72
1-40
12/19/85
68-86
9/20/72
41-79
1/7/86
123-126
9/21/72
80-95
1/8/86
121,122
9/26/72
96-107
1/9/86
97-120
10/3/72
108-120
2/4/86
136-155
10/26/72
121-128
2/5/86
127-135
11/8/72
129-134, 151-162
2/6/86
156-172
11/7/72
135-150
2/19/86
174-186, 201,204,205
11/9/72
163-195
2/20/86
187-193, 194-200
11/16/72
196-211
2/21/86
173,202,203
11/27/72
212-219
3/5/86
209-218
3/6/86
193,206-208
3/7/86
219
Brevard County-1986
Brevard County-1997
Date
Monument Number
Date
Monument Number
Range
Range
8/27/85
1-13
10/97
1-219
8/28/85
14-23
8/29/85
24-46
12/4/85
52-67
12/5/85
47-51
12/18/85
87-96
Maximum Dune Height (DH) and Distance to Maximum Height (DHBW)
Dune Height (DH) and the Distance to Maximum Dune Height (DHBW) are important
site-specific variables that are strong determinants of susceptibility to inundation (Bush et al.,
1999; Fisher, 1984; Gares, 1988). Maximum dune height is defined as the highest point on the
profile that is recorded seaward of the monument. By considering the point seaward of the
monument, variations due to the extent of the profile inland are controlled. The Distance to the
Maximum Height variable is the distance from NGVD to the maximum height. This variable
gives an indication of the position of the highest point on the profile to the shoreline, rather than
the fixed point of the monument. The importance of the interaction between sediment on the
foreshore and supply to the dunes reflected by the Distance to the Maximum Dune Height has
been discussed by Davidson-Arnott (1988). The distance to maximum height variable gives an


158
Table G-3. Continued
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05 Normality
Number of Units
UN
83
5.6
8.3
0.0
40.0
0.2513
0.097 Reject
UNC
83
8.3
9.9
0.0
52.0
0.2184
0.097 Reject
UN.3
83
15.5
14.9
0.
76.0
0.2196
0.097 Reject
UNa-i
83
2.7
5.6
-3.0
46.0
0.2781
0.097 Reject
UN.3-2
83
7.2
13.1
-11.0
60.0
0.2964
0.097 Reject
UN-i
83
9.9
14.7
-11.0
70.0
0.2754
0.097 Reject
Hectares of Impervious
IMP,,
83
0.2
0.4
0.0
1.9
0.3274
0.097 Reject
IMPu
83
0.4
0.7
0.0
3.3
0.2839
0.097 Reject
IMP,,
83
0.4
0.7
0.0
3.3
0.2338
0.097 Reject
IMP*.,
83
0.2
0.5
-0.02
3.3
0.3264
0.097 Reject
IMP.3J
83
0.2
0.4
-0.4
2.2
0.3026
0.097 Reject
IMP.,
83
0.5
0.8
-0.1
4.3
0.2587
0.097 Reject
DACC
81
2.2
8.8
-13.0
16.9
0.0678
0.098 Accept
Hectares of Commercial
C
83
0.1
0.3
0.0
1.8
0.5070
0.097 Reject
Cc
82
0.2
0.7
0.0
3.3
0.4190
0.097 Reject
Cu
80
0.3
0.8
0.0
4.3
0.3687
0.098 Reject
Ct2-1
82
0.2
0.5
-0.3
3.3
0.4302
0.097 Reject
Ct3-2
80
0.1
0.4
-0.8
2.1
0.4009
0.098 Reject
Ct3-1
80
0.3
0.7
-0.3
4.3
0.3765
0.098 Reject
Future Land Use
FLUtf
83
9.4
8.1
0.0
51.9
0.1330
0.097 Reject
FLUCa
83
0.6
1.1
0.0
4.1
0.3195
0.097 Reject
FLUU
83
38.0
24.6
0.0
117.0
0.1270
0.097 Reject
FLUCa
83
0.1
0.5
0.0
2.0
0.3195
0.097 Reject


140
120
100
z>
o
-
o
£2
E
3
80
60
40
20
/
Vilano
9> Beach
St.
Ponte Vedra
*. Beach
Q -£C
0
*
9
O 1

<0
£ £
: n3 a
6
6
9 !
TO 0) -jC
03
; .c .2
; § $
Q
lo
: 9
o
; ?
O
9
§ a :
3 (O a .
§ .:
i am *
A ?- 2^
Wn _
SiAftK ...
O

? )
^ 5
£ : '
0!SR, o
X.' Monument
121 X'V,


X
Anastasia Island
TD
1,
p
;
ix
' 4 cd
Q<=
X
i.9
x&
;
, q
Lrj
7
xm x xX?
10
Monument
15 20 25 30 35 40 45 50
Distance Alongshore from Monument 1 (km)
X 1972 Units 1986 Units
1999 Units -- Potential Units
Figure 5-6. St. Johns County total units, 1972 to 1999, with potential units (UN,,, UNa, UNt3, FLUa)
Matgnsas Inlet


175
Table H-15. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to 198),
Monument to Dune Height (MDH)) and dependent variables at 0.05 significance
MDH
MDHa
MDHa
MDHa.,
MDH,3.2
MDH,3.1
MDHlo,
MDHf
POS
UN
-
-
-
-
-
-
-
-
-
UN*
-
-
-
-
-
-
-
-
-
UNa
-
0.3556
0.4024
0.4028
-
0.4153
0.4810
-
-0.3816
unq.,
-
-
-
-
-
-
-
-
-
UN-2
-
0.3557
0.4791
-
-
0.4660
0.4419
-
-
UN-i
-
0.3343
0.5554
0.3913
-
0.5556
0.5788
0.3425
-0.3253
UH
-
-
-
-
-
-
-
-
-
UH(2
-
-
-
-
-
-
-
-
-
UH
-
0.3869
0.4240
0.4335
-
0.4460
0.4519
0.3371
-0.3314
uhq.,
-
-
-
-
-
-
0.3713
-
-
UHa-2
-
0.3783
0.5004
0.3328
-
0.4863
0.4180
-
-
UHo-i
-
0.3479
0.5729
0.3936
-
0.5690
0.5789
0.3480
-0.3198
IMP,,
-
-
-
-
-
-
-
-
-0.3013
IMP,,
-
-
-
-
-
-
-
-
-
IMP
-
-
-
-
-
-
-
-
-
IMP.,
-
-
-
-
-
-
-
-
-
IMP, 3.2
-
-
-
-
-
-
-
-
-
IMPa.,
-
-
-
-
-
-
-
-
-
PIM
-
-
-
-
-
-
-
-
-
pim,2
-
-
-
-
-
-
-
-
-
PIM.3
-
-
-
-
-0.3306
-
-
-
-
PIMa-i
-
-
-
-
-
-
-
-
-
PIM.3-2
-
-
-
-
-
-
-
-
-
PIMa-i
-
-
-
-
-
-
-
-
-
ACC
-
-
-
-
-
-
-
-
-0.3757
DACC
-
0.3681
0.5097
0.3556
-
0.4724
0.4983
0.4558
-
POS
-0.3890
-0.4180
-0.4806
-
-0.3403
-0.5932
-0.3351
1.0000
Qi
-
-0.3338
-
-
-
-
-
-
-
Ca
-
-
-
-
-
-
-
-
-
Ca
-
-
-
-
-0.3536
-
-
-
-
Ct2-1
-
-
-
-
-
-
-
-
-
Q3-2
-
-
-
-
-
-
-
-
-
03-1
-
-
-
-
-0.3575
-
-
-
-
FLUD
-
-
-
-
-
0.3926
-
-
-
FLU,2
-
-
-
-
0.3610
-
-
-
-
FLUDq
-
-
-
-
0.3911
-
-
-
-
FLUCa
-
-
-
-
-
-
-
-
-
FLUa
-
0.3970
0.3970
0.4100
-
0.4824
-
0.4343
-
FLUDa
-
0.4820
0.4501
0.4909
-
0.5189
-
0.4523
-
FLUCa
-
-
-
-
-
-
-
-
-0.4429


36
Hurricanes impacts in northeast Florida have been largely indirect with limited activity
from storms traveling from the Gulf of Mexico over the peninsula and back into the Atlantic.
Hurricane conditions were experienced in 1964, when hurricane Donna passed over north central
Florida. This hurricane was exiting Florida and moving offshore having passed over Floridas
north central peninsular area. In addition to direct hits and winter storms, Northeast Florida is
prone to indirect storm impacts. The recognized recurve pattern of storm paths up the
southeastern United States impacts the area. In northeast Florida indirect hurricane conditions
have caused flooding of infrastructure, storm surge and dune erosion and wind damage
(Reesman, 1994). Storms during the 1990s have caused local erosion along the northeast coast.
Hurricane Floyd in 1999 threatened the northeast Florida coast but remained offshore and
eventually made landfall in North Carolina. The northeast Florida study area has not experienced
any direct hurricane landfall during the 27-year research.
The most recent 2004 storm history is after to the data used in this research. However, it is
important to note that three storms impacted the study areas. Brevard County experienced
hurricane conditions from Hurricanes Frances and Jeanne. Both these storms also produced
tropical storm conditions in St. Johns County. The impacts on the St. Johns County
renourishment projects are discussed in the results section. Hurricane Charley also exited south
of St. Johns County, in the vicinity of Daytona Beach.
Winter Storms
Winter storms or Noreasters are extratropical storms that impact the coast from October to
April. Although they may not have the extreme wind speeds associated with hurricanes they
affect wider swaths of the coast because they are larger and may stall over coastal areas. These
storms can be over 1,000 km wide and cause surges of over 4.5 m. Prolonged wave activity
enhances the destructive capacity of a winter storm. Noreasters derive their names from the
prevailing wind direction. These storms rotate counterclockwise and travel north along the east
coast of the United States (Davis and Dolan, 1993). The low-pressure core is accentuated by high


110
Table 5-23. Summary of non-parametric results by hypothesis, St. Johns County
Hypothesis
Independent
Variable
Relationship
Dependent Variables
la-Actual geomorphology and
BW,, BWt2
Positive
IMP,,. IMPe. IMP,,
development
BWtf
lb-Actual geomorphology and
BW BWo
Positive
FLUD tl FLUD,,
adopted future land use
BW
2a-Dynamic geomorphology
BW,,.,.
Positive
IMP,, IMPc IMP,3
and development
BWf
Positive
UN 0.0, IMP,,, a. o, PIM
LT
Positive
IMP ,1 ,2, t3, PIM tl, t2, t3 c t3
2b-Dynamic geomorphology
BW,3_,
Positive
FLUD,, FLUD.3
and adopted future land use
BWf
Positive
FLU a FLU0
LT
Positive
FLUD,, FLUD a FLUD,,
3-Temporal lag between
geomorphology and the human No relationships
variables
Table 5-24. Summary of non-parametric results by hypothesis, Northern St. Johns County, Ponte
Yedra to Vilano Beach
Hypothesis
Independent
Variable
Relationship
Dependent Variables
la-Actual geomorphology and
development
DHBW.3,
Negative
UNoj.UNB-i.UHaj, UH,3.,
lb-Actual geomorphology and
adopted future land use
BW,, BWa
BW,3.
Positive
FLUD, FLUDo
mdhi2,
MDH.3
Positive
FLU0
dhbw,3
Negative
FLUD,,
2a-Dynamic geomorphology
and development
-
2b-Dynamic geomorphology
and adopted future land use
3-Temporal lag between the
MDHa.i.
MDH_,
Positive
FLU ,3.
actual and dynamic
geomorphology and the human
variables
No relationships
I 1 Statistical relationship inconsistent with research hypothesis
Hypothesis 4, the difference between variable relationships for the two study areas, was not
included in the summary tables. Hypothesis 4 is supported by the differences in significant
relationships in Tables 5-22 and 5-23. The maximum dune height (DH) in Brevard County is a
significant independent variable, whereas it is not significant in St. Johns County. The beach


1
77
Row-wise Spearman Rank Correlations were performed for both St. Johns and Brevard
County. This methodology was selected to evaluate the continuous and discrete data. Nominal
data includes that presence of renourishment (RN), dune renourishment in Brevard County
(RND), structures (SW) and State erosion designation (ER). The Spearman Rank correlation is an
indicator of a simple relationship by rank order, so that a positive relationship between variables
shows that the highest measure of the independent variable is associated with the highest measure
of the dependent variable. This indicator of monotonocity does not distinguish linear from non
linear relationships because the ranked data provide a directional indicator of the variable
association but not an indicator of distance between variables. All dependent and independent
variables were analyzed.
The non-parametric statistics provide general bivariate comparisons for the direction of
variable association. Multiple regression analyses are used to evaluate the multiple interactions
of variables and to measure and model the dimensions of the impacts of variables. Independent
variables were transformed and integrated (Appendix B). The categorical data, such as the
presence of absence of structures and the designation of erosion concern (ER) determined by the
Clark (1999) were used as dummy variables for analyses (Appendix B). Other dummy variables
include the presence of renourishment (RN), dune renourishment (RND, Brevard County only),
and structures (SW). This portion of the data analyses enables the use of the ordinal variables to
be evaluated for interaction with other variables more appropriately than in the non-parametric
statistical analyses. A stepwise analysis of each dependent variable was performed. Once the
relevant variables were isolated, multiple regression analyses were performed for all the Brevard
County sample areas, the entire St. Johns County data and the St. Johns County data by
geomorphic area.
Methodology Implications
Both the number of units and density changes are sensitive if the numbers (UN, UH) and
available hectares are small. For example in St. Johns County at monument 184 there was a


8
(2004) used a 15-year horizon over which he evaluated the impact of renourishment on beach
profiles of the Dutch coast.
This research considered the time period of accelerated coastal development in Florida. In
St. Johns County access was not available to Anastasia Island until the 1950s (Olsen, 1974). The
proposed period from 1972 to 1999 represents the timeframe for much of the development in the
two counties (Figure 2-1) (Bodge and Savage, 1989; Brevard County, 1989; Long, 1968; St.
Johns County, 1979, 1993,2002; Toth, 1988). Impacts of physical characteristics on
development can only be determined for time in which development had occurred. Beginning in
the 1970s ensures that the baseline development already present was low density. Change in those
areas, and the development of formerly vacant areas, will illustrate the impacts of the physical
environment. Similarly the legislation requiring state-coordinated planning was initiated in 1972,
and local comprehensive plans was required in 1975. This importance of land use controls on
settlement patterns along the coast is discussed later in this section.
The importance of time lag should also be mentioned, particularly because response in the
coastal zone is not necessarily linear. Any analysis of the coast should consider lagged effects.
In longshore drift, the impact of jetties, for example, is not immediate (Nordstrom, 1996; U. S.
Army Corps of Engineers, 1993). A cyclical pattern of shoreline positions over time, analyzed
using a linear regression, may appear stable (Nordstrom, 1994). The use of the dynamic
geomorphology variables, described in the methodology will address these issues.
Few processes or landforms in geomorphology are isolated in space. It is important to
consider each research area part of a complex spatial system. Findings from one scale cannot
necessarily be extrapolated, because with increased scale, there is increased complexity in the
system. Conclusions about specific landforms cannot be extended to others that appear similar,
but vary in size (Phillips, 1988; Phillips, 1997). Haggett and others (1977) describe the scales of
geographic inquiry and suggest caution when inferring characteristics from one level to another.
This research used the same scale, spacing, and frequency of data for both study areas.


89
movement of the maximum dune height. However the average Brevard County DHBW returns
to 49.9m in 1997 from a 1972 measurement of 49.2m.
The 1999 DHBW in St. Johns County is similar to 1972, and lower in certain areas. The
average beach width for the entire county does not recede back to the 1972 width, as it does in
Brevard County. Although the maximum dune height (DH) moved seaward in 1986, the DHBW
was wider. In northern St. Johns County the DHBW is narrowest in 1999 (63.8m) and widest in
1986 (77.7m), which is consistent with the BWq and BWt3. On Anastasia Island the DHBW is
also widest in 1986 at over 125m, but the decrease in 1999 is not to the extent of the level in
1972. Summer Haven has seen a consistent decline in the DHBW from 1972 to 1999.
Long Term Change (LT)
The long-term changes show variations (Chapter 4, figures 4-3 and 4-4) with the highest
accretion of over 1.3m/yr occurs adjacent to Port Canaveral Inlet and in Cocoa Beach. South of
Satellite beach there is one area of Brevard County experiencing long-term erosion, between
monuments 154 and 163. The average long-term change in Brevard County is 0.3m/yr (Table 5-
4) and is an indicator of a coastal area behaving as a single geomorphic unit.
The average long-term change for all monuments in St. Johns County is 0.13m/yr. Table
5-4 shows why consideration of St. Johns County by geomorphic unit is important. Northern St.
Johns County and Anastasia Island have distinctly different patterns of long-term change.
Northern St. Johns County is predominantly stable with areas of small long-term erosion at Ponte
Vedra and Vilano Beach. Rapid accretion is occurring at monument 122, adjacent to St.
Augustine Pass. Anastasia Island varies from severe erosion of over 7m/yr at St. Augustine
Beach to long-term accretion of over 2 m/yr in central Anastasia Island. The Sea Haven area,
south of Matanzas Inlet is experiencing erosion. Anastasia Park is not included in this research
because its status precludes development potential. However, the area south of St Augustine Pass
with long-term erosion problems was renourished in 2002 and 2003.


68
The use of the Stormwater management accepted single-family impervious area is
evaluated using GIS. The total area for each 9-ha sample area was compared to the amount of
impervious are that was estimated using the impervious area factor to evaluate the validity of the
estimated impervious area for single-family home sizes. In Ponte Vedra, in St. Johns County, it is
noted that original single-family structures present in the 1972 photography have been expanded
or replaced, resulting in an enlarged impervious area footprint. Conversely structures constructed
since the establishment of the Federal Emergency Management Agency FIRM maps in
designated V zones, must be elevated. The increased cost of construction for elevation of
structures also limits the impervious footprint. In Brevard County the existing single-family lot
sizes in Cocoa Beach west of Highway A1 A, are small (less that 0.1 ha) and expansion of
residential structures, when constrained by lot size will be vertical and not impact the total
impervious area.
Future Land Use (FLU, FLUD, FLUC)
Land use designations are available from the adopted county Comprehensive Plans. The
comprehensive plans for each time period contain future land use designations for the entire
County. The amount of each land use category in the area immediately adjacent to the monument
is determined using the existing land use maps and GIS and converted to units per hectare for
each 9-ha area.
Table 4-9. Land use data availability by study area
Study Area
Data Availability
Brevard County
St. Johns County
1972 (adopted 1981)(FLUD), 1989 (not available)
2000 (2010 horizon) (FLU, FLUD,, FLUC,,)
1979 (FLUD), 1989 (FLU12, FLUDt2, FLUC,2)
2001 (2015 horizon) (FLU, FLUD,, FLUC,,)
The future land use designations in the first comprehensive plans adopted in the 1970s are
general and did not specify future land uses in sufficient detail for distinctions along the coast. In
1972 Brevard County adopted an open space plan (Brevard County Planning Department, 1972)
through a 1995 planning horizon, that was incorporated in the 1981 general future land use maps


167
Table H-7. St Johns County Spearman Rank analyses, Monument to Dune Height (MDH)) and
dependent variables at 0.05 significance
MDH
MDHa
MDHa
MDHa-i
MDHa-2
MDH, 3-,
MDH,0,
MDHf
POS
UN
-
-
-
0.2820
-
0.2216
0.2920
-
-
UNa
-
-
-
0.2435
-
0.2308
0.2893
-
-
UNa
-
-
-
0.2320
-
-
0.3093
-
-
UN.,
-
-
-
-
-
-
-
-
-
UNu.2
-
-
-
-
-
-
_
-
_
uni3.,
-
-
-
-
-
0.2215
0.2367
-
-
UHtl
-
-
-
-
-
-
-
_
_
UH,,
-
-
-
-
-
-
-
_
-
UH,3
-
-
0.2519
-
-
-
-
_
_
UHa.,
-
-
-
-
-
-
-
_
-
UHa.2
-
-
-
-
-
-
_
_
_
UHo-i
-
-
-
-
-
-
-
-
-
IMP,,
-0.1996
-
-
0.2313
-
0.2470
0.3334
-
-
IMPa
-0.2095
-
-
-
-
-
0.3869
-
-
IMPU
-
-
-
-
-
-
0.2460
-
-
IMPa-i
-
-
-
-
-
-
-
-
0.2197
IMP0.2
-
-
-
-
-
-
-
_
_
IMP,,.,
-
-
-
-
-
-
-
-
0.2112
PIM
-
-
-
-
-
-
_
_
_
PIMa
-
-
-
-
-
-
_
_
_
PIM.3
-
-
-
-
-
-
-
-
0.1792
PIMq.i
-
-
-
-
-
-
-
-
0.2200
PIMi3_2
-
-
-
-
-
_
_
_
_
PIMa-i
-
-
-
-
-
-
-
-
0.2628
ACC
-
-
-
-
-
-0.2204
-0.2300
-0.2067
-
DACC
-
-
-
-
-
0.0297
-
-
-
POS
0.4046
-
-
-0.2965
-
-0.2247
-
-0.2727
-
Q,
-
-
-
-
-
-
-
-
-
Ca
-
-
-
-
-
-
-
-
0.1874
ca
-
-
-
-
-
-
-
-
0.1848
Ct2-1
-
-
-
-
-
-
0.2433
-
0.2094
Q3-2
-
-
-
-
-
-
-
-
-
Ct3-1
-
-
-
-
-
-
-
-
0.1847
FLUD
0.1967
-
-
-0.2008
-
-
-
-0.1972 0.3633
FLUa
0.2261
-
-
0.3356
-
0.2922
-
0.2618
_
FLUD0
-
-
-
-
-
-
_
_
_
FLUCa
-0.2321
-
-
-
-
-
-
-
-
FLU,.,
-
-
0.3641
0.3496
-
0.4074
0.2244
0.3390
-
FLUDa
-
-
-
-
-
0.1959
-
-
-0.1932
FLUCa
-
-
-
-
-
-
-
-
-


I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope apd quality, as a dissertation
for the degree of Doctor of Philosophy.
I certify that I have read this study and tha/'in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation
for the degree of Doctor of Philosophy.
Csar Cavie
Professor of Geography
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate, in scope and quality, as a dissertation
for the degree of Doctor of Philosophy.
Timothy Fik
Associate Professor of Geography
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequpte^n scope and quality, as a dissertation
for the degree of Doctor of Philosophy.
Peter Waylen
Professor of Geogf!
I certify that I have read this study and that in my opinion it conforms to acceptable
standards of scholarly presentation and is fully adequate^ir^ope and cmafity, as a dissertation
for the degree of Doctor of Philosophy.
Paul Zwicr
Associate j^rofj^sor of Urban and Regional
Plannw
This dissertation was submitted to the Graduate Faculty of the Department of Geography
the College of Liberal Arts and Sciences and to the Graduate School and was accepted as partial
fulfillment of the requirements for the degree of Doctor of Philosophy.
May 2005
Dean, Graduate School


61
The Beach Width Factor for situation a) is 1.0 indicating continuing accretion. In situation b) the
Beach Width Factor is 0.5. The positive value indicates net but not continual, accretion. A
negative Beach Width Factor indicates the Net change has been negative. A Beach Width Factor
of-1.0 indicates an eroding shoreline.
LAND
a)
b)
OCEAN
Total
Beach
Change
40m
Figure 4-7. Beach width dynamic geomorphology variable
Compilation of Data
Data from the FDEP website are used in raw form to avoid rounding, aggregation and
other errors. These data require considerable manipulation to render them suitable for analysis.
Data from each county must be reviewed for completeness of record. Data sets that contained
information only at 1,000-meter intervals or for a localized range of monument for each county
were not used. Data were imported and converted so that the geomorphic variables could be
extracted. Each monument placement was reviewed and adjusted in instances where the
monument was relocated. Using the methodology proposed by Rahn (2001) any monument that
had been moved in excess of 3m north or south of the original position was excluded. The 3m
dimension assumes that the profile continues to reflect the local topography. Monuments using
the same azimuth that were relocated landward were suitable for use, but only the portion of the
profile present in the earlier positioning of the monument was used.


141
Table E-l. Continued
Monument Date
Number Set
Northing Northing
(position 2)
NS Change Easting Easting
(in m) 1 (position 2)
EW
change
(in m) 2
83
Jan-80
1402842.00 1402839.00
0.91 630592.80630597.50
-1.43
84
Aug-72
1401866.00
630805.50
85
Aug-72
1401148.00
630957.50
86
1993
Monument replaced > 3m from original
87
1993
Monument replaced > 3m from original
88
Jan-80
1398219.00 1398229.00
-3.05 631601.70631603.00
-0.40
89
Jan-80
1397353.00 1397355.00
-0.61 631789.10631810.50
-6.52
90
Jan-80
1396744.00 1396742.00
0.61 631925.10631923.00
0.64
91
Jan-80
1395879.00 1395879.00
0.00 632151.50632151.50
0.00
92
Jan-80
1395007.00 1395007.00
0.00 632354.00632354.00
0.00
93
Aug-72
1394034.00
632579.50
94
Jan-80
1393061.00 1393061.00
0.00 632790.50632790.50
0.00
95
Jan-80
1392304.00 1392299.00
1.52 632933.20632953.00
-6.04
96
Aug-72
1391383.00
633158.50
97
1993
1390479.00 1390479.00
0.00 633371.50633371.50
0.00
98
Aug-72
1389503.00
633588.50
99
1993
Monument replaced > 3m from original
100
1993
Monument replaced > 3m from original
101
Aug-72
1386622.00
634229.00
102
Aug-97
Monument replaced > 3m from original
103
Jun-85
1384696.00 1384696.00
0.00 634662.00634662.00
0.00
104
Aug-97
Monument replaced > 3m from original
105
1993
Monument replaced > 3m from original
106
1993
Monument replaced > 3m from original
107
Jan-80
1380966.00 1380972.00
-1.83 635512.80635748.00
-71.69
108
Jul-83
1380073.00 1380073.00
0.00 635716.50635716.50
0.00
109
Jan-80
1379165.00 1379165.00
0.00 635931.50635931.50
0.00
110
Jan-80
Monument replaced > 3m from original
111
Aug-72
1377232.00
636442.00
112
Aug-97
1376261.00 1376260.00
0.30 636673.10636673.50
-0.12
113
Jan-80
1375414.00 1375414.00
0.00 636902.00636902.00
0.00
114
Aug-72
1374518.00
637162.00
115
1993
Monument replaced > 3m from original
116
Jun-85
1372683.00 1372673.00
3.05 637704.60637602.50
31.12
117
Jan-80
Monument replaced > 3m from original
118
1993
Monument replaced > 3m from original
119
No Data
120
Jun-85
1369059.00 1369058.00
0.30 638779.00638777.80
0.37
121
Jan-80
Monument replaced > 3m from original
122
Aug-72
1366336.00
639568.50
123
Aug-72
1365417.00
640083.50
124
Aug-72
1364473.00
640358.00
125
Jun-85
Monument replaced > 3m from original
126
Jun-85
1363536.00 1363536.00
0.00 640734.50640734.50
0.00
127
1993
Monument replaced > 3m from original


33
The littoral drift on the east coast of Florida is predominantly north to south (Reesman,
1994). In Brevard County drift of approximately 38,000 to 76,000 m3/yr is to the south (FDEP
2004a). However, Stapor and May (1983) have noted several littoral cells on the Northeast coast
and describe Anastasia Island as an area of convergence and the area between Vilano Beach and
Ponte Vedra as an area of divergence (Figure 3-2). Drift, predominantly during the summer, is to
the north on Anastasia Island (Stapor and May, 1983). In St Johns County the prevailing drift
direction is to the south and reported rates vary from 112,000 to 336,000 m3/yr (Foster et al.,
2000). Anecdotal evidence reports pulses of sediment along Ponte Vedra beach. This may be
due to renourishment activities to the north (Foster et al., 2000). Femandina beach was
renourished in 1978. The Fort Clinch area in northern Nassau County was renourished in 1996.
The dredging of St. Marys inlet to accommodate the US Navy has resulted in the placement of
material on Amelia Island (Reesman, 1994). On Anastasia Island the rate is lower at 152,000 to
228,000 m3/yr to the south (FDEP 2004a).
Storms
The impact of storm activity is considered a long term and macroscale variable (Davis and
Dolan, 1993). It is obvious that hurricane and storm activity impacts settlement decisions
although the extent to which this impact influences settlement cannot be easily evaluated within a
30-year timeframe.
The hurricane that hit in 1885 discouraged further settlement. The storm pushed the
ocean waves over the barrier island (elevation 10 feet [3.2m]) flooding out the homesteaders.
The beach near Canaveral Lighthouse was severely eroded prompting President Cleveland and
the Congress to allot money for an effort to move the tower 1 mile [1.61 km] west (Rabac, 1986,
page vii)
The hurricane history of the two study areas is different in the long-term and over the 30-
year study period. The record of hurricanes from 1872 to present shows that the east central


200
150
=)
o
5 inn
* co jd -{*:
E
3
Z
50
cP __ 5: co co
355-
rfWLj CD CteP CD C.
*
Ponte Vedra
Monument 121
A
Monument 1
10 15 20 25 30 35 40 45 50 55
Distance Alongshore from Monument 1 (km)
[x 1972 Beach width 1986 Beach width 1999 Beach widthl
60 J 65
Monument 198
70
Figure 5-1. St. Johns County beach width variations, 1972-1999, (BWtl, BWt2, BW,3)


100
areas increased from 4.1 ha to 5.6 ha on Anastasia Island from 1986 to 1999. The future land use
commercial designation trends in St. Johns County show a decrease in the average number of
hectares with a commercial future land use, but an increase in the maximum hectares. This is an
indicator of planning for more highly concentrated commercial development.
Hypotheses Testing, Bivariate Statistical Analysis
Row-wise Spearman Rank correlations were performed for both St. Johns and Brevard
County (Appendix H). The variable evaluations are shown in relation to the hypothesis that each
relationship supports.
Beach Width Index (BW)
The Beach Width Index (BW) variable, a measure of the distance form NGVD to the
monument shows no relationship with the dependent variables in the individual time periods (ti, a
and t3) as proposed in Hypothesis la in Brevard County. The change in beach width from 1972 to
1986 has a positive relationship between the changes in the number of units (UN), unit density
(UH), impervious area (IMP) and percentage impervious (PIM) in each of the dynamic time
periods (Hypothesis 2a) (Table 5-7).
Table 5-7. Beach width change 1972 to 1986 and development variables in Brevard County
Development Variables Beach Width Change, 1972 to 1986 (BW,2-i)
1972-1986 (t2-i) 1986-1997 (,3.2) 1972-1997 fo-i)
Units (UN)
0.205
0.248
0.306
Density (UH)
0.178
0.239
0.289
Impervious Hectares (IMP)
0.279
0.292
0.326
% Impervious (PIM)
0.216
0.282
0.259
95% confidence interval
This indicates that areas with higher intensities of development show a functional
relationship with areas where beach width is accreting. It appears that the dynamic beach width
change from 1972 to 1986 influences the units, units per available hectare, impervious area and
hectares of commercial property in later time periods (Hypothesis 3). The impervious area
measures (IMP and PIM) are highest where the total beach width change (BWtoI) was the highest
(Hypothesis 2a). During each time period sample areas with higher total change had the highest


ACKNOWLEDGMENTS
I would like to acknowledge the assistance of my supervisory committee chair (Dr. Mossa)
and members (Drs. Caviedes, Fik, Waylen, and Zwick). Several State of Florida and local
government officials provided invaluable assistance in data collection and interpretation: Tom
Watters and Emmett Foster, Department of Environmental Protection, Division of Beaches and
Shores; Mike Campbell, Corey Bowens, and Tim Brown, St Johns County; Mel Scott and Ann
Rembert, Brevard County; Sue Carrol and Albert Tolley, Brevard County Property Appraiser;
and the cities of Cocoa Beach, Melbourne, and Satellite Beach. I gratefully acknowledge receipt
of an O. Ruth McQuown Scholarship to fund this research, and funding provided by the
following: Department of Geography, University of Florida; College of Liberal Arts and
Sciences, University of Florida; the Florida Society of Geographers; and the City of Gainesville.
My sincere thanks go to my family and friends for their support and encouragement (especially
Kurt, Jeremy, and Emma); and to the Godmother of this endeavor, Sharon Cobb.
IV


45
All development variables use primary data sources and are derived for this research from
maps and photography. Each of the geomorphic variables are collected at monuments located
approximately 300m apart along the entire coast of Florida, excluding the Big Bend area and
Florida Keys. Development, or human variables are collected in sample areas adjacent to the
monument. Sample areas were selected to maximize analyses coverage. Sample areas were
designed to extend an equal distance wither side of the monument by 150m. The 300m
dimension alongshore and inland results in a 9-ha square sample area. The sample area is
oriented parallel to the shore and perpendicular to the meridian (Appendix D). The seaward
extent of the 9-ha sample area is defined by the extent of the digital land use coverage from the
DOQQs.
The influence of beach width, maximum dune height, distance to maximum dune height,
distance from the monument to the maximum dune height and long term shoreline change on the
actual and future land use, number of dwelling units, impervious area and development potential
is evaluated at each time period.
Figure 4-1. Beach profile and geomorphic variables


194
DOLAN, R., FENSTER, M. S., and HOLME, S. J., 1991. Temporal analysis of shoreline
recession and accretion. Journal of Coastal Research, vol. 7, no. 3, pp.723-744.
EL-RAEY, Y. F., and NASR, S., 1996. GIS assessment of the vulnerability of the Rosetta area,
Egypt to impacts of sea level rise. Environmental Monitoring and Assessment, vol. 46, pp.
59-77.
ESSEX, S. J., and BROWN, G. P., 1997. The emergence of post-suburban landscapes on the
North Coast of New South Wales: A case study of contested space. International Journal of
Urban and Regional Research vol. 21, no.2 pp. 259-285.
FENSTER, M., and DOLAN, R., 1996. Assessing the impact of tidal inlets on adjacent barrier
island shorelines. Journal of Coastal Research, Winter, pp. 294-310.
FERNALD, E. A., and PURDUM E. D., 1992. Atlas of Florida^ Institute of Science and Public
Affairs, Florida State University. University Press of Florida, Gainesville, Florida. 276 pp.
FIELD, M. E., 1974. Buried strandline deposits on the central Florida inner continental shelf.
Geological Society of America Bulletin, vol. 75, pp. 57-60.
FIELD, M. E., and DUANE, D. B., 1976. Post Pleistocene history of the United States inner
continental shelf: significance to the origin of barrier islands. Geological Society of
America Bulletin, vol. 87, pp. 691-702.
FINKL, C. W., 1996. What might happen to Americas shoreline if artificial beach replenishment
is curtailed: a prognosis for Southeastern Florida and other sandy regions along regressive
coasts. Journal of Coastal Research, vol. 12, no. 1 pp. iii-ix.
FINKL, C. W., CHARLIER, R. H., 2003. Sustainability of subtropical coastal zones in
Southeastern Florida: Challenges for urbanized coastal environments threatened by
development, pollution, water supply and storm hazards. Journal of Coastal Research, vol.
19, no. 14, pp. 934-943.
FISHER, J. J., 1968. Barrier island formation: discussion. Geological Society of America Bulletin,
vol. 79, pp. 1421-1426.
FLORIDA DEPARTMENT OF AGRICULTURE, 1928. Florida, an Advancing State, 1907-
1917-1927: an Industrial Survey. Authorized by the Legislature of 1927, Nathan Mayo,
Commissioner of Agriculture, Tallahassee, FL. 342 pp.
FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION, 2000a. Strategic beach
management plan, central Atlantic coast region. Office of Beaches and Coastal Systems,
October 2000, Tallahassee, FL. 14 pp.
FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION, 2000b. Strategic beach
management plan, northeast Atlantic coast region. Office of Beaches and Coastal Systems,
October 2000, Tallahassee, FL. 16 pp.


CHAPTER 6
DISCUSSION AND CONCLUSIONS
Berry (in Chorley, 1973) cautioned against the mindless use of conventional inference
statistics and measures of association in geographic research, without regard for the validity of
their assumptions. The potential for spurious conclusions in this research was recognized.
Conclusions with temporal implications must be sequentially appropriate. For example, in St.
Johns County the density of dwelling units appeared to be a function of the beach width during
later time periods. Similarly, the division of St. Johns County into geomorphic unit was
determined to be advantageous because the characteristics of the areas are dissimilar.
The relevance of the independent variables in relation to the dependent, or human
variables, varied by jurisdiction. Similarly variables that were not important on a county wide
basis were significant in St. Johns County when divided by geomorphic unit. The maximum
dune height (DH) is a significant independent variable in Brevard County, but to a lesser degree
in St. Johns County. The beach width (BW) at the specific time periods is a significant variable
in St. Johns County (Hypotheses la and lb) but only the dynamic beach width variable impacts
dependent variables in Brevard County (Hypothesis 2). The distance from the monument to
maximum dune height (MDH) is significant in Brevard county (although not consistent with
hypotheses) and the separate geomorphic units of St. Johns County, but not the entire county.
The impact of a temporal lag on dependent variables (Hypothesis 3) is present Brevard County,
and St. Johns County. Similarities between the two study areas include positive associations
between long-term accretion, and the location of higher numbers of units, density, impervious
area and future land uses. The use of dummy variables and weighted variables were important in
Brevard County, but not significant in St. Johns County. The regression analyses provided
additional insight into the dimension of the interactions of variables. Similar to the non-
120


22
(Hart, 2000). The value of a parcel of land may be reduced by environmental restrictions, for
example. The recognition that coastal areas are highly desirable for development forces local
jurisdictions to address the competing needs of development pressures, preservation of traditional
uses (such as fishing), protection of the environment, and maintenance of the coast for public
recreational use. Such delegated authority to the local level has inherent problems. Each
proposal is reviewed individually and the cumulative impacts of coastal development may be
overlooked.
Managing growth in Florida has been a dilemma since the introduction air conditioning,
the Space Program in Brevard County and the selection of Florida by the Disney Corporation for
the location of their second theme park. In 1972 the first requirements for comprehensive
planning were enacted by the Legislature in the State Comprehensive Planning Act. In 1985 the
Local Government Comprehensive Planning and Land Development Regulation Act (Chapter
163, Florida Statues) specified the requirements of Florida cities and counties to develop
comprehensive plans and land development regulations. These plans had requirements specific to
the coast, such as protection of coastal resources, control of water dependent uses, limiting of
developments in high hazard areas and the provision of public access (South Florida Regional
Planning Council, 1989). Section 9J-5 of the Florida Administrative Code specifies the minimum
criteria for coastal zone management elements of the comprehensive plan. Communities must
inventory, analyze and project the impacts of future land use and its impact on hurricane
evacuation. Each local jurisdiction must develop post-disaster plans for high hazard areas and
attempt to minimize future exposure of development, infrastructure and individuals to coastal
hazards.
Determinations of county wide existing and future land use designations, by local
jurisdictions were required after the 1972 State Comprehensive Planning Act and the 1985 Local
Government Comprehensive Planning and Land Development Regulation Act. The first
Comprehensive Plan submitted to the Department of Community Affairs under the 1985


198
NOAA, 1987. Tropical cyclones of the North Atlantic Ocean, 1871-1986. Historical Climatology
Series 6-2, National Climatic Center, Asheville, NC, 186 pp.
NORDSTROM, K. F., 1987. Predicting shoreline changes at tidal inlets on a developed coast.
Professional Geographer, vol. 34, no. 4, pp. 457-465.
NORDSTROM, K. F., 1994. Beaches and dunes of human-altered coasts. Progress in Physical
Geography, vol. 18, no. 4, pp. 497-516.
NORDSTROM, K. F., 1996. Developed coasts. In Carter, R. W. G. and C. D. Woodroffe, eds.,
Coastal Evolution; Late Quaternary Shoreline Morphodynamics. Cambridge Univ. Press,
Cambridge, U. K., pp. 477-509.
NORDSTROM, K. F., DE BUTTS, H. A., JACKSON, N. L., BRUNO, M. S., 2002. Municipal
initiatives for managing dunes in coastal areas: A case study of Avalon, New Jersey, USA.
Geomorphology, vol. 47, no. 2-4, pp. 137-151.
NORDSTROM, K. F., LAMPE, R., VANDERMARK, L. M., 1999. Reestablishing naturally
functioning dunes on developed coasts. Environmental Management, vol. 25, no. 1, pp. 37-
51.
NORDSTROM, K. F., and PSUTY, N. P., 1980. Dune district management: A framework for
shorefront protection and land use control. Coastal Zone Management Journal, vol. 7, No.
1, pp. 1-23.
NORDSTROM, K. F., PSUTY, N. P., and CARTER, R. W. G., 1990. Coastal Dunes: Form and
Process. John Wiley and Sons, New York, 392 pp.
OLIVIER, M. J., GARLAND, G. G., 2003. The short-term monitoring of foredune formation on
the East coast of South Africa. Earth Surface processes and Landforms, vol. 28, no. 10 pp.
1143-1155.
OLSEN, E. J., 1974. Northern St. Johns County Coastal Management Plan. Shore and Beach, vol.
42, pp. 29-35.
OLSEN, E. J., 2003. Brevard County Florida Federal shore Protection Project South Reach
Beach Fill: Post-Construction Physical Monitoring Report. Olsen Associates, Inc,
Jacksonville, FL, 47 pp.
OLSEN, E. J., and BUCKINGHAM, W. T., 1989. Sand source analysis for beach restoration,
Brevard County, Florida. Olsen and Associates, Jacksonville, for the Board of County
Commissioners, Brevard County, Florida, unpaged.
OLSEN, S. B., 2003a. Frameworks and indicators for assessing progress in integrated coastal
management initiatives. Ocean and Coastal Management, vol. 46, no.3-4, pp. 347-361.
OVERBERG, P., 2000. A boom along the edge. USA Today, July 27, 2000, pp. 4A.
PHILLIPS, J. D., 1988. The role of spatial scale in geomorphic systems. Geografisker Analer.,
vol. 20 pp. 359-368.


66
Table 4-8. Dependent (human/development) variable details
Dependent Variables
Name
Total Number of Dwelling Units
UN
Density of Dwelling Units per Hectare
UH
Hectares of Impervious Area
IMP
Percentage Impervious Area
PIM
Hectares of Commercial Development
C
(includes Hotels, multi-family over 6
units per structure, offices, port related)
Total Potential Units Adopted in Future
FLU
Land Use Plan
Total Residential Density Adopted in
FLUD
Future Land Use Plan
Total Potential Hectares of Commercial
FLUC
Development Adopted in Future Land
Use Plan
Temporal Scale
Name
Actual
1972
ti
1986
t2
1999 (1997 Brevard)
t3
Dynamic
Change from 1972 to 1986
t2-l
Change from 1986 to 1999(1997 Brevard)
t3-2
Change from 1972 to 1986(1997 Brevard)
t3-l
Appendix A contains source and measurement data for each variable.
Impervious Area (IMP) and Percentage Impervious Area (PIM)
The impervious area and percentage impervious area are more complete measures of actual
development. Impervious areas impact the ability of the dune to act as a sediment store and
aeolian transport (Nordstrom, 1994; Nordstrum and McCluskey, 1985) and prevent the
absorption of water in storm events (Hall and Halsey, 1991). This research uses an adopted
impervious area assumptions for single-family homes. Stormwater runoff at the coast is a major
contributor to non-point source pollution and stormwater permits are required of all development
except single-family residential. The permits, issued by the St. Johns River Water Management
District in both Brevard County and St. Johns require that runoff be stored on site (Von der
Osten, 1993). Local county and municipal regulations mirror the requirement. The standard is
that the first 2.5 cm must be retained on site and the volume of runoff from a site must be no
greater than the runoff before development. The area of each structure and associated


109
When St. Johns County is considered by geomorphic segment, dependent variables with
positive relationships with accretion are the number and density of units, and the future land use
and density adopted for 2015, for Anastasia Island. For Ponte Vedra to Vilano Beach there are no
significant relationships between long-term change and dependent variables. The positive
relationship noted between accretion, higher intensity development, and plans for greater density
in both St. Johns and Brevard County suggest that the long-term coastal change is a variable that
influences development patterns.
Summary of Non-parametric Results by Hypothesis
Tables 5-22 and 5-23 summarize results of the non-parametric analyses for Brevard and St.
Johns County. The relationships between variables that were not predicted by the hypothesis
tested are shaded. In Brevard County the maximum dune height (DH) independent variable did
not exhibit relationships with the dependent variables that would be anticipated. The distance
from the monument to maximum dune height to the monument in both Brevard and St. Johns
County did not support the hypotheses proposed in Chapter 2. The significant results of the
separate geomorphic units in St. Johns County are shown in Table 5-23 and 5-24.
Table 5-22. Summary of non-parametric results by hypothesis, Brevard County
Hypothesis
Independent
Variables
Relationship
Dependent Variables
la-Actual geomorphology
DH,it t2, t3
Negative
IMP tl- t2, o.
and development
MDH ,i q t3
Negative
(IMP, PIM, Qu, a. a.
lb-Actual geomorphology
DH,i, a, t3
Negative
FLUD FLU.3, FLUD 0, FLUC
and adopted future land use
MDHti, t2, t3
Negative
t3
FLUDtl FLU t3 FLUDt3
2a-Dynamic
BWa-,
Positive
UN12.1, UHq.i, IMPi2.i, PIM-i
geomorphology and
BW
Positive
UN UH o-i. PIM ,3.i
development
MDHm
Positive
IMP ,1 a, t3. PIMtli ,2, 13, C,1, (2, t3
LT
Positive
IMP ,i t2 t3 PIM a t3 C t3
2 b-Dynamic
LT
Positive
FLUD,, FLUD,2 FLUD,3
geomorphology and
MDH io,
Positive
FLUD,, FLUD,3
adopted future land use
3-Temporal lag between the
BW,2.,
Positive
UN t3-2, UH t3_2, IMP t3-2, PIM,3.2.
actual and dynamic
geomorphology and the
DH,i, t2 ,3
Positive
UN o-i. UH 0-1, IMP 0-1, PIM,3.,
UNt (3-2, UH t3-2
human variables
DH,!,a t3
Negative
FLUD,, FLUDo
DHBW.2
Positive
FLUo FLUD,, FLUC,,
I 1 Statistical relationship inconsistent with research hypothesis


73
1977; Miller, 1980). The example below shows that the smaller the change in geomorphic
variable from one time period to another, the more suitable for higher levels of human
development or hypothetically a positive relationship. Also the larger the geomorphological
factor variable the more suitable for more intense human development (number of dwelling units,
impervious area). A low factor value represents a large difference in the net and total change and
so a dynamic area. A negative factor value indicates a lower dune or decreasing beach width, for
example.
Table 4-12. Hypothesis 2a, dynamic geomorphic and human variable relationships.
Dynamic
Geomorphology
(Over Entire Period)
Hypothetical
Relationship
Human Variable
(Change Over Period)
Change in Beach Width Index (BWt2.i,
Impervious Area, (IMPtr
BWmBWo.,,BWw);
Change in Dune Height (DHu-i, DH,:,_2
DHu., DHJ;
Change in Distance Monument to
Maximum Dune Height (MDI I;7,
MDHt3.2iMDH3.1 MDH,0,);
Change in Distance NGVD to
Maximum Dune Height (DHBWu.
,, DHBWa.2,DHBW3.| DHBWt01);
Negative
IMPo), Percent Impervious
Area (PIMu-PIMo) Number of
Dwelling Units (UNtr UN^),
Dwelling Units per Hectare
(UH,r Uht3), Commercial
Hectares (Qr C,3)
Factor Variable
Beach Width Index Factor, (BWf);
Dune Height Factor, (DHf);
Distance Monument to Maximum
Dune Height Factor (MDHf);
Distance NGVD to Maximum Dune
Height Factor (DHBWf)
Positive
Impervious Area, (fMP,r
IMPt3), Percent Impervious
Area (PIM.pPIM*) Number of
Dwelling Units (UN,r UNt3),
Dwelling Units per Hectare
(UH,r UHt3), Commercial
Hectares (C,r Ct3)
Hypothesis 2b: The dynamic geomorphology indicators influence the land use control
decision-making. This hypothesis proposes an adaptation of Bush and others (1999) with future
land use outcomes as the result of the characteristics of the physical environment. The example
below shows that the smaller the change in geomorphic variable from one time period to another,
the more suitable for higher adopted future total units and densities. Also the larger the
geomorphological factor variable the more suitable for higher adopted future total units and
densities.


64
Table 4-7. Sample data changes for seaward (east) relocation of monument
1972
Amend:
Monument to maximum dune height reduced 10 m
Beach width index (NGVD to monument) reduced 10 m
Maximum dune height revised to the maximum height
seaward of the repositioned monument position
1979-Monument relocated seaward (east) 10 m
1986
1986 data are unchanged
1999
1999 data are unchanged
Monument data are provided in State Plane NAD 29 and was converted to NAD 83 to be
consistent with the projections of the DOQQs and land use data in the GIS. Appendix E shows
the Brevard and St. Johns County monument position and profile details.
Development Variables
The future land use, units per hectare and percent of impervious areas adjacent to the
profiles are obtained using aerial photography and GIS. The exact location of the monument and
Northing and Easting State Plane coordinates are plotted on the aerials for each site. The
photographs show 400 m inland on average, and where the barrier island is narrow, this inland
extent will also show the sound or river. A 9-ha area centered at the monument is used to
determine the uses and impervious areas immediately adjacent to the monument. The centerline,
or meridian of the 9-ha sample area is centered at the monument.
The physical extent of development, defined as any building or impervious area, defines
the seaward extent of the sample area. For example, if buildings exist closer to the beach than the
monument is located, the sample area is aligned with the seaward extent of development. This
may be the case when the monument is located in the dunes beyond and landward of
development. The seaward extent of the sample area may extend beyond the monument. This
extent is determined by the most recent time period. The 9-ha square has dimensions of 300 m
inland from the monument and 150 m either side of the monument. The appropriateness of


168
Table H-8. St Johns County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW)) and dependent variables at 0.05 significance
DHBW
DHBWa
DHBW,.,
DHBWa.,
DHBWa-z
DHBWa-,
DHBW.O,
DHBWf
UN
0.2297
0.3453
0.3619
0.2686
0.2065
0.3653
-
0.3662
UNn
0.1715
0.2807
0.2709
0.2204
0.1478
0.2964
-
0.2896
UNa
-
-
-
0.1813
-
-
0.1710
-
UNa-,
-
-
-
-
-
-
-
-
UNa-2
-
-
-
-
-
-
-
-
UNa-,
-
-
-
-
-
-
-
-
UH
-
0.2268
0.2101
0.2046
-
0.2400
-
0.2362
UHa
-
-
-
-
-
-
-
-
UH
-
-
-
-
-
-
-
-
UHu.,
-
-
-
-
-
-
-
-
UH.3-2
-
-
-0.2370
-
-
-0.2028
-
-
UHo.,
-
-
-
-
-
-0.1885
-
-
IMP,,
0.1890
0.3333
0.3599
0.2918
0.1812
-
0.1783
0.3910
IMP,2
0.3586
0.4472
0.4428
0.2944
0.0908
0.3194
0.2245
0.3549
IMPa
0.3792
0.4564
0.4304
0.3153
0.0780
0.3503
0.2747
0.3444
impq_,
0.3641
0.3820
0.3378
0.2142
-
0.1678
0.1453
0.1853
IMPa-2
-
-
-
-
-
-
-
-
IMPo-i
0.3496
0.3547
0.3118
0.2047
-
0.2338
0.1881
0.2035
P1M
-
-
0.2341
0.2251
-
-
-
0.2593
PIMt2
0.2333
0.3441
0.3019
0.2421
-
0.2282
0.1739
0.2414
PIMa
0.2899
0.3758
0.3110
0.2506
-
0.2428
0.2163
0.2157
PIMa-,
0.2568
0.2978
0.2266
0.1796
-
-
-
-
PIMa-2
-
-
-
-
-
-
-
-
PIMa.,
0.2784
0.2881
0.2172
-
-
-
-
-
ACC
-0.3860
-0.3658
-0.4567
-0.2376
-0.2337
-0.4035
-0.2484
-0.4117
DACC
0.1838
-
-
-
-
-
-
-
POS
0.3237
0.2272
0.2537
-
-
-
-
-
Qi
-
0.2019
0.2001
0.1786
-
0.1890
0.1927
0.1962
Ca
0.3029
0.3629
0.3492
0.2457
-
-
-
0.2179
Ca
0.3405
0.3847
0.3798
0.2490
-
0.2511
0.2411
0.2283
Ct2-1
0.3416
0.3909
0.3456
0.2702
-
-
-
-
Q3-2
-
-
-
-
-
-
-
-
Q3-I
0.2954
0.3199
0.3117
0.1930
-
0.1918
0.1928
0.1845
FLUD11
0.3952
0.1799
0.1340
-0.0415
-
-0.1247
0.0561
-0.2102
FLUa
0.3823
0.4916
0.4854
0.4562
-
0.4453
0.2959
0.4758
FLIJD,,
0.2700
0.3681
0.3230
0.3692
-
0.2989
0.1959
0.2879
FLUCa
-
-
-
-
-
-
-
-
FLUa
0.3320
0.2921
0.2359
0.2108
-
-
-
-
FLUDt3
0.2560
0.2074
-
-
-0.2643
-
-
-0.1680
FLUCa
-
-
-
-
-
-
-
-


173
Table H-13. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to 198),
Beach Width (BW)) and dependent variables at 0.05 significance
BW
BW,2
BWo
BWa.i
BW.3-2
BW,3.,
BW,0,
BWr
LT
UN
-
-
-
-
-
-
-
-
-
UNa
-
-
-
-
-
-
-
-
0.3799
UN,j
-
0.3680
0.3719
0.3979
-
0.4067
-
-
0.5261
UN,2-,
-
0.3784
-
0.4251
-
-
0.3534
-
0.4072
UNu.2
-
0.3410
0.4020
-
-
0.3465
-
-
0.4840
UN,j.,
-
0.4829
0.4398
0.4662
-
0.4156
0.3367
-
0.5366
UH
-
-
-
-
-
-
-
-
0.3160
UH
-
-
-
-
-
-
-
-
0.3933
UH,3
-
0.3703
0.3623
0.4130
-
0.3950
-
-
0.5299
UHa-i
-
0.3915
-
0.4447
-
-
0.3834
-
0.4432
UHb.2
-
0.3387
0.4084
-
-
0.3469
-
-
0.4694
UHo.,
-
0.4827
0.4386
0.4684
-
0.4092
0.3407
-
0.5304
IMP,,
-
-
-
-
-
-
-
-
0.3021
IMP0
-
-
-
-
-
-
-
_
_
IMP,,
-
-
-
-
-
-
-
-
-
IMP,2-,
-
-
-
0.3096
-
0.3183
0.3505
-
-
IMP,3.2
-
-
0.3198
-
-
-
-
-
0.3054
IMP|3.|
-
-
-
-
-
-
-
-
-
PIM
-
-
-
-
-
-
-
-
-
PIMa
-
-
-
-
-
_
_
_
_
PIM,j
-
-
-
-
-
-
-
-
_
PIM.2.,
-
-
-
-
-
-
0.3505
-
-
PIM.3-2
-
-
0.3262
-
-
-
-
-
-
pim,3.,
-
-
-
-
-
-
-
-
-
ACC
-
0.3272
-
-
-
-
-
-
-
DACC
-
0.3654
0.4446
-
-
0.3696
-
-
0.5574
POS
-
-0.3221
-
-0.3253
-
-
-
-
-
Q,
-
-
-
-
-
-
-
-
-
c
-
-
-
-
-
-
-
-
Co
-
-
-
-
-
-
-
-
-
Ct2-1
-
-
-
-
-
-
-
-
-
Ct3-2
-
-
-
-
-
-
-
-
Ct3-1
-
-
-
-
-
-
-
-
-
FLUD
0.4678
0.5403
0.6907
0.3424
-
0.5847
0.3268
0.3510
-
FLU,2
-
-
-
-
-
-
-
_
FLUDo
-
-
-
-
-
-
_
_
_
FLUCa
-
-
-
-
-
-
-
-
-
FLUo
0.4744
0.6945
0.5828
0.5612
-
0.4639
0.5256
-
0.5660
FLUD.3
0.5412
0.7298
0.6365
0.5346
-
0.4598
0.5368
-
0.6317
FLUCo
-0.3816
-0.3014
-0.4142
-
-
-0.3371
-
-0.4822
-0.4414


62
In the case where the revised monument position is west of the original position the profile,
data recorded after the repositioning are adjusted (Figure 4-9). Relocation landward results from
monument destruction from storms, coastal erosion, profile changes and construction at the
original monument location (Foster 2002, personal communication). Profile data recorded are
amended to reduce the monument to maximum dune height (a), and the beach width index
(NGVD to monument) (b), for consistency amongst all the data sets. The standard of 3m in
north-south variation is assumed not to necessitate amendments in dune height variables (Rahn,
2001). In cases where the maximum dune height occurs at the landward of the original
monument position, the maximum dune height recorded at or seaward of the original position is
used.
In the case where the revised monument position is seaward or east of the original position
the profile data recorded before the repositioning are adjusted (Figure 4-10). Relocation
landward occurs due to construction at the position of the monument and road realignments
(Foster 2002, personal communication). Profile data recorded before the repositioning of the
monument are amended to reduce the monument to maximum dune height (a) and the beach


5-22. Summary of non-parametric results by hypothesis, Brevard County 109
5-23. Summary of non-parametric results by hypothesis, St. Johns County 110
5-24. Summary of non-parametric results by hypothesis, Northern St. Johns County,
Ponte Vedra to Vilano Beach 110
5-25. Summary of non-parametric results by hypothesis, Anastasia Island, St. Johns
County 111
6-1. Summary of bivariate analyses of actual geomorphology and human variables by
jurisdiction 121
6-2. Bivariate analyses of dynamic geomorphology and human variables 123
6-3. Proposed development suitability matrix 128
A-l. Hurricanes and tropical storms that have impacted Brevard County 130
A-2. Hurricanes and tropical storms that have impacted St. Johns County 132
B-l. Dependent and independent variable details 133
E-l. Brevard County Monument position and profile details 139
E-2. St. Johns County Monument position and profile details 144
F-l. Brevard County long term change determination 150
G-l. Descriptive statistics, dependent and independent variables, Brevard County 155
G-2. Descriptive statistics, dependent and independent variables, St. Johns County 156
G-3. Descriptive statistics, dependent and independent variables, Ponte Vedra to
St. Augustine Pass (Monument 1 to 122) St. Johns County 157
G-4. Descriptive statistics, dependent and independent variables, Anastasia Island
(Monuments 141-195), St. Johns County 159
H-l. Brevard County Spearman Rank analyses, Beach Width (BW) and dependent
variables at 0.05 significance 160
H-2. Brevard County Spearman Rank analyses, Dune Height (DH)) and dependent
variables at 0.05 significance 162
H-3. Brevard County Spearman Rank analyses, Monument to Dune Height (MDH)) and
dependent variables at 0.05 significance 163
H-4. Brevard County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW)) and dependent variables at 0.05 significance 164
x


113
perceived improved access and visibly. Higher commercial activity may be areas long impacted
by development, and so with dune fields that have been compromised over time.
Hypothesis lb theorizes that the local geomorphology influences the land use control
decision-making. This hypothesis proposes that future land use plans are developed after
consideration of actual geomorphological conditions (Hails, 1977). The Brevard County adopted
future land use density (FLUDti) is a function of the 1972 dune height, long-term change and
shoreline orientation. The 1972 potential density in Brevard County, reflected in the adopted
future land use, is negatively related to dune height, or lower dunes. Higher future densities were
adopted in areas with low long-term change, or accretion and in the 9-ha sample areas oriented
away from north. The combination of these variables explains over 60 percent of the variation in
1972 future land use densities. It may be concluded that higher densities in 1972 were planned
appropriately for long-term shoreline conditions, but in areas with lower dunes. From a
development perspective lower dunes are more desirable for enhanced coastal visibility.
However, lack of dune protection from erosion, waves and storms make areas with lower dunes
less geomorphically appropriate.
Brevard County, Entire County-1972 Future Land Use Units (FLUD,i)
FLUDtl= 89.915 4.066 DHt, 21.147 LT + 0.821 OR
(11=109, R2 = 0.649)
FLUD,i = Potential Residential Density, 1974 Comprehensive Plan (units per hectare)
DH,i = 1972 Dune Height (m)
OR = Shoreline Orientation (degrees from north)
Similar to the 1972 future land use density, the 1997 total proposed units (FLU,3) is a
function of the dune height during that period (t3). The future land use is also a function of the
1972 distance from the monument to maximum dune height. The 1997 potential total units in
Brevard County, reflected in the 2010 adopted future land use, is associated with areas with lower
dunes, similar to the 1972 density. This, in conjunction with lower distances from the monument
to the maximum dune height in 1972, explains almost half of the variation in the 1997 total units.


17
is occurring as small family units of older people having large lots and second home commuters
from the nearby metropolitan areas (pp. 11). Similarly, along the north coast of new South
Wales, Australia, 35 percent of second homebuyers purchased homes for retirement destinations
(Essex and Brown, 1997).
The economic prosperity of the late 1990s and the new century has contributed to
residential development and the second home market in coastal areas (Overberg, 2000).
However, research in Australia indicates that the economy may not be the most important factor
in coastal location. Walmsley and others (1998) found that pull factors, such as the physical
environment, climate and lifestyle influence development more than push factors, such as
employment prospects and salaries. Polling 150 households that moved to the north coast of New
South Wales, he concluded that migrants to the coast were influenced by image and quality of
life, rather than employment opportunities, pay and working conditions.
Legislated Incentives for Development
Development of Floridas barrier islands has been as a result of the interaction of many
forces. A measure of the importance of the physical amenity of the coastal zone, available
access, local restrictions or incentives is captured in this research, while Federal and State tax
advantages are not. In this research the influence of politics in the study area, or at county level
and the State and National level are also a component of what is reflected in the settlement
patterns. The influence of legislation as an incentive or disincentive for development on the coast
is likely to be equally if not more important, than the physical characteristics.
Several provisions in the Federal tax code have influenced coastal residential development
(Beatley et al, 1994). Deductions for home mortgages on personal income tax returns were
intended to assist home ownership. Second home mortgages can also be deducted providing
additional tax incentives for those affluent enough to afford them. The use of residences for a
commercial enterprise, such as rental property is also subsidized by the tax code (Thom, 2004).
Losses incurred for lack of rental income, or deductions to improve the property are permitted.


the dune crest height was used as a proxy for the condition of the dune field. A low
distance from the crest to a fixed point on the profile represents a stable local
environment. The research showed this to be inconsistent with the data, and concludes
that movement of the crest position seaward represents dune field progradation.
Analyses at the county level showed contrasting approaches to future land use
designations and coastal development. Beach width was a determining variable in St.
Johns County, whereas dune height was more important in Brevard County. The
intensity of development is consistent with the long-term change in both jurisdictions.
This work broadens understanding of the interaction of the physical environment and
human occupation in the coastal zone. Determining relationships between the physical
parameters and types of development provides tools to help coastal managers,
geomorphologists, land use planners, and public officials to maximize access, while
minimizing unintended impacts in coastal areas.
xvi


146
Table E-2. Continued
Monument
Number
Date
Set
Northing Northing
(position 2)
NS
Change Easting Easting
(in m) (position 2)
1
EW
change
(in m)
2
80
Jun-72
2071417.13
396987.89
8!
Jun-72
2070331.86
397217.60
82
Jul-86
2069333.74 2069339.25
-1.68 397410.43 397453.31
-13.07
83
Jun-72
2068287.23
397635.12
84
1995
2067226.08 2067224.61
0.45
397885.14 397886.11
-0.30
85
Jun-72
2066207.09
398122.08
86
1995
Monument replaced >
3m from original
87
Jun-72
2064183.33
398585.38
88
Jun-72
2063162.67
398808.02
89
Jun-72
2062226.11
398999.67
90
Jun-72
2061225.57
399238.55
91
Jun-72
2060196.91
399430.46
92
Jun-72
2059161.55
399642.04
93
Jun-72
2058188.99
399877.97
94
Jun-72
2057183.72
400067.27
95
Jun-72
2056211.45
400261.71
96
Jun-72
2055202.43
400525.80
97
Jun-72
2054206.45
400768.16
98
1995
Monument replaced >
3m from original
99
Jun-72
2052183.11
401190.73
100
Jun-72
2051168.29
401427.64
101
1995
2050145.73 2050152.81
-2.16 401624.22 401645.40
-6.46
102
1995
2049184.59 2049177.14
2.27
401876.61 401869.05
2.30
103
Jun-72
2048209.66
402087.52
104
Jan-79
2047248.24 2047248.24
0.00
402323.27 402323.27
0.00
105
Jun-72
2046282.58
402558.22
106
Jan-79
Monument replaced >
3m from original
107
Aug-86
2044267.32 2044264.00
1.01
403094.99 403123.40
-8.66
108
Jun-72
2043236.49
403395.76
109
1995
Monument replaced >
3m from original
110
Jan-79
2041170.25 2041166.09
1.27
403965.23 403919.26
14.01
111
Jun-72
2040148.68
404231.70
112
Jan-79
Monument replaced >
3m from original
113
Jun-72
2038183.57
404808.90
114
Jan-79
Monument replaced >
3m from original
115
Jun-72
2036177.22
405413.59
116
Feb-84
2035161.69 2035161.69
0.00
405727.89 405727.90
0.00
117
Jun-72
2034104.35
406102.11
118
Jun-72
2033084.26
406485.12
119
Jun-72
2032061.73
406921.04


189
APPENDIX J. Continued
Dependent
FLUD.3
Adjusted R-Squared
0.658865
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
1.95296
0.4338925
4.5010
0.000038
Reject Ho
0.992985
(BWa)J
1.296842E-061.294047E-07
10.0216
0.000000
Reject Ho
1.000000
F-Ratio
100.4325
0.000000
1.000000
T-Critical 2.006647
N=53
FLUD,3 = 1999 Future Land Use Density, Comprehensive Plan (units/hectare)
(BW a)3 = Cubed Value of 1986 Distance from NGVD to Maximum Dune Height (m)
Hypothesis 4: The dependent variables will have different relationships with the
independent variables in the two separate study areas. (Byrnes et al., 1995).
Dep.
Variable
R;
Intercept
P.
Variable
Pt
Variable
Ps
Variable
FLUDh
(n=109)
0.649
-89.915
-4.066
DH
-21.147
LT
0.821
OR
Dependent Variable FLUD,i
Adjusted R-Squared 0.6488
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
-89.91521
24.67579
-3.6439
0.000418
Reject Ho
0.950599
DHtl
-4.065736
1.308955
-3.1061
0.002433
Reject Ho
0.868188
LT
-21.14734
3.318424
-6.3727
0.000000
Reject Ho
0.999993
OR
0.821133
0.1204817
6.8154
0.000000
Reject Ho
0.999999
T-Critical
1.982597
F-Ratio
68.1320
0.000000
1.000000
N=109
FLUDti = Potential Residential Density, 1974 Comprehensive Plan (units per hectare)
DH,i = 1972 Dune Height (m)
OR = Shoreline Orientation (degrees from north)
Table J-l 1. Potential residential density, 1979 Comprehensive plan (FLUDtl) (also hypothesis lb)
St. Johns County
Dep.
Variable
R2
Intercept
P.
Variable
P2
Variable
p3
Variable
FLUD
(n=124)
0.498
9.211
0.022
BW ,|
-0.058
OR
0.085
DACC


92
contained no units and others (monuments 94, 150 and 160) experienced a decrease in the number
of units caused by demolitions and renovations in Ponte Vedra (monuments 15 to 27), and the
removal of mobile home parks (monument 150). Areas of former mobile home parks, when
replaced with single-family homes result in lower densities, and when replaced with multifamily
(greater than 8 units per building) or commercial, higher impervious areas.
Descriptive statistical for the two geomorphic units in St. Johns County, north and south of
the St. Augustine Inlet (Appendix G) show that in the north part of St. Johns County from Ponte
Vedra to Vilano Beach the average number of dwelling units increases from 5.6 in 1972 to 15.5
in 1999 for the 83 9-ha sample areas. The a mean increase of 9.9 units which was lower than the
countywide increase of 10.6 dwellings. In the south part of St. Johns County, known as Anastasia
Island, from St Augustine Beach to Matanzas Inlet, dwelling units increases from 11.5 in 1972 to
24.9 in 1999 for the 44 9-ha sample areas. The standard increased from 12.5 to 25.9, indicating
that by 1999 there was a greater range in the number of dwelling units by sample area. Anastasia
Island has a higher average dwelling unit count per 9-ha sample area than the countywide average
for each time period.
Dwelling Units per Hectare (UH)
The dwelling units per hectare variable is a measure of residential density. It is the ratio of
the number of units in each 9-ha sample area to the hectares available for development. The
hectares unavailable for development include water bodies, conservation areas and parks.
Brevard County residential density increases from 3.2 du/ha in 1972 to 5.0 du/ha in 1997 for the
138 9-ha sample areas (Table 5-5). In Brevard County decreased density occurred where the
single-family units were converted to buildings with greater than 8 units, and land that was
removed from availability for development. The Brevard County Park System was funded by a
sales tax 1986, and had a goal of coastal property acquisition reducing the total available hectares
in the density calculation. Increases in residential density are consistent with the total number of
units (UN) unless the available area decreased.


34
coast of Florida has experienced more direct storm activity than the northeast coast of Florida
(Appendix A).
Table 3-1. Hurricane and tropical storm activity in the study areas
County/Area
Hurricane/
Tropical Storm
Landfalls within
100 km since
1970
Hurricane/
Tropical Storm
Historical Record
Exiting
Hurricane
Historical
Record
Offshore
Hurricane
Historical
Record
Brevard (east
central Florida)
4/2
8/2
6
7
St. Johns
(northeast
Florida)
0/2
2/2
6
4
The distinction between hurricanes and tropical storms was not made before 1890. The
pattern of hurricane activity in Florida shows that storm intensities and numbers have varied.
From 1931 to 1940 there were only six hurricanes. 1941-1950 [was] the most devastating
decade in Floridas history since records were kept (Williams & Duedall, 1997, pp. 18). There
were 12 hurricanes that made landfall during that period compared to only three from 1951 to
1960 (U. S. Army Corps of Engineers, 1992). Brevard County has the distinction of extending
further into the Atlantic than St. Johns County. The cuspate shape of the foreland renders it more
vulnerable than the more embayed St. Johns County. Hurricane David was the first hurricane to
strike the Brevard County area since the storm in 1928. The eye of the hurricane passed over the
coast and moved back offshore, eventually making landfall in northeast. Hurricane Erin, which
later impacted the panhandle of Florida, hit east central Florida in 1994 as a Category 1 hurricane.
There have been two tropical storms that made landfall during the study period, in 1983 and
1994. This area also experiences indirect impacts of offshore hurricanes. For example, Hurricane
Floyd in 1999 threatened the northeast Florida coast but remained offshore and eventually made
landfall in North Carolina. The documented history back to 1872 shows that the region of
northeast Florida experienced only two direct hurricane landfalls in 1880 and 1964. Hurricane
Dora and the storm of 1880 are the only storms to have hit the northeast coast of Florida directly.


APPENDIX A: HURRICANES AND TROPICAL STORMS IN THE NORTHEAST FLORIDA
REGION
Table A-l. Hurricanes and tropical storms that have impacted Brevard County
Date
Name
Area/Landfall/
Characteristics
Type
Source
1871
(Aug)
Unnamed
Hit east central Florida, may not have
been a hurricane
H
Williams &
Duedall (1997)
1876
(Sept.)
Unnamed
Traveled north along the Indian
River Lagoon, or Brevard beaches
(conflicting history)
O
Williams &
Duedall (1997)
1880
(Aug)
Unnamed
Cocoa Beach (conflicting history,
may have been further south)
H
Williams &
Duedall (1997)
1885
(Aug)
Unnamed
Glanced off coast in Brevard County
O
NOAA (1987)
1921
(Oct.)
Category 3
at Tarpon
Springs
Hit at Tarpon Spring on west coast
and exited at Ponce de Leon Inlet
E
Jacobs (1993),
Williams &
Duedall (1997)
1926
(July)
Category 2
Hit south and traveled up the Indian
River Lagoon, 145 km/hr winds, 73.2
cm rainfall
H
Jacobs (1993),
Williams &
Duedall (1997)
1928
(Aug.)
Category 2
Jupiter and traveled up the Indian
River Lagoon
O
Jacobs (1993),
Williams &
Duedall (1997)
1960
(Sept.)
Donna
Indirect impact, exited north of
Brevard County
E
Jacobs (1993),
Reesman
(1994)
1964
(Sept.)
Dora,
Category 2
St. Augustine, North Florida, exiting,
202 km/hr winds, 72.4 cm rainfall,
3.0m. surge
H
Jacobs (1993),
Williams &
Duedall (1997)
1965
(Sept.)
Betsy,
indirect
impact
Indirect impact, 97 km/hr winds at
Melbourne
O
Jacobs (1993),
Reesman
(1994),
Williams &
Duedall (1997),
NOAA (1987)
1968
(Oct.)
Gladys,
category
Exited north after crossing
peninsular, 145 km/hr winds, 72.4
cm rainfall, 2.0m surge
E
Jacobs (1993),
Reesman
(1994),
Williams &
Duedall (1997),
NOAA (1987)
130


136
Table B-l. Continued
Variable Description
Name
Scale
Data Sources
Transformed Variable Examples
Transformation Of All Independent
Variables
Squared
(BW)'
m
1972 Beach Width 1972 Beach Width
Cubed
(BW)J
m
1972 Beach Width 1972 Beach Width *
1972 Beach Width
Log (Independent Variable)
LBW
m
Log (1972 Beach width)
Interactive Variables Examples
Interaction Of All Independent Variables)
Dune Height Dune Height
to NGVD
DHDH
BW
m
Time Specific Independent Variable Time
Specific Independent Variable (1972 Dune
Height 1972 Dune Height to NGVD)
1972 Dune Height *(1972
Dune Height to NGVD)2
DHDH
BW2
m
Time Specific Independent Variable (Time
Specific Independent Variable)2 1972 Dune
Height (1972 Dune Height to NGVD *
1972 Dune Height to NGVD)
(1972 Dune Height)2 1972
Dune Height to NGVD
DH2D
HBWti
m
(Time Specific Independent Variable)2 *
Time Specific Independent Variable (1972
Dune Height 1972 Dune Height) 1972
Dune Height to NGVD
Dummy Variables Examples
All Independent Variables Dummy Variable
Use of Erosion as Dummy
BWER
Continuous
or 0
ER (l=erosion, 0=not designated) *
independent variable (1972 Beach Width)
Use of Structures as Dummy
BWSW
Continuous
or 0
SW (l=structures present, 0=none) *
independent variable (1972 Beach Width)
Use of Renourishment as
Dummy
BW.iRN
Continuous
orO
RN (l=renourishment occurred, 0=none) *
independent variable (1972 Beach Width)
Use of Dune Renourishment
as Dummy (Brevard County
only)
BWRN
D
Continuous
or 0
RND (l=dune renourishment occurred,
0=none) independent variable (1972
Beach Width)
Use of Position of Road as
Dummy
BW.iRO
AD
Continuous
or 0
ROAD (l=nearest coast >100m, 2=100-
200m from sample area seaward extent,
3=0ver 200m from sample area seaward
extent, 4=more than 1 parallel road in
sample area) independent variable (1972
Beach Width)


132
Table A-2. Hurricanes and tropical storms that have impacted St. Johns County.
Date
Name
Area/Landfall/
Characteristics
Type
Source
1898
(Oct)
Unnamed
Femandina Beach, 73.5 cm rainfall
H
Williams &
Duedall (1997)
1921
(Oct.)
Category 3
at Tarpon
Springs
Hit at Tarpon Spring on west coast
and exited to ocean and Ponce de
Leon Inlet
E
Jacobs (1993),
Williams &
Duedall (1997)
1944
(Oct.)
Unnamed
Existed at Fernandina Beach, 3.7m
storm surge
E
Jacobs (1993),
Reesman (1994),
Williams &
Duedall (1997)
1960
(Sept.)
Donna
Indirect impact, exited south of
area at Daytona
E
Jacobs (1993),
Reesman (1994)
1964
(Sept.)
Dora,
Category 2
St. Augustine, North Florida, 202
km/hr winds, 72.4 cm rainfall,
3.7m surge
H
Jacobs (1993),
Williams &
Duedall (1997)
1968
(Oct.)
Gladys
Exited after crossing peninsular,
145 km/hr winds, 72.4 cm rainfall,
2.0m surge
E
Jacobs (1993),
Williams &
Duedall (1997),
NOAA (1987)
1979
(SePO
David,
Category 2
Traveled north up the east coast of
Florida, exited at New Smyrna
O
Jacobs (1993),
Reesman (1994)
1984
(Sept.)
Diana,
Tropical
Storm
Close to shore between
Jacksonville and Daytona, 112
km/hr winds
O
Williams &
Duedall (1997)
1996
(Ag)
Fran
Remained offshore and made
landfall in North Carolina
O
Williams &
Duedall (1997)
1999
(Sept)
Floyd
Remained offshore and made
landfall in North Carolina
O
FDEP (2000)
2004
(Aug)
Charley,
Category 3
Landfall at Punta Gorda, FL,
exited at Daytona Beach
E
(FDEP 2004b)
2004
(SeP)
Frances,
Category 2
Landfall at Sewalls Point, FL.
TS
FDEP (2004a),
FDEP (2004b)
2004
(SePt)
Jeanne,
Category 3
Landfall at Hutchinsons Island,
FL. TS conditions in St. Johns
TS
FDEP (2004a),
FDEP (2004b)
Characteristics noted reflect peak winds, minimum pressure and maximum surge recorded in the
northeast Florida region. Data after 1945 is considered reliable. H = Hurricane, TS = Tropical
Storm, E = Exiting at coast, O = Offshore


152
Table F-l. Continued
Monument
End
Point
(m)
Rate Averaging
(Olsen 1989)
(m)
Difference
(m)
Average of
Olsen and End
Point
(m)
(LT) Adjacent
Average
(m)
79
80
81
0.14
0.15
0.01
0.15
0.13
82
0.07
0.15
0.08
0.11
0.10
83
0.06
0.00
-0.06
0.03
0.06
84
0.06
0.00
-0.06
0.03
0.02
85
-0.03
0.00
0.03
-0.01
0.01
86
87
88
0.20
0.00
-0.20
0.10
0.10
89
0.19
0.00
-0.19
0.10
0.10
90
0.21
0.00
-0.21
0.11
0.09
91
0.12
0.00
-0.12
0.06
0.08
92
0.13
0.00
-0.13
0.06
0.07
93
0.15
0.00
-0.15
0.07
0.06
94
0.05
0.00
-0.05
0.03
0.05
95
0.11
0.00
-0.11
0.06
0.04
96
0.05
0.00
-0.05
0.03
0.03
97
-0.01
0.00
0.01
0.00
0.01
98
99
100
101
102
103
104
105
106
107
108
-0.03
0.00
0.03
-0.01
0.00
109
0.03
0.00
-0.03
0.02
0.00
110
111
-0.02
0.00
0.02
-0.01
-0.02
112
-0.05
0.00
0.05
-0.02
0.00
113
0.06
0.00
-0.06
0.03
0.02
114
-0.04
0.15
0.20
0.05
0.04
115
116
0.09
0.15
0.07
0.12
0.12
117
118
119
120
0.09
0.15
0.06
0.12
0.12
121
122
0.18
0.15
-0.03
0.17
0.16


28
beaches in Florida (Foster, 1992) representing over 25 percent of the sandy shores in the United
States (Morgan and Stone, 1985).
The most dominant feature along Florida coast is the presence of barrier islands (Davis et
al., 1992). Pilkey and Dixon (1996) identity four conditions that must exist for barrier island
formation. These are sea level rise, gently sloping coasts, a source of sediment, and a wave
regime suitable for transporting sand. The favorable factors for barrier island development are
present in Florida and explain the dominance this feature. The only areas of Florida that do not
have barrier islands are the Florida Keys and the Big Bend area (Figure 2-1), which lacks
sufficient wave energy and an adequate sediment supply (Lannon and Mossa, 1997).
Barrier Islands
Barrier island shapes are determined by coastal conditions. The coast of Florida has been
classified from moderate to zero energy environments (Tanner, 1960), and the study areas are
microtidal (Davis and Fox, 1980; Davis, 1994; Davis 1997). Typical of microtidal wave
dominated conditions, the barriers are long and narrow with few inlets and have smooth
uninterrupted shorelines. Inlets are traditionally unstable with large flood deltas and are prone to
migration and closure if not stabilized. Dunes, and in areas that are prograding, dune ridges, are
usually present (Davis, 1994a). The barrier island system of Florida has developed in the last
3000 years (Davis, 1994b). Florida was a large carbonate platform covered with shallow seas
100 million years ago. Sediments from the southern Appalachians were carried along both coasts
of Florida during the Pleistocene. There are minimal terrigeous sediments entering the system
and the sediment from rivers is trapped within estuaries. Therefore, barrier islands are formed
from the reworking of old sediments enabled by the slow rate of sea level rise.
Sea level rise during the Holocene, along with wave and tide climates influenced the
formation of barrier islands. Sea level rise has continued from 15 to 18,000 BP to present. The
rise was most rapid until 7,000 BP, when the rate slowed. There are a variety of scenarios
proposed on sea level rise rates, and the rate and change in sea level rise is dependent on


187
APPENDIX J. Continued
Hypothesis 2: The dynamic geomorphology impacts human variables
Hypotheses 2a: The dynamic geomorphology indicators influence the actual human
variables. (Lundberg and Handegard, 1996; McMichael, 1977; Miller, 1980).
Table J-6. Percent impervious area (PIMp) Brevard County, 1997
Dep.
Variable
R2
Intercept
Pi
Variable
P2
Variable
Pi
Variable
PIMo
(n=l 10)
0.552
-379.003
-0.124
BWtot
-39.611
LT
2.584
OR
Dependent Variable
PIMo
Adjusted R-Squared
0.5515
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
-379.0029
41.24565
-9.1889
0.000000
Reject Ho
1.000000
BWtot
-0.1237122
6.021266E-02
-2.0546
0.042355
Reject Ho
0.530388
LT
-39.61076
9.626182
-4.1149
0.000076
Reject Ho
0.982901
OR
2.583614
0.2599153
9.9402
0.000000
Reject Ho
1.000000
T-Critical
1.982383
F-Ratio
46.0940
0.000000
1.000000
N=110
PIMo = 1997 Percent Impervious Area (%)
BW ,0, = Total Beach Width Change, absolute value (m)
LT = Long term Change, 1870-1999, (m)
OR = Shoreline Orientation (degrees from north)
Hypothesis 2b: The dynamic geomorphology indicators influence the land use
control decision-making, (adaptation of Bush et al., 1999)
Table J-7. Future land use units (FLUp) Brevard County, 1997
Dep.
Variable
R2
Intercept
P,
Variable
P2
Variable
FLU0
(n-113)
0.351
267.215
287.849
LTSW
-0.614
BW a
ROAD
Dependent Variable FLU ^
Adjusted R-Squared 0.3509
Independent Regression
Variable Coefficient
Intercept 267.2149
LTSW 287.8491
B W a ROAD -0.6139084
T-Critical 1.981567
Standard T-Value
Error (Ho: B=0)
26.93647 9.9202
65.976 4.3629
8.893248E-02-6.9031
Prob Decision
Level (5%)
0.000000 Reject Ho
0.000029 Reject Ho
0.000000 Reject Ho
Power
(5%)
1.000000
0.990983
0.999999


60
Coastline
ROAD = 3
ROAD = 2
ROAD = 1
9-hectare sample area
Figure 4-6. Determination of highway location (ROAD) variable
Figure 4-7 shows the calculation of total beach width change. The net change from 1972
to 1997 (BWo-i) is 20 m for both examples, and is the total change for a. However, the total
change (BWtot) is 40 m for profile b. Total change is the cumulative change from the initial data
year to the final year. The total beach width change value is always positive (or zero) because the
value is the sum of the change in the shoreline position of the edge of the beach each year.
Profiles that experience both erosion and accretion will have a much larger total beach width
change than net beach width change. The net variation and total variation in maximum dune
height is also calculated using the same methodology. Variations in the distance from the point
of maximum height to NGVD are also used as an indicator of a geomorphically dynamic area.
A factor for each of the geomorphic variables is developed using the Total and Net
changes. The factor is a ratio of the Net change to Total change. The Total change is an absolute
value, whereas the Net change value can be positive or negative. The Factor maximum value is
1.0 and minimum is -1.0. A Beach Width Factor (BWf) of 1.0 represents a beach width that has
accreted from the first measurement to the last (Figure 4-6a). A negative Beach Width Factor
indicates that the shoreline has retreated during the time period. In both Figure 4-8 a) and b) the
Net Beach Width (from the 1972 to 1997) is 20 m. The Total change is 20 m for a) and 40 for b).
Monument
100m


114
Lower values for the distance from the monument to maximum dune height are hypothesized to
be an indicator of a stable dune field. Areas with stable dune fields are more suitable for higher
number of units. The 1972 variable also supports hypothesis 3, in that the FLU^ is a function of
the geomorphology in an earlier time period. In this case extensive coastal research was
completed in 1972 (Brevard County Planning Department, 1972) that served as the base data for
later recommendations.
Brevard County, Entire County-1997 Future Land Use Units (FLU ,3)
FLUts =547.346-71.231 DHt3-1.337MDHtl
(n=l 06, R2=0.479)
FLUo = Potential Units, 1999 Comprehensive Plan
DH3= 1997 Dune Height (m)
MDH,i = 1972 Distance from Monument to Maximum Height (m)
In Brevard County, a similar relationship between total number of units adopted in the
2010 future land use plan and 1997 dune height is noted in conjunction with the 1986 beach
width, weighted by the road location. The negative relationship with the road weighted beach
width indicates that the further the parallel access from shore, the higher the total units. If the
parallel highway is further inland, the area seaward of the highway and available for development
is larger. In Brevard County such areas are characterized by the development of shore-
perpendicular roads and high residential densities, or commercial activities. In St. Johns County
north of Vilano Beach, Highway A1A was moved inland and property was accumulated under
single ownership. The resulting area is being developed as high-density (over 60 du/ha) family
development called Serenata Beach.
Brevard County, Entire County-1997 Future Land Use Units (FLU ,3)
FLUt3 = 608.833 76.111 DH 0.388 BW ^ROAD
(n=105, R2=0.517)
FLU t3 = Potential Units, 1999 Comprehensive Plan
DH t3 = 1997 Dune Height (m)
BW aROAD = 1986 Beach Width (m) weighted by the position of the parallel access (3-
<100m inland, 2-100m to 200m inland, l->200m inland, 4 more than 1 parallel access road)


161
Table H-l. Continued
BW
BWa
BW BWc.,
BWo.2
BWa,
BWt0, BWf
LT
Qi
-
-
-
0.1896
-
0.3454
0.2786
C
-
-
-
-
-
0.3489 -
0.2716
Cu
-
-
-
-
-
0.3364 -
0.3015
Q2-1
-
-
0.2000
-
-
-
-
Ct3-2
-
-
0.1980
-
0.2078
-
-
Ct3-1
-
-
0.2537
-
0.2249
0.2019 -
0.2107
FLUD
-
-
-
-
-
0.4639 -
0.3172
FLU.3
-0.1836
-
-
-
0.2363
0.4046
0.3299
FLUDc3
-
-
-
-
-
0.3804
0.3037
FLUCU
-
-
-
-
-
-
-


144
Table E-2. St. Johns County Monument position and profile details
Monument Date
Number Set
Northing Northing
(position 2)
NS
Change Easting Easting
(in m) (position 2)
1
EW
change
(in m)
2
i
Jun-72
2151940.35
379681.86
2
Jun-72
2150939.04
379906.64
3
Jun-72
2149962.53
380124.53
4
1995
2149012.72 2149014.45
-0.53
380332.33 380338.24
-1.80
5
Jun-79
2148015.11 2148016.92
-0.55
380332.33 380564.46
-70.75
6
Jun-72
2147032.27
380787.71
7
Jun-72
2146036.28
381013.14
8
Jun-72
2145049.30
381235.83
9
Jun-72
2144045.63
381465.14
10
1995
2142995.74 2142991.46
1.31
381709.32 381697.97
3.46
11
1995
2141978.43 2141979.43
-0.31
381943.82 381945.26
-0.44
12
Jun-72
2140909.86
382189.05
13
Jun-72
2139874.45
382471.06
14
Jan-84
2138789.89 2138790.16
-0.08
382736.89 382737.85
-0.29
15
May-84
2137737.55 2137736.88
0.20
383002.67 383001.40
0.39
16
Jul-86
Monument replaced > 3m from original
17
Jun-72
2135718.15
383504.00
18
Jun-72
2134730.17
383776.22
19
Jun-72
2133735.63
384042.45
20
Jun-72
2132738.50
384253.30
21
Jun-72
2131727.80
384493.70
22
Jun-72
2130724.03
384687.52
23
1995
Monument replaced > 3m from original
24
Jun-72
2128728.69
385169.08
25
Jun-72
2127709.24
385409.38
26
May-84
2126711.64 2126711.64
0.00
385651.96 385651.96
0.00
27
Jun-72
2125718.56
385904.01
28
Jun-72
2124677.71
386095.03
29
Jun-72
2123703.93
386352.13
30
Jun-72
2122677.47
386526.67
31
Jun-72
2121671.81
386789.35
32
Jan-79
Monument replaced > 3m from original
33
Feb-84
Monument replaced > 3m from original
34
Jun-72
2118620.47
387441.59
35
Jan-79
2117655.75 2117656.14
-0.12
387657.93 387656.84
0.33
36
Jun-72
2116619.01
387874.65
37
Jun-72
2115584.45
388105.19
38
1995
2114563.50 2114569.80
-1.92
388314.26 388316.42
-0.66
39
Jun-72
2113528.29
388543.45


35
Figure 3-2. Coastal municipalities and geomorphic characteristics, St. Johns County, Florida


54
The rate calculation method (figure 4-5), which averages all the long-term rates of change,
reduces the influence of random profile variability, seasonal influences and measurement error
inherent in the different data types. The rate averaging calculation is considered the most
accurate of the methods (Foster and Savage, 1989) although the comparative methodology using
all three produces long-term shoreline change rates less influenced by extreme values derived
from a specific methodology.
Last
End Point Rate
Least Squares Fit
Time
Shoreline position record
Figure 4-4. Calculation of long-term shoreline change, end point and least square fit methods
Shoreline
position
from
monument
(m)
m Rates determined to be long-
Shoreline position record term by DEP
Figure 4-5. Calculation of long-term shoreline change, rate-averaging method


103
Table 5-11. Beach width factor and human variables in St. Johns
Year
UN(n=138)
Human Development Variables
IMP (n=138) PIM (n=134)
FLU (n=138)
1972
0.3999
0.4125
0.2280
NA
1986
0.2750
0.3996
0.2026
0.5510
1999
0.1892
0.3531
-
0.2433
95% confidence interval
Maximum Dune Height (DH)
The actual geomorphology or dune height in each time period (DH,i, DHt2, DH^) has a
negative relationship with development variables in Brevard County (Tables 5-12 and 5-13). For
example, higher numbers of actual and future units were associated with smaller dunes. This
does not support Hypothesis la, which would anticipate a positive relationship between
maximum dune height and impervious area, or higher dunes being an indicator of an area that is
suitable for more intense development. Hypothesis 2a also proposes that future land uses would
be more intense in areas with higher dunes but the relationship is negative.
Table 5-12. Dune height and impervious area in Brevard County
Impervious Area
Maximum Dune Height (DH)
(IMP)
1972
1986
1997
1972
-0.607
NA
NA
1986
-0.620
-0.644
NA
1997
-0.603
-0.642
-0.627
95% confidence interval, NA=temporal antecedence,
Table 5-13. Dune height and future land use density in Brevard County
Future Land Use
Dune Height (DH)
1972
1986
1997
1972 (FLUD)
-0.7220
NA
NA
1997 (FLUtf)
-0.5742
-0.5603
-0.5792
1997 (FLUDo)
-0.6357
-0.6210
-0.6499
1997 (FLUC,,)
-0.4402
-0.3710
-0.3848
95% confidence interval, NA=temporal antecedence,
In Brevard County the maximum dune height is higher to the south of the county where
densities are lower. The relationship between dune height and impervious area is one that would
be expected of a shoreline that has been developed since the beginning of the study period.
Where there are large impervious areas, sediment cannot be stored inland in dunes for coastal
protection during storm events. In the event of high wave activity, the dunes seaward of the


71
** COMMERCIAL
HIGH DENSITY
RESIDENTIAL
LA INSTITUTIONAL
ALOW\MEDIUM
RESIDENTIAL
RIGHTS-OF-WAY
VACANT
WATER
Permitted
Density (mid
range) Area =
26 Potential
Residential
Units
Figure 4-13. Determination of future land use total units (FLU) in 9-ha sample area
Figure 4-14. Determination of future land use density of units (FLUD) in 9-ha sample area


Figure 1-1. Brevard County Monument to highest point variations with trend, 1972-1997 (MDHt], MDHQ, MDH,i)
Sebastian Inlet


X1972 Distance from Monument to Highest Point 1986 Distance from Monument to Highest Point
1999 Distance from Monument to Highest Point
Figure 1-4. St. Johns County Monument to highest point variations, 1972-1999 (MDH,i, MDHt2, MI)¡ 1.;)


Inaccurate Assumptions and Hypotheses Misspecifications 125
Potential for Future Research 127
APPENDIX
A HURRICANES AND TROPICAL STORMS IN THE NORTHEAST FLORIDA
REGION 130
B DEPENDENT AND INDEPENDENT VARIABLE DETAILS 133
C SAMPLE RAW DATA FROM THE DEPARTMENT OF ENVIRONMENTAL
PROTECTION 137
D USE OF AERIAL PHOTOGRAPHY AND EXCLUSION OF AREAS
UNAVAILABLE FOR DEVELOPMENT 138
E COUNTY MONUMENT POSITION AND PROFILE DETAILS 139
F BREVARD COUNTY LONG TERM CHANGE DETERMINATION 150
G DESCRIPTIVE STATISTICS, BREVARD AND ST. JOHNS COUNTY 155
H NON-PARAMETRIC STATISTICS (SPEARMAN RANK) ROW WISE
CORRELATIONS, BREVARD AND ST. JOHNS COUNTY 160
I TIME SERIES GEOMORPHIC VARIABLES 177
J REGRESSION RESULTS, BREVARD AND ST. JOHNS COUNTY 184
LIST OF REFERENCES 191
BIOGRAPHICAL SKETCH 203
vii


55
Foster and Savage (1989) suggest that the averaging of shoreline change rates between
adjacent profiles, or longshore averaging, minimizes errors. The length of the segment of
coastline included in the longshore average is important. A segment that is too long will
oversimplify and obscure local conditions. A segment that is too short may be impacted by an
individual profile that is not reflective of the segment. The number of points selected is also
determined by local conditions, such as the extent of coastal structures and the presence of inlets.
Projections of shoreline change are made in light of the current conditions. It is reasonable to
assume that a single storm event in the future could render the estimates invalid. Similarly areas
experiencing substantial changes may reach equilibrium and the rate of change will slow. In
locations where coastal structures are present, rate of change may temporarily cease when the
structure is reached (Wright, 1991).
This methodology does not accommodate the influence of sea level rise, land subsidence or
emergence. Foster (1992) does not consider these to be significant factors in Florida for the
calculation of long-term (greater than 100 year) shoreline change. He concludes that the impacts
of sea level rise are obscured by the variability in tides, storms and longshore sediment
transportation. The impact of shoreline protection structures and beach renourishment are also
random (Foster, 1992). Data frequencies used in this research area also insufficient to illustrate
such short-term impacts as seasonal changes and the influences of wave and tidal climates. The
timeframe considered in this research is insufficient for sea level impacts to be quantified and
infrequent enough for short-term influences with records only each decade. However, while the
timeframe is unsuitable for these scales it is well suited for the analysis of development and plans
for development. A longer spectrum would take the research beyond the development horizon
and required future land use planning documentation.
Long-term change evaluation Brevard County has not been conducted to by the FDEP.
However, long-term shoreline change rates are derived using the Historical Shoreline Position


13
consistently narrower where the shore was stabilized, except where groins and renourishment
occurred.
Stanczuk (1975), A1 Bakri (1996), Bush and others (1999), and Rahn (2001) evaluated the
influence of development on beach profile changes at smaller scales. Stanczuk (1975) evaluated
36 profiles over a 4-month period on Bogue Banks, North Carolina. He noted that on a small
scale developed areas updrift prevented sediment movement, caused changes in profile width and
gradient, and prevented the profile from recovering from the impacts of seasonal changes and
storms. Bush and others (1999) used beach width, slope, and elevation derived from profile data
to develop qualitative geoindicators. These indicators were expanded for use along the North
Carolina coast for risk assessment and hazard mitigation. Rahn (2001) compared the beach
profiles in developed and undeveloped sites in two areas of the Florida panhandle.
The major shortcomings of beach profile data are the spatial and temporal frequency of
data collection. Temporal frequency is a concern because of the dynamic nature of the coast.
Profile data give specific information only for the time period during which they were collected.
The data provide no indication of historical or seasonal changes, nor can they be used to predict
the future (Stanczuk, 1975). The beach profiles Stanczuks study are a snapshot of the beach
morphology at a specific time. This is a problem because beach profiles are extremely dynamic
and sensitive to storm or seasonal conditions. Similarly the coarse scale alongshore will not
reflect a continuous surface. The data cannot be used to interpolation shore-normal topography at
this scale. The individual profiles are used in conjunction with development variables recorded in
the adjacent sample areas at the transect. Using profile data over the study period to determine
dynamic geomorphology variables reduces the influence of outlying values. The Department of
Environmental Protection conducts data collection for evaluating beach conditions during the fall
and spring, at times when storm activity has been minimal.
Seasonal variations reflected in the profile data taken at different times of year may also
lead to inconsistencies or errors. Wright (1991) used dry-beach width during summer, to


200
SHIDELER, G. L., and SMITH, K. P., 1984. Regional variability of beach and foredune
characteristics along the Texas Gulf Cost barrier system. Journal of Sedimentary
Petrology, vol. 54, no. 2, pp. 507-526.
SMITH, A. W. S., 1994. Response of beachfront residents to coastal erosion along the
Queensland Gulf Coast, Australia. Journal of Coastal Research, vol. 12, pp. 17-25.
SNELL, B., 2004. Rock Bottom, the stormy summer created 50 years of erosion overnight.
Florida Trend, November 2004, pp. 24.
SOUTH FLORIDA REGIONAL PLANNING COUNCIL, 1989. Strategies for Addressing
Coastal Issues. FAU/FIU Joint Center for Environmental and Urban Problems, 125 pp.
STANCZUK, D. T., 1975. Effects of development on barrier island evolution, Bogue Banks,
North Carolina. Duke University Masters Thesis, Durham, NC, 126 pp.
STAPOR, F. W., and MAY J. P., 1983. The cellular nature of littoral drift along the northeast
Florida Coast. Marine Geology, vol. 51, pp. 217-237.
STONE, G. W., FISCHER, D. W., and MORGAN, J. P., 1985. The variability of Florida's coast
to Storm Wave Susceptibility. Journal of Shoreline Management, vol. 1, pp. 81-104.
STONE, G. W., and SALMON, J. D., 1988. Hurricane-related morphodynamics and
implications for hazard mitigation, Perdido Key, Florida, USA. Coastal Management, vol.
16, pp. 245-270.
SUDAR, R. A., POPE, J., HILLYER, T., and CRUMM, J., 1995. Shore protection projects of the
US Army Corps of Engineers. Shore and Beach, April, pp. 3-16.
SWIFT, D. J. P., 1975. Barrier island genesis: evidence from the central Atlantic shelf, eastern
USA. Sedimentary Geology, vol. 14, pp. 1-43.
TANNER, W. F., 1960. Florida Coastal Classification. Transactions of the Gulf Coast
Association of Geological Societies, vol. 10, pp. 259-266.
THIELER, E. R., and DANFORTH, W. W., 1992. The Digital Shoreline Mapping and Analysis
System DSMS/DSAS; a new method for obtaining shoreline change data from maps and
aerial photographs. Eos, Transactions, American Geophysical Union, vol. 73, no. 43, pp.
288-289.
THOM, B., 2004, Geography, planning and the law: A coastal perspective. Australian
Geographer, vol. 35, no. 1, pp. 3-16.
TOTH, D. J., 1988. Salt water intrusion in coastal areas of Volusia, Brevard and Indian River
Counties. St. Johns River Water Management District, technical publication No. SJ 88-1,
160 pp.
ULLMANN, O. P., OVERBERG, P., and HAMPSON, R., 2000. Growth Reshapes Coast. USA
Today, July 27, 2000, Section 5A


59
The bridge north of St. Augustine Pass provides access at monument 121 on US AIA. St.
Augustine Beach is provided access by the Bridge of Lions (State Road 214) and the State Road
312 bridge that reaches the coast at monument 140. State Road 206 provides access to Anastasia
Island at Crescent Beach at monument 174.
ROAD, or location of access in the 9-ha sample areas, was recorded using the DOQQs in
the T3 period. The location of the shoreline parallel access is a measure of the potential for
development locations. This variable was weighted from a value of 1 to 4 using the location of
the shore-parallel access, shown in Figure 4-6. Location of the road in the seaward third, or first
100 m of the 9-ha sample area was designated a 3. The exception to the diagram below was the
presence of more than one shore parallel highway, which was designated as a 4.
Dynamic Geomorphology Variables
The dynamic geomorphology variables are a measure of the amount of change each
variable has experienced over the study period. Beach width is used to illustrate the concept the
net (BWtf.i) and total change (BWtot) variables (Figure 4-7). The calculated beach width for each
profile, for each time period is used to determine the net and total beach width changes. The net
change is calculated by subtracting first recorded width (BWti) from the most recent beach width
(BW,3). A positive value over the study period indicates net accretion, or increase in the distance
to NGVD from the monument. The net change provides a measure that is an important indicator
of the 27-year pattern. This is the same method used to calculate the end point rate, a component
in the Long Term Shoreline change variable. In areas where continuous changes have occurred,
the net change shows the net effects regardless of the series of events, storm impacts or variation
in the times of year the data was collected. Using this variable, data anomalies are smoothed.
Beach width variations reflect areas along a barrier island that are more dynamic, those that erode
and recover more than adjacent areas. The total beach width change variable represents the total
changes in beach width for the entire time period.


149
Table E-2. Continued
Monument Date
Number Set
Northing
Northing
(position 2)
NS
Change Easting
(in m)
1
Easting
(position 2)
EW
change
(in m)
2
198
Jul-86
Monument replaced > 3m from original
199
Jun-72
1950313.29
428953.79
200
1995
1949330.77
1949336.57
-1.77
429181.89
429186.98
-1.55
201
Jun-72
1948349.60
429461.86
202
Jun-72
1947377.53
429714.76
203
Jun-72
1946403.51
430046.87
204
1995
1945422.29
1945414.55
2.36
430345.73
430320.48
7.69
205
Jul-86
1944435.88
1944443.13
-2.21
430640.02
430628.51
3.51
206
Jun-72
1943461.44
430951.19
207
Jun-72
1942475.66
431257.00
208
Jun-72
1941525.40
431632.38
209
Jun-72
1940544.78
431959.23
Notes
1 Negative sign represents movement to south of original position
2 Negative sign represents movement to west of original position
No data in 1972, 1986 position used as
* original


39
Atlantic
Avenue
Gas Station
Motel Pool
Monument
32
Street N
Motel Pool
Monument
32
Street N
Atlantic
Avenue
Gas Station
Figure 3-3. Urbanization at monument 32, Brevard County. A) 1974. B) 1986.


4-14. Hypothesis 3, lagged geomorphic and human variable relationships 75
4-15. Hypothesis 4, variable interactions by jurisdiction 75
5-1. Descriptive statistics, beach width (BW) 81
5-2. Descriptive Statistics, maximum dune height (DH) 84
5-3. Descriptive Statistics, maximum dune height (DH), Anastasia Island 84
5-4. Descriptive statistics, long-term change (LT), orientation (OR) and monument
position from north (POS), distance to access (ACC) and distance and direction
to access (DACC) 90
5-5. Descriptive statistics, density (UH), and future land use density (FLUD) 95
5-6. Descriptive statistics, percentage of impervious area (PIM) 98
5-7. Beach width change 1972 to 1986 and development variables in Brevard County 100
5-8. Beach width and impervious area in St. Johns County 101
5-9. Beach width and future land use in St. Johns County 102
5-10. Beach width and future land use in St. Johns County (monuments 141 to 198) 102
5-11. Beach width factor and human variables in St. Johns 103
5-12. Dune height and impervious area in Brevard County 103
5-13. Dune height and future land use density in Brevard County 103
5-14. Dune height and human variable change (1986 to 1997) in Brevard County 104
5-15. Distance from the monument to maximum height and development variables in
Brevard County 105
5-16. Distance from the monument to maximum dune height and future land use in
Brevard County 105
5-17. Distance from the monument to maximum dune height and development variables in
Brevard County 105
5-18. Lagged relationship between the 1986 distance from dune height to NGVD
and adopted future land use variables in Brevard County 107
5-19. 1999 Distance from dune height to NGVD and change in human variables in
St. Johns County 107
5-20. Long term change, development and future land use variables, Brevard County 108
5-21. Long term change, development and future land use variables, St. Johns County 108
IX


127
Potential for Future Research
The timeframe for this research is suitable for the evaluation of developmental
characteristics. The 11 to 14 year time span between records enables the research to consider the
extent to which plans have been followed and development has occurred. An important
consideration for future research is the overlay of geomorphic data at the same temporal scale.
Data available at more frequent intervals would provide improved insight into geomorphic
patterns. The long-term change variable best illustrates the use of geomorphology that is
compatible with the dependent variables selected. However, this research does provide a
methodology to develop physio-human modeling and evaluate the policy implications of land use
planning. Modeling techniques such as GIS in conjunction with LIDAR will experience similar
issues, in that the amount of data colleted spatially are even more fine-grained than this research
and are difficult to compare to developmental variables which make take years to be evidenced.
The quantification of human behavior in the form of coastal development patterns is made over
30 years, beyond which the impact of long-term anecdotal knowledge of coastal characteristics is
difficult to quantify.
This methodology evaluating the impact of the physical environment on human variables
can be applied throughout Florida. Data are available for at least three time periods for coastal
counties in Florida. The potential for application of this research includes the production of a
stratified classification system that could serve as a guideline for development suitability. The
classification shown in Table 6-3 is an example of designation by development suitability. Areas
with high long-term change, or accretion, and higher dunes, and areas with long-term accretion
and wider beaches, are most suitable for development. Areas experiencing long-term erosion,
low dunes and narrow beaches are least suitable for development. A simple numeric suitability
scale could be applied alongshore as a development guide. The application of the criteria in
Table 6-3 to St. Johns County would result is a classification of 1 on central Anastasia Island and
a value of 3 at Summer Haven, south of Matanzas Inlet.


25
an immediate timescale without inaccurate conclusions. Van Der Wal (2004) used a 15-year
evaluation of renourishment to determine delayed impacts of the activity.
Hypothesis 4: The dependent variables will have different relationships with the
independent variables in the two separate study areas.
The explanatory power of the individual variables will be different in each county. For
example, the influence of the shoreline orientation, drift direction and storm history in each
county will make the local geomorphology less significant due to the larger scale and longer-term
impacts. The regression coefficients and significant variables for each county will be different.
Schwartz (1971) and Shideler and Smith (1984) show that areas cannot be evaluated without
those adjacent. In this research the two counties are not adjacent, and governed by different
policy-making bodies. Thus conclusions about the two counties are likely to be dissimilar. Davis
(1997) used research along the Gulf of Mexico coast and demonstrated the alongshore variability.


154
Table F-l. Continued
Average of
End Rate Averaging Olsen and End (LT) Adjacent
Point (Olsen 1989) Difference Point Average
Monument (m) (m)(m)(m)(m)
167
168
169
170
-0.03
0.16
0.15
0.00
0.15
0.14
171
0.10
0.15
0.06
0.12
0.17
172
0.16
0.30
0.15
0.23
0.18
173
0.08
0.30
0.23
0.19
0.20
174
0.08
0.30
0.23
0.19
0.19
175
176
177
0.15
0.46
0.30
0.31
0.31
178
179
0.24
0.61
0.37
0.42
0.38
180
0.07
0.61
0.54
0.34
0.38
181
182
0.24
0.46
0.22
0.35
0.34
183
0.21
0.46
0.24
0.34
0.32
184
0.10
0.46
0.36
0.28
0.27
185
0.09
0.30
0.22
0.20
0.23
186
0.11
0.30
0.20
0.21
0.20
187
0.10
0.30
0.20
0.20
0.21
188
0.16
0.30
0.14
0.23
0.22
189
0.15
0.30
0.16
0.23
0.23
190
191
0.13
0.30
0.18
0.22
0.24
192
0.24
0.30
0.07
0.27
0.24
193
194
0.20
0.30
0.10
0.25
0.24
195
0.14
0.30
0.16
0.22
0.23
196
0.14
0.30
0.16
0.22
0.23
197
0.17
0.30
0.14
0.24
0.24
198
0.24
0.30
0.06
0.27
0.26
199
0.22
0.30
0.09
0.26
0.26
200
0.17
0.30
0.14
0.24
0.25
Average difference between Olsen
and End Point 0.03


93
The density of dwelling units increases from 1.4 in 1972 to 3.5 in 1999 for the 138 9-ha
sample areas in St. Johns County (Table 5-5). Increasing by 2.1 units per hectare. Decreases in
the number of dwelling units were caused by demolitions and renovations in Ponte Vedra
(monuments 15 to 27), and the removal of mobile home parks at St. Augustine Beach. When
divided by geomorphic unit the descriptive statistics do not reflect spatial differences in
residential density. St. Johns County from Ponte Vedra to Vilano Beach has a density increases
from 1.4 in 1972 to 3.5 in 1999 for the 83 9-ha sample areas. Anastasia Island from St Augustine
Beach to Matanzas Inlet has average density increases from 1.7 units per hectare in 1972 to 3.7 in
1999 in the 44 9-ha sample areas.
Future Land Use Variables (FLU, FLUD)
The number of units existing in each of the time periods is shown with the FLUt3 in Figures
5-3 and 5-4. Apart from the CBRA area, the trend is that number of units increases from 1972 to
1999 and that the future land use plan (FLU,3) permits higher units than the 1999 record. The
CBRA area was intentionally proposed with lower future land use densities than exist to reflect
that the designation does not permit use Federal funding for future development (Mel Scott,
Brevard County Growth Management, personal communication, 2003). Brevard County prepared
the first comprehensive plan required under the 1986 Growth Management Act in 1988.
However, future land use data were not available digitally for the 1986 timeframe and were not
recreated when GIS use became prevalent. Property Appraisal Atlases in paper format were use
in Brevard County until the 2000 update of the Comprehensive Plan. Therefore, there are no
FLU,2 data. The average residential density increases from 21.2 du/ha for FLUDtl to 22.3 for
FLUDt3. The maximum number of units permitted in the t3 Comprehensive Plan in one 9-ha
sample area in Brevard is over 560 units. The future land use residential densities in Brevard
County have not increased substantially since 1972, indicating that average densities of over
du/ha at the time were ambitious. The average residential density increases from 1.3 du/ha in
1972 to 6.3 in 1999 in St. Johns County. The maximum total units permitted in one 9-ha sample


APPENDIX B: DEPENDENT AND INDEPENDENT VARIABLE DETAILS
Table B-l. Dependent and independent variable details
Variable Description
Name
Units
Data Sources
Monument
MON
Nominal
(discrete)
Numbering System
1972 Beach Width
BW
m
DEP converted data,
1986 Beach Width
BW
m
http://www.dep.state.fl.us/beache
1999(1997) Beach Width
BW,3
m
1972 to 1986 Beach Width
BWtf.i
m
1986 to (1997)1999 Beach Width
BWg-2
m
. ,
1972 to (1997)1999 Beach Width
BW0.,
m
Total Beach Width Change
BWlot
m
Beach Width Factor
BWf
Between -
1 and 1
1972 Dune Height
DH
m
DEP converted data,
1986 Dune Height
DH.2
m
http:// www. dep. state. fl. us/beache
1999 (1997)Dune Height
DH
m
1972 to 1986 Dune Height
DH.,
m
1986 to (1997)1999 Dune Height
DH.3.2
m
1972 to (1997)1999 Dune Height
DH-i
m
Total Dune Height Change
DHlo,
m
Dune Height Factor
DHf
-1 and 1
1972 Monument to Dune Height
MDHtl
m
DEP converted data,
1986 Monument to Dune Height
MDH12
m
http://www.dep.state.fl.us/beache
s/data/his-shore.htm#ProfileData
1999 (1997) Monument to Dune Height
MDHu
m
1972 to 1986 Monument to
Dune Height
MDHt,.,
m
1986 to (1997)1999 Monument to
Dune Height
MDH(3-2
m
Modified DEP data, derived
from Annual Dune Height data
1972 to (1997)1999 Monument to
Dune Height
MDHo.,
m
Total Monument to Dune Height
Change
MDHtoI
m
Monument to Dune Height Factor
MDHf
-1 and 1
1972 Dune Height to NGVD
DHBW
m
DEP converted data,
1986 Dune Height to NGVD
DHBWu
m
http://www.dep.state.fl.us/beache
s/data/his-shore.htm#ProfileData
1999 (1997)Dune Height to NGVD
DHBWo
m
1972 to 1986 Dune Height to NGVD
DHBWe.i
m
1986 to (1997)1999 Dune Height to
NGVD
DHBW.3.2
m
Modified DEP data, derived
Tom Annual Dune Height data
1972 to 1999 Dune Height to NGVD
DHBW,3.i
m
133


24
for higher adopted future land use densities, so the higher the maximum dune height, the higher
the proposed number of units permitted in the future planning horizon.
Hypothesis 2: The dynamic geomorphology impacts human variables
Hypothesis 2a: The dynamic geomorphology indicators influence the actual human
variables. A dune height that varied over decades indicating dynamic local coastal
geomorphology would be negatively correlated to human variables such as the number of
dwelling units and impervious area. The more height variation the more dynamic the
environment and the less suitable it is for development. Thus the area would have a lower the
number of units, and smaller impervious areas indicating that the physical environment had
impacted the development characteristics. Lundberg and Handegard (1996) noted the adaptation
of agricultural uses to the environment, and McMichael (1977) and Miller (1980) noted the
preference of higher ground inland of the barrier island for settlement.
Hypothesis 2b: The dynamic geomorphology indicators influence the land use control
decision-making. An example of this hypothesis is a beach width changed over time in any
direction that would indicate a dynamic coastal area. Such an area would not be suitable for the
establishment of high proposed future land use densities. The more beach width increased and
decreased over time the less suitable the area for development. Thus the area should have a lower
planned future land use density. Bush et al., (1999) detail zoning restrictions used for hazard
mitigation in North Carolina. This hypothesis proposes the reverse, with zoning outcomes as the
result of the characteristics of the physical environment.
Hypothesis 3: There are temporally lagged relationships between the actual and dynamic
geomorphology variables and the human variables. This hypothesis contemplates that
geomorphology in one time period will influence human variables in later time periods. For
example, the wider the beach width the more stable the coastal environment and therefore the
more suitable for greater impervious area percentage in the later time period. Nordstrom (1987)
noted that the impact of jetties on the coastal system was delayed and could not be evaluated on


70
The 1979 plan for St. Johns County contained detail from which a density (FLUD,i) was
determined. Recent adopted plans have land use assigned to each parcel of property. In St. Johns
County digital existing land use was produced digitally in 1996 and contained less than 8.1
hectares of land on the coast with a revised land use designations from the 1990 Comprehensive
plan (Tim Brown, St. Johns County Planner, personal communication, 2001). These data were
used to determine the FLUC, FLUD^ and FLUQ2. In St. Johns County there is one incorporated
coastal municipality, St. Augustine Beach. Digital data were obtained for the 2001
comprehensive plan. The individual areas of future land use categories are calculated using
GIS. A range of units is traditionally provided for planning residential land use categories. The
midpoint of residential land use densities is used for this research. Commercial uses included
offices, tourist related uses, hotels, port commercial and retail. Public facilities uses were not
included in the commercial designation. Areas designated for future open space, recreation or
conservation used were not included as developable and removed from the total hectares
available. Figure 4-13 shows 5.49 hectares of low/medium residential land use and 0.36 hectares
of high-density residential land use. The mid point of the low/medium residential density is 4
du/ha allowing 22 potential units. The mid point of the high residential density land use is 10
du/ha, which results in 4 potential units, for a sample area total of 26 units. When divided by the
total residential hectares, the resulting density is 26 units in 5.9 hectares, or 4.4 du/ha (Figure 4-
14)
Application of Variables in Hypotheses
Hypothesis 1: Local geomorphology impacts human variables at the same interval
Hypothesis la: The local geomorphology influences the actual development. This
hypothesis is illustrated by a relationship between actual geomorphology, and the human
variables at that time (Conway and Nordstrom, 2003; McMichael, 1977; Miller, 1980). Examples
of the hypothetical relationships between the 1972 geomorphology and the 1972 human variables
are shown below. The hypotheses would be the same for the two other discrete time periods.


50
The end point rate is the difference between the first record and the last record divided by
the entire time period. The end point rates are calculated similarly to net change variable for the
profile data. However, the data are taken from historical maps, shore normal profile data, and
digitized historical shorelines from the U. S. Coastal and Geodetic Survey, the National Ocean
Survey (NOS) and the U. S. Geologic Survey. The least squares method models the slope of the
best-fit line when shoreline width and time are plotted. The rate averaging method is the average
long-term rate of change using a combination of rates over the time periods. The magnitude of the
end point methodology determines which records are used. If the end point methodology shows a
small amount of change, it should take a longer time between observations to detect significant
shoreline changes. The FDEP also conducts rate comparison, sensitivity and digitizing variability
tests to determine the points to be included. The time period for each data point collected is
calculated. Data obtained from maps verses surveyed profiles will have different degrees of
accuracy and different minimum time span requirement. Rate combinations over a time period
shorter than the data type minimum are excluded as not reflecting long-term trends. In this way,
short time segments do not influence the calculated rates unduly. All three methods are compared
to demonstrate specific sensitivity to any of the methods.
Each methodology has potential for errors. Each of the records has a level of accuracy
determined by the source information. The end point data gives a net effect that is useful in areas
where there have been continuous changes, such as the impact of beach renourishment (Houston,
1995) that would influence the results of the other methodologies. Using this methodology data
irregularities are dampened. The least squares fit method is sensitive to clusters of records
(Figure 4-4). In the case of shoreline information the data are sparse in the earlier time periods
and more comprehensive in the recent past. The least squares method does not afford a weighting
system to increase the emphasis on more accurate data.


Maximum Dune Height (DH) and Distance to Maximum Height (DHBW) 48
Monument to Maximum Dune Height (MDH) 49
Long Term Shoreline Change (LT) 49
Coastal Structures (SW) and Renourishment Projects (RN, RND) 56
Geographic Location (POS) and Orientation (OR) 57
Distance (ACC), Direction (DACC) and Location (ROAD) of Access 58
Dynamic Geomorphology Variables 59
Compilation of Data 61
Development Variables 64
Dwelling Units (UN) and Dwelling Units per Hectare (UH) 65
Impervious Area (IMP) and Percentage Impervious Area (PIM) 66
Future Land Use (FLU, FLUD, FLUC) 68
Application of Variables in Hypotheses 70
Data Analyses 75
Methodology Implications 77
5. ANALYSES AND RESULTS 79
Independent Variable Characteristics 79
Beach Width (BW) 79
Maximum Dune Height (DH) 80
Monument to Maximum Dune Height (MDH) 87
Maximum Dune Height to NGVD (DHBW) 88
Long Term Change (LT) 89
Access (ACC, DACC) Variables 90
Dependent Variables Characteristics 91
Number of Dwelling Units (UN) 91
Dwelling Units per Hectare (UH) 92
Future Land Use Variables (FLU, FLUD) 93
Impervious Area (IMP) and Percent Impervious Area (PIM) 94
Commercial (C) and Commercial Future Land Use (FLUC) Variables 98
Hypotheses Testing, Bivariate Statistical Analysis 100
Beach Width Index (BW) 100
Maximum Dune Height (DH) 103
Monument to Maximum Dune Height (MDH) 104
Maximum Height to NGVD (DHBW) 106
Long Term Change (LT) 107
Summary of Non-parametric Results by Hypothesis 109
Multivariate Statistical Analyses 111
Hypothesis 1: Local Geomorphology and Human Variables at each Time Interval.... 112
Hypothesis 2: The Dynamic Geomorphology and Human Variables 115
Hypothesis 3: Temporal Lag of Geomorphic and Human Variables 117
Hypothesis 4: Dependent and Independent Variables in Separate Jurisdictions 118
Post Study Period Data 118
6. DISCUSSION AND CONCLUSIONS 120
Actual Geomorphology and Human Variables 121
Dynamic Geomorphology and Dependent Variables 122
Influence of Geomorphic Variables on Subsequent Development 124
Variation by Location 124
vi


Abstract of Dissertation Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Doctor of Philosophy
SPATIAL AND TEMPORAL GEOMORPHIC VARIABILITY AND COASTAL
LAND USE PLANNING, NORTHEAST FLORIDA
By
Heidi J. L. Lannon
May 2005
Chair: Joann Mossa
Major Department: Geography
The research quantified the influence of local geomorphology of coastal areas
on the suitability of existing development patterns and future land use plans. Brevard
and St. Johns County (located on the east coast of Florida) were studied from 1972 to
1999. The State of Florida requirement for comprehensive plans containing future land
use designations provided base data for development of a policy-evaluation model.
Impacts of the physical characteristics of the coastline on the number and
density of dwelling units, impervious area, and development potential were evaluated at
1 km intervals. Geomorphic variables (beach width, maximum dune height, crest
position, and shoreline change) interact with development patterns and future land use
designations, and are determined by location. The net and total change are measures of
the dynamic characteristics used to evaluate temporal variations.
Results supported the anticipated relationships among wider beach width, higher
levels of impervious area, density, commercial hectares, and future land use. However,
development levels are more intense in areas with lower maximum dune heights,
suggesting that low dunes are a preferential condition for development. The position of
xv


4
-6 i
Augustine
Beaeh

10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200
Monument Number
Long Term Change (Foster at al,. 2000)
Figure 4-2. Long-term shoreline change, St. Johns County, 1872 to 2000


CHAPTER 2
LITERATURE REVIEW
The influences of anthropogenic activities are integral to coastal geomorphology (Malone,
2003, Sherman and Bauer, 1993). However, coastal research has predominately focused on
human impacts on the coastal zone, rather than the influence of the physical environment. Human
impact has been reviewed at the macro scale (Brown and McLachlan, 2002; Clark, 1976; Clark,
1997; Phillips, 1988; Phillips, 1997; Viles and Goudie, 2003; Viles and Spencer, 1995) and micro
levels (Conway and Nordstrom, 2003; Gares, 1987; Nordstrom, 1994; Nordstrom et al., 2002;
Sherman and Bauer, 1993). Nordstrom (1994) recognizes human activity as an integral part of
the coastal system. He discusses the lack of literature specific to human altered coasts. Natural
landscapes are a myth, that human agency is not an intrusion in the coastal environment so much
as it is now part of the coastal environment. (Nordstrom, 1994, pp. 508) Others contend that the
natural system must be understood before human influences can be evaluated (Sherman and
Bauer, 1993). The interaction between physical and human geography has been also been
described as a form of landscape geography, bridging the systematic and regional geography
approaches (Lundberg and Handegard, 1996).
The natural or physical environment is influenced by, and also influences human factors.
This research evaluated the weight of the physical environment as a factor affecting human
variables. Lundberg and Handegard (1996) investigated coastal agricultural uses to evaluate how
humans have adapted to the use of the environment over time. Adjacent agricultural practices
may be dissimilar in identical environmental conditions, suggesting that a variety of feedback
loops influence the spatial patterns. Lundberg and Handegard (1996) state that the landscape is
a reflection of environmental, and social conditions and processes in society (pp. 168). In New
Zealand, geomorphology has been used to determine the potential uses of areas (Hails, 1977).
5



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163
Table H-3. Brevard County Spearman Rank analyses, Monument to Dune Height (MDH) ) and
dependent variables at 0.05 significance
MDH
MDH,2
MDH,3
MDH, 2.,
MDH,3.2 MDH0.1
MDH,,
MDHf
POS
UN
-
-
-
-
-
-
-
-0.2943
UNa
-
-
-
-
-
-
-
-0.2198
UN,3
-
-
-
-
-
-
-
-
UNa-i
-
-
-
-
-
-
-
-
UNt3-2
-
0.2365
-
-
-0.2469 -
-0.1885
-
0.3242
UN,3.1
-
0.1481
-
-
-
-
-
0.2254
UH
-
-
-
-
-
-
-
-0.2969
UH
-
-
-
-
-
-
-
-0.2003
UH,3
-
-
-
-
-
-
-
-
UHa-i
-
-
-
-
-
-
-
-
UH,3.2
-
0.2437
-
-
-0.2464 -
-0.1890
-
0.3201
UH,3-i
-
-
-
-
-
-
-
0.2240
IMP,,
-0.2990
-0.2748
-
-
-
0.2816
-
-0.6686
IMP,,
-0.3363
-0.3075
-0.1722
-
-
0.2385
-
-0.6632
IMP,3
-0.3605
-0.3002
-0.1990
-
-
0.1764
-
-0.6603
IMP,2.,
-
-
-
0.2187
0.1928
-
0.2315
-0.2210
IMP,3.2
-
-
-
0.2129
-
-
-
-
IMPa.,
-
-
-
0.2501
0.2142
-
-
-0.2552
PIM
-0.2701
-0.2522
-
-
-
0.3075
-
-0.6456
PIM,2
-0.2609
-0.2811
-
-
-
0.2959
-
-0.6499
PIM.3
-0.2792
-0.2684
-0.1035
-
-
0.2494
-
-0.6614
PIM,2.,
-
-
-
0.1691
-
-
0.1913
-0.2331
PIM.3.2
-
-
-
0.2067
-
-
-
-
PIMa-,
-
-
-
-
-
-
0.2055
0.2753
ACC
0.2420
-
-
-
-
-0.3238
-
0.6800
DACC
-0.3157
-0.3022
-0.2412
-
-
0.2894
-0.2130-0.6897
POS
0.5124
0.3509
0.2960
-
-
-0.3391
-
1.0000
C.1
-0.3228
-0.2868
-
-
-
0.2741
-
-0.6226
Ca
-0.3413
-0.3022
-
-
-
0.2355
-
-0.6197
Ca
-0.3534
-0.2978
-0.1875
0.0381
-
0.1820
-
-0.6211
Ct2-1
-
-
-
0.2239
0.1758
-
0.2069
-0.2922
03-2
-
-
-
-
-
-
-
-
Ct3-1
-
-
-
0.2462
0.2178
-
0.2385
-0.3481
FLUD
-0.2869
-0.2363
-
-
-
0.2523
-
-0.8103
FLU,3
-0.4047
-0.3649
-0.2408
-
-
0.2007
-
-0.6171
FLUDo
-0.3641
-0.3365
-
-
-
0.3037
-
-0.6541
FLUCa
-
-
-
-
0.2593
-
-


157
Table G-2.
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05
Normality
Hectares of Commercial
C 138 0.1
0.3
0.0
1.8
0.4799
0.075
Reject
ca
136
0.4
0.9
0.0
5.0
0.3545
0.076
Reject
Co
134
0.7
1.4
0.0
6.8
0.3355
0.076
Reject
Ctf-l
138
0.3
0.8
-0.4
5.0
0.3646
0.075
Reject
Ct3-2
138
0.3
1.0
-0.8
6.8
0.3686
0.075
Reject
Qm
138
0.6
1.3
-0.3
6.8
0.3353
0.075
Reject
Future Land Use
FLU 138
13.1
13.7
0.0
76.2
0.1615
0.075
Reject
FLUCo
138
0.4
0.9
0.0
4.1
0.3092
0.075
Reject
FLUo
138
36.8
26.1
0.0
133.0
0.1294
0.075
Reject
FLUC
138
0.2
0.7
0.0
5.6
0.5016
0.075
Reject
Table G-3.
Descriptive statistics, dependent and independent variables, Ponte Vedra to St.
Augustine Pass (Monument 1 to 122) St. Johns County
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05
Normality
Monument to Maximum Dune Height
MDH 66 5.7 6.9
0.0
30.5
0.1881
0.108
Reject
MDHa
67
8.2
6.9
0.0
27.7
0.1169
0.108
Reject
MDHb
66
8.1
7.00
0.0
27.7
0.1668
0.108
Reject
MDHa.i
69
2.5
8.5
-22.0
27.7
0.1955
0.106
Reject
MDHa-2
69
-0.2
6.3
-20.8
20.4
0.2149
0.106
Reject
MDH,3-i
70
2.3
9.2
-22.0
26.8
0.1759
0.105
Reject
MDH,ot
70
9.3
9.3
0.3
36.6
0.2129
0.105
Reject
MDHf
70
0.01
0.8
-1.0
1.0
0.1885
0.105
Reject
Maximum
DHBW
Dune
111
Height to NGVD
68.4 8.3
41.7
85.7
0.0913
0.084
Reject
dhbw,2
110
77.7
11.7
45.4
111.7
0.0587
0.084
Accept
DHBW
110
63.8
12.8
35.7
118.9
0.0697
0.084
Accept
DHBW-i
110
9.3
12.1
-17.1
43.8
0.0668
0.084
Accept
DHBW0.2
110
-13.8
14.3
-64.2
45.4
0.1189
0.084
Reject
dhbw,3.,
110
-4.5
11.7
-45.6
35.1
0.1052
0.084
Reject
DHBW101
110
28.9
18.0
1.3
104.5
0.1291
0.084
Reject
DHBWf
110
-0.2
0.5
-1.00
1.0
0.1179
0.084
Reject


153
Table F-l. Continued
Monument
End
Point
(m)
Rate Averaging
(Olsen 1989)
(m>
Difference
(m)
Average of
Olsen and End
Point
(m)
(LT) Adjacent
Average
(m)
133
0.14
0.15
0.01
0.15
0.16
124
0.14
0.14
125
126
0.26
0.30
0.04
0.28
0.28
127
128
0.13
0.30
0.17
0.22
0.22
129
130
0.11
0.15
0.05
0.13
0.14
131
0.13
0.15
0.02
0.14
0.12
132
0.05
0.15
0.11
0.10
0.11
133
0.05
0.15
0.10
0.10
0.11
134
0.08
0.15
0.07
0.12
0.11
135
0.06
0.15
0.09
0.11
0.11
136
137
138
0.12
0.15
0.03
0.14
0.13
139
0.09
0.15
0.06
0.12
0.12
140
0.08
0.15
0.07
0.12
0.12
141
0.08
0.15
0.08
0.11
0.11
142
0.04
0.15
0.11
0.10
0.09
143
-0.01
0.15
0.16
0.07
0.08
144
145
146
147
0.12
0.30
0.19
0.21
0.21
148
149
150
151
152
153
154
-0.05
0.00
0.05
-0.02
-0.03
155
-0.07
0.00
0.07
-0.03
-0.04
156
-0.11
0.00
0.11
-0.05
-0.05
157
-0.14
0.00
0.14
-0.07
-0.07
158
-0.14
0.00
0.14
-0.07
-0.08
159
-0.20
0.00
0.20
-0.10
-0.08
160
-0.15
0.00
0.15
-0.07
-0.07
161
-0.12
-0.13
162
-0.12
-0.07
163
0.02
-0.03
164
0.01
0.03
165
0.06
0.04
166


Distance from Monument 1 (km)
X 1972 Maximum Height 1986 Maximum Height 1997 Maximum Height
Figure 5-3. Brevard County maximum dune height variations, 1972-1997 (DHtl, Dlll2, DHt3)


190
APPENDIX J. Continued
Dependent Variable FLUDti
Adjusted R-Squared 0.4980
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
9.21105
2.556698
3.6027
0.000458
Reject Ho
0.946737
BWtl
2.233969E-02
3.589396E-03
6.2238
0.000000
Reject Ho
0.999987
OR
-5.830832E-02
1.532162E-02
-3.8056
0.000223
Reject Ho
0.965260
DACC
8.473538E-02
9.816629E-03
8.6318
0.000000
Reject Ho
1.000000
T-Critical
1.979764
F-Ratio
42.0016
0.000000
1.000000
N=124
FLUD,i = Potential Residential Density, 1979 Comprehensive Plan (units per hectare)
BW ,i = 1972 Distance from NGVD to Maximum Dune Height (m)
OR = Shoreline Orientation (degrees from north),
DACC = Distance and Direction from Access Point
Table J-12. St. Future land use density (FLUD,i) Johns County north, Monument 1 to Monument
120, 1972
Dep.
Variable
Rz
Intercept
P,
Variable
P2
Variable
FLUD
(n=82)
0.545
-2.272
0.049
BW tl
-1.038
BWf
Dependent Variable FLUDti
Adjusted R-Squared 0.5451
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
-2.272346
0.7942346
-2.8611
0.005385
Reject Ho
0.806916
BW tl
4.940527E-02
1.129674E-02
4.3734
0.000037
Reject Ho
0.990872
BWf
-1.038004
0.1526959
-6.7979
0.000000
Reject Ho
0.999999
T-Critical
1.990063
F-Ratio
50.1306
0.000000
1.000000
N=82
FLUD,i = Potential Residential Density, 1979 Comprehensive Plan (units per hectare)
BW ,i = 1972 Distance from NGVD to Maximum Dune Height (m)
BWf = Total Beach Width divided by Net Beach Width


105
Table 5-15. Distance from the monument to maximum height and development variables in
Brevard County
Impervious Area
Variables
Monument to maximum dune height (MDH)
1972 (MDH) 1986 (MDHa) 1997 (MDHa)
1972 (IMP,,)
-0.2990
NA
-
1986 (IMPa)
-0.3363
-0.3075
NA
1997 (IMPa)
-0.3605
-0.3002
-0.1990
1972 (PIM)
-0.2701
NA
-
1986 (PIM0)
-0.2609
-0.2811
-
1997 (PIMo)
-0.2792
-0.2684
-0.1035
1972 (Q,)
-0.3228
NA
-
1986 (Cq)
-0.3413
-0.3022
-
1997(Ca)
-0.3534
-0.2978
-0.1875
95% confidence interval, denotes no significance, NA=temporal antecedence,
Table 5-16. Distance from the monument to maximum dune height and future land use in Brevard
County
Future Land Use Monument to Maximum Dune Height (MDH)
1972 1986 1997 TOTAL
(MDHti) (MDH a) (MDH ) (MDHtot)
1972 (FLUD) -0.289 NA 0.252
1997 (FLUtf) -0.405 -0.365 -0.241 0.201
1997 (FLUD) -0.364 -0.337 0,259
95% confidence interval, denotes no significance, NA=temporal antecedence,
The measure of change in MDH over time is a more appropriate indicator of the condition
of the dune field, because each measure of change is independent of the original monument
locations. Areas where the highest point has not migrated or a low total change (MDHlot) would
be appropriate for higher levels of development area under Hypothesis 2a. However, in Brevard
County there is a consistent positive relationship (0.18 to 0.31) between the impervious and
commercial development variables and MDH ,ot (Table 5-17).
Table 5-17. Distance from the monument to maximum dune height and development variables in
Brevard County
Monument to Monument to Maximum Dune Height (MDH)
Maximum Dune
Height (MDHtot) IMP PIM C
1972 () 0.2816 0.3075 0.2741
1986(a) 0.2385 0.2959 0.2355
1997 (q) 0.1764 0.2494 0,1820
95% confidence interval


74
Table 4-13. Hypothesis 2b, dynamic geomorphic and future land use relationships.
Dynamic
Geomorphology
(Over Entire Period)
Hypothetical
Relationship
Land Use Control Variable
Change in Beach Width Index
Negative
Future Land Use Density
(BWtf.b BWoj.BWe-i, BW,ot);
(FLUtf, FLU,,), (FLUD-
Change in Dune Height (DHg.i,
DH^DHa-, DH,ot);
Change in Distance Monument to
Maximum Dune Height (MDH^.
,, MDHtf.j.MDHj.i MDHtot);
Change in Distance NGVD to
Maximum Dune Height
(DHBW.2.,, DHBWtf.2 DHBW3.
.. DHBW,ot);
FLUD)
Factor Variable
Future Land Use Density
Beach Width Index Factor, (BWf);
Dune Height Factor, (DHf);
Distance Monument to Maximum
Dune Height Factor (MDHf);
Distance NGVD to Maximum Dune
Height Factor (DHBWf)
Positive
(FLUD- FLUD)
Hypothesis 3: There are temporally lagged relationships between the actual and dynamic
geomorphology variables and the human variables. This hypothesis contemplates that
geomorphology in one time period will influence human variables in later time periods
(Nordstrom, 1987; Van Der Wal, 2004). The example below shows a positive relationship
between the dune height in 1972 and the human variables in later time periods. The second
example shows the wider the beach width in 1986 the more stable the coastal environment and
therefore the more suitable for greater a impervious area and dwelling units in the later time
period.
Hypothesis 4: The dependent variables will have different relationships with the independent
variables in the two separate study areas. The explanatory power of the individual variables will
be different in each part of the coastline (Byrnes et al., 1995). For example, the dune height in
Brevard County will not have the same relationships with the human variables are the dune height
in St. Johns County. The regression coefficients and significant variables for each county will be
different.


Table A-1. Continued
131
Date
Name
Area/Landfall/
Characteristics
Type
Source
1979
(Sept.)
David,
Category 2
Landfall at Melbourne, traveled north
up the Indian River Lagoon and
exited at New Smyrna, 145 km/hr
winds, 73.0 cm rainfall
H
Jacobs (1993),
Reesman
(1994)
Williams &
Duedall
(1997)
1981
(Aug.)
Dennis,
Tropical
Storm
Exited after passing over peninsular
at Melbourne Beach
E
Williams &
Duedall
(1997)
1983
(Aug.)
Barry,
Tropical
Storm
Landfall at Melbourne Beach. Hit
Texas as a hurricane after passing
over peninsular
TS
Williams &
Duedall
(1997)
1988
(Nov.)
Keith,
Tropical
Storm
Landfall at Ft. Myers. Exited
between Melbourne and Cape
Canaveral after passing over
peninsular
E
Williams &
Duedall
(1997)
1994
(Nov.)
Gordon,
Tropical
Storm
Exited after passing over peninsular
at Melbourne Beach, 73 km/hr
winds, tornadoes
E
Williams &
Duedall
(1997)
1994
(Nov.)
Gordon,
Tropical
Storm
Looped in Atlantic and made landfall
at Cape Canaveral, 40 to 48 km/hr
winds
TS
Williams &
Duedall
(1997),
1995
(July)
Erin,
Category 1
Florida East Coast, 137 km/hr winds,
73.9 cm rainfall
H
Williams &
Duedall
(1997), FDEP
(2000)
1996
(Aug)
Fran
Remained offshore and made landfall
in North Carolina
O
FDEP (2004)
1999
(Sept)
Floyd
Remained offshore and made landfall
in North Carolina
O
FDEP (2000)
1999
(Oct)
Irene
Offshore and made landfall in NE
O
FDEP (2000)
2004
(Sept)
Frances,
Category 2
Landfall at Sewalls Point, FL.
Stalled over southern Brevard.
Max. 198 km/hr winds
H
FDEP
(2004a),
FDEP (2004b)
2004
(Sept)
Jeanne,
Category 3
Landfall at Hutchinsons Island, FL
after loop in Atlantic. Tropical storm
conditions in St. Johns
H
FDEP
(2004a),
FDEP (2004b)
Characteristics noted reflect peak winds, minimum pressure and maximum surge recorded in the
east central Florida region. Data after 1945 is considered reliable. H = Hurricane, TS = Tropical
Storm, E = Exiting at coast, O = Offshore.


118
Hypothesis 4: Dependent and Independent Variables in Separate Jurisdictions.
This hypothesis supposes that the explanatory power of the individual variables will be different
in each part of the coastline (Byrnes et al., 1995). The Brevard County 1972 future land use
density (FLUD,i) is a function of the 1972 dune height, long term change and shoreline
orientation as discussed in Hypothesis lb. The combination of these variables explains over 60
percent of the variation in the 1972 future land use density. Higher designated density is a
function of lower dunes, low long-term change and a shoreline orientation towards northwest to
southeast. In contrast on Anastasia Island in St Johns County high 1972 densities (FLUDu) are a
function of a high 1972 beach width, an opposite orientation to Brevard County (more northwest
to southeast) and the proximity to access to the mainland to the south.
When the total proposed units in the future land use plan (FLUt3) are considered, Brevard
County total units are a function of the 1997 dune height and the 1972 distance from the
monument to the maximum dune height, as discussed in Hypothesis 1 b. The combination of
these variables explains 48 percent of the variation in the total units proposed. Higher designated
future land use units are a function of lower dunes, and a low distance to the maximum dune
height. In contrast St Johns County over 60 percent of the variation in total units (FLUo) is a
function of the 1986 beach width, the change in dune height from 1972 to 1999 and orientation.
Higher total units occur where the beach width was wider in the earlier time period, the change in
dune height is lower and the orientation is northwest to southeast.
Post Study Period Data
The study period of this research does not incorporate the 2004 hurricane season, which
impacted both St. Johns and Brevard County (Appendix A). In St. Johns County, the FDEP
recommends post-hurricane feasibility studies for beach restoration at Vilano Beach (monuments
110 to 117 and Summer Haven (monuments 197 to 209), and acceleration of maintenance
renourishment at St Augustine Beach (monument 137 to 150) (DEP 2004b). Snell (2004) notes


32
1.1 to 1.2 m. The prevailing wave and wind approach is from the northeast (Foster et al., 2000),
although during the summer the wave direction is from the southeast with smaller waves.


135
Table B-l. Continued
Variable Description
Name
Scale
Data Sources
1986 to 1999(1997)
Impervious Area
IMP,3.2
Ha
Derived from Impervious Area Data
1972 to 1999 Impervious Area
IMP.3-,
ha
1972 Percentage Impervious
PIM
/o
1986 Percentage Impervious
PIM,2
%
Derived from Impervious Area data and GIS
1999 Percentage Impervious
PIM.j
%
deteimined aiea available
1972 to 1986 Percentage
Impervious
PIM.2.,
%
1986 to 1999 Percentage
Impervious
PIMu-2
%
1972 to 1999 % Impervious
pim.3.,
%
Location of Parallel Access
ROAD
Ordinal(
1 to 4)
1972 and 1986 Blue lines and 1997 (1999)
DOQQ
Distance to Access
ACC
km
Use of monument position data and GIS
position of access
Direction to Access
DACC
km
Use of monument position data and GIS
position of access, Positive south, negative
north
1972 Hectares Commercial
c,,
ha
DEP Aerial Blue Line 1972, 1:1200 scale
1986 Hectares Commercial
Ca
ha
DEP Aerial Blue Line 1986, 1:1200 scale
1999 Hectares Commercial
Co
ha
Brevard County DOQQ, 1997, St. Johns
County DOQQ, 1999, use of Mr. Sid and X
tools
1972 to 1986 Hectares
Commercial
Ca-i
ha
Derived from Hectares of Commercial and
GIS determined area available
1986 to 1999 Hectares
Commercial
Co-2
ha
1972 to 1999 Hectares
Commercial
Ct3-1
tia
Future Land Use Units per
Hectare
FLUD
du/ha
Brevard County BOCC, 1981 (Brevard), St.
Johns County, 1979 (St. Johns)
Future Land Use Units (St.
Johns only)
FLUo
du/ha
St. Johns County GIS, Tim Brown (Personal
Communication 2001)
Future Land Use Units per
Hectare (St. Johns only)
fujd,2
du/ha
Future Land Use Commercial
Hectares (St. Johns only)
FLUCe
la
Number of Potential Units
(beyond 2010 Brevard
County, 2015 St. Johns
County,)
FLU,3
Units
County and City Land Use GIS data (St. Johns
County, 2002). 2000 Brevard County Plan,
2001 St. Johns County Plan.
Future Land Use Residential
Density
FLUD
du/ha
County and City Land Use GIS data
Hectares of Commercial
FLUCt,
ectares
County and City Land Use GIS data
Geographic Position
POS
cm
Use monument Northing and Easting for
distance from monument


99
commercial development county wide. In northern St. Johns County commercial hectares
increases were greater from 1972 to 1986. On Anastasia Island the commercial development has
been consistent, and the average commercial hectares for the sample areas for monuments 141 to
195 is higher than in northern St. Johns County. By 1999 the 44 sample areas on Anastasia Island
had an average of 1.7 ha of commercial development.
Brevard County has more coastal commercial development than St. Johns County although
there are areas of St. Johns County, such as St. Augustine Beach (monuments 141 to 150), where
commercial development levels approach those of coastal Brevard County. Large hotel
complexes and grocery stores with extensive impervious parking areas have existed in the Cocoa
Beach area of Brevard County since the 1970s due to the influence of NASA, the Cape
Canaveral complex and associated industries, and Patrick Air Force Base. The proposed 2010
commercial future land use in Brevard County is higher at 0.7 ha than the 0.2 ha average in St.
Johns County. Not only is Brevard County more intensely developed currently, but also that the
future land use intentions are for increased intensity of commercial development.
The commercial future land use designations adopted in 1989 and for 2015 show that the
average area anticipated for commercial development in St. Johns County decreased from 0.4 to
0.2 ha. In northern St. Johns County (monuments 1 to 121) the commercial future land use plans
show a decrease in the average and maximum hectares for commercial development. This is an
indicator that the 1989 future land use designation may have been overly ambitious, and that the
distance to access and lack of infrastructure and services in the form of potable water, central
sewer and public safety functions that limit potential development, were recognized subsequently.
In northern St. Johns County the Ponte Vedra area has developed and expanded since 1972. The
influence of the Jacksonville metro area has continued to drive consistent increases in impervious
area, densities and projected future land use. On Anastasia Island much of the intense
condominium expansion and development occurred since 1986 and the first large grocery store
was constructed in St. Augustine Beach in 2001. The maximum value for all the 9-ha sample


197
LEATHERMAN, S. P., 1982. Barrier Island Handbook. University of Maryland, College Park,
MD, 108 pp.
LENCEK, L., and BOSKER, G., 1998. The Beach: The History of Paradise on Earth, Penguin
Group, New York, NY, 310 pp.
LINS, H. F., 1980. Patterns and trends of land use and land cover in Atlantic and Gulf coast
barrier islands. US Geological Survey Professional Paper 1156, Reston, V A, 164 pp.
LONG, H. D., 1968. Urban data abstract, Brevard 1968. Institute for Social Research, Urban
Research Center, Florida State University, Tallahassee, 217 pp.
* LUCAS, A. E., 1996. Data for coastal GIS: issues and implications for management. GeoJournal,
vol.39, no. 2, pp. 133-142.
LUNDBERG, A., and HANDEGARD, T., 1996. Changes in the spatial structure and function of
coastal cultural landscapes. GeoJournal, vol. 39, no.2, pp. 167-178.
MALONE, T. C., 2003. The coastal component of the U.S. integrated ocean observing system.
Environmental Monitoring and Assessment, vol. 81, vo.1-3 pp. 51-62.
MCBRIDE, R. A., 1987. Tidal inlet history, morphology and stability, eastern coast of Florida,
USA. Coastal Sediments 87, New Orleans ASCE, pp. 1592-1607.
MCMICHAEL, A. E., 1977. A model for barrier island settlement pattern. Florida
Anthropologist, vol. 30, no. 4, pp. 47-60.
MEESENBURG, H., 1996. Man's role in changing the coastal landscapes in Denmark.
GeoJournal vol. 39, no.2, pp. 143-151.
MEI, C., He, S., and FANG, K., 2004. A note on the mixed geographically weighted regression
model. Journal of Regional Science, vol. 44, no. 1, pp. 143-157.
MEYER-ARENDT, K. J., 1990. Modeling environmental impacts of tourism development along
the Gulf Coast. The Compass, vol. 67, no. 8, pp. 272-283.
MILLER, J. J., 1980. Coquina middens in the Florida East Coast. Florida Anthropologist, vol. 33,
pp. 2-14.
MORGAN, J. P., and STONE, G. W., 1985. A technique for quantifying the coastal
geomorphology of Florida's barrier islands and sandy beaches. Shore and Beach, vol. 1, pp.
19-26.
MOSSA, J., 1993. Field guide: coastal landforms and processes of northeast Florida. University
of Florida, Department of Geography, 46 pp.
MOSSA, J., and MCLEAN, M., 1997. Channel planform and land cover changes on a mined
river floodplain: Amite River, Louisiana, USA. Applied Geography, vol. 17, no. 1, pp. 43-
54.
NEUMAN, M., 1999. A new approach to planning and governing: the Jersey shore experience.
Ocean and Coastal Management, vol. 42, pp. 815-834.


143
Table E-l. Continued
Monument Date
Number Set
Northing Northing NS Change Easting
(position 2) (in m)
1
Easting
(position 2)
EW
change
(in m)
2
173
Aug-72
1321996.00
658131.50
174
Aug-72
1321094.00
658425.90
175
Jan-80
Monument replaced > 3m
from original
176
Aug-97
Monument replaced > 3m
from original
177
Aug-72
1318478.00
659781.00
178
Aug-97
Monument replaced > 3m
from original
179
Aug-72
1316957.00
660544.50
180
Aug-72
1315966.00
661052.50
181
Aug-97
Monument replaced > 3m
from original
182
Aug-72
1314224.00
661977.50
183
Aug-72
1313400.00
662408.00
184
Aug-72
1312458.00
662906.50
185
Aug-72
1311555.00
663309.00
186
Jul-83
1310668.00 1310668.00 0.00
663836.50
663836.50
0.00
187
Aug-97
1310039.00 1310048.00 -2.74
664161.00
664320.10
-48.49
188
Aug-72
1309184.00
664529.50
189
Jul-83
1308323.00 1308323.00 0.00
665064.50
665064.50
0.00
190
Aug-97
Monument replaced > 3m
from original
191
Aug-72
1306571.00
665926.50
192
Aug-97
1305691.00 1305690.00 0.30
666400.90
666399.50
0.43
193
Jan-86
Monument replaced > 3m
from original
194
Aug-72
1303899.00
667338.00
195
Aug-72
1303012.00
667799.50
196
Aug-72
1302124.00
668245.80
197
Aug-72
1301171.00
668647.00
198
Aug-72
1300284.00
669115.50
199
Aug-72
1299474.00
669532.00
200
Aug-72
1298501.00
670026.00
201
No Data
Monument replaced > 3m
from original
202
No Data
126886.00 126992.00 -32.31
670848.50
671139.40
-88.67
203-218
No Data
Monument replaced > 3m
from original
219
Aug-72
1282426.00
687108.40
Notes
1 Negative sign represents movement to south of original position
2 Negative sign represents movement to west of original position


3
Anthropologists have investigated prehistoric barrier island settlement in Georgia, South
Carolina and Florida (McMichael, 1977; Miller, 1980). Settlement patterns show a preference for
elevated sites on the relict Pleistocene sand ridges, particularly in areas where intertidal creeks
provided access to the back barrier lagoons and marshes in the interior (McMichael, 1977). In St.
Johns county occupation of coastal areas may have been seasonal and short-term (Miller, 1980),
and determined by the productivity of the lagoon and adjacent environments. There is no
evidence of ancient settlement, on the seaward side of barrier islands (Miller, 1980).
Figure 2-1. Study areas: Brevard and St. Johns counties, Florida
After World War II, the automobile made the shoreline increasingly accessible. Until
1950, coastal development had existed in the form of exclusive resorts and coastal areas adjacent
to large metropolitan areas that were accessible by locomotive. Traveling to the coast by camper


10
with components of length, width, height/depth and time. GIS has expanded the potential for
evaluating landscape conditions through the interrelationship of scale, pattern and process
(Walsh et al., 1998, pp. 183). However, GIS techniques should not be used in isolation without
the integration of fieldwork (Walsh et al., 1998). GIS has traditionally been used to illustrate
spatial relationships. This research used temporal and spatial data to analyze relationships among
the planned and built environment and the geomorphic characteristics of the coast.
An important aspect of GIS in geomorphology is the ability to show topography. The
coastal domain of Florida, however, has no extreme (elevations ranging from 0 to 10 meters). El-
Raey and Nasr (1996) also note the difficulty of vertical or z scale in low-lying coastal areas
and the difficulty of interpolating topography information for use on coastal scales with low z
values. GIS was used to evaluate the relationship of the human variables, land-cover, and
topography. El-Raey and Nasr (1996) used an average elevation for each land-cover category in
an attempt to quantify losses due to sea-level rise. In this research dune height represents the
topographic measure. GIS have practical applications in addition to its importance in coastal
research. In New Jersey investment in GIS were crucial to the coordination of coastal zone
management (Neuman, 1999). The State Planning Commission was funded to use GIS in a
multi-agency level dialogue, with input from state and local agencies, citizens and private
interests.
A crucial aspect of using GIS in spatial and temporal research is its ability to use a wide
variety of data types, such as maps, aerial, or remotely sensed images, survey data, and land use
coverages. This research has some limitations for GIS applications. The research data comprise
points and lines in vector form. Each data transect is separate in space. Interpolation of the
characteristics of the shore-normal profile from one area to the next is possible, using one of the
many methods of interpolation. The combination of types of planform and profile data allow the
user to produce a three-dimensional representation of the shoreline. Coastal research could


75
Table 4-14. Hypothesis 3, lagged geomorphic and human variable relationships.
Actual Geomorphology
(For 3 Time Periods)
Hypothetical
Relationship
Lagged Land Use Control Variable
1972 Dune Height (DH,i)
Relationship with
variable in later time
period
2015 Future Land Use Density
(FLU, FLUDt3), 1986 and 1999
Impervious Area, (IMP,2, IMPt3),
1986 and 1999 Percent Impervious
Area (PIM, PIMt3,) 1986 and
1999 Number of Dwelling Units
(UNC, UNo), 1986 and 1999
Dwelling Units per Hectare (UH,
UH), 1986 and 1999 Commercial
1986 Beach Width Index
(BW)
Relationship with
variable in later time
period
Hectares (Co, Ct3)
1999 Impervious Area, (IMPt3),
1999 Percent Impervious Area
(PIM,3) 1999 Number of Dwelling
Units (UN,3), 1999 Dwelling Units
per Hectare (UH,3), 1999
Commercial Hectares (Cp)
Table 4-15. Hypothesis 4, variable interactions by jurisdiction
Actual Geomorphology
(For 3 Time Periods)
Hypothetical
Relationship
Land Use Control Variable of that
County
Brevard County Dune Height
Varies-different from
Brevard County Future Land Use
(DUm-DH.,)
St. Johns County
Density (FLUo. FLU*), (FLUD-
FLUD,3) Brevard County Impervious
Area, (IMP,1-IMP,3), Brevard County
Percent Impervious Area (PIM,i-PIM^)
Brevard County Number of Dwelling
Units (UN,i- UN), Brevard County
Dwelling Units per Hectare (UH,i-
UHo), Brevard County Commercial
Hectares (Q1.Q3)
St. Johns County Dune
Varies-different from
St. Johns County Future Land Use
Height (DH,2_i-DH,3_i)
Brevard County
Density (FLU* FLU*), (FLUD-
FLUD,3) St. Johns County Impervious
Area, (IMP,i-IMP,3), St. Johns County
Percent Impervious Area (PIM,i-PIM)
St. Johns County Number of Dwelling
Units (UN,r UN^), St. Johns County
Dwelling Units per Hectare (UH,r
UHtf), St. Johns County Commercial
Hectares (C,i.C,3)
Data Analyses
The 34 dependent and 43 independent variables were assembled in a database for analyses.
Statistical analyses were performed using the NCSS statistical package. Descriptive statistics for


11
produce cell coverages suitable for raster manipulation. However, the spacing of these data
(more than 300m apart) is not conducive to interpolation.
Information sources for investigating coastal changes in planform include navigational
maps, USGS 1:24,000 topographic maps, NOS t sheets, aerial photography, and remotely
sensed images. Spatially using aerial photography is one way to evaluate the coast (Table 2-2).
However, caution is needed when interpreting data. Theiler and Danforth (1994) give a
comprehensive methodology for preparing a control network, resolving distortions and
inaccuracies, before inputting the information into a mapping program. Other considerations in
evaluating of data accuracy are map shrinkage, defects, projection, and age (Crowell et al., 1999).
The age of the photography, tilt, relief displacement, radial lens distortion, position of the tidal
datum, fiduciary points (known points on overlapping photographs), photograph overlap and
control points available for triangulation, film buckling, humidity, and type of paper, must all be
considered in assessing the accuracy of the aerial photography (Theiler and Danforth, 1994).
GIS has increasingly been used in conjunction with aerial photography in coastal areas.
The scales of coverages and extent of coastline investigated vary from individual dune systems to
broad analyses of entire coastal reaches. Bush and others (1999) consider aerial photography
suitable for coastal evaluation at the regional, local and site-specific scale. El-Raey and Nasr
(1996) used 1:25,000 scale photography for regional evaluations and 1:2000 photographs on a
local scale to investigate the impacts of sea-level rise on land use, population and land value
along the north coast of Egypt. Stanczuk (1975) used aerial photography with profile data to
evaluate the impacts of development of coastal characteristics.
Aerial photography has been used in coastal areas to show changes over time (Carter and
Woodroffe, 1994; Hails, 1977). Nordstrom evaluated the effects of engineering structures on four
inlets in New Jersey, and determined the planform changes over time. He found that a formerly
unidirectional drift system had been altered, and that shoreline mobility had been reduced after
1935. Two areas of rapidly expanding urbanization along the Australian coast were evaluated to


92
contained no units and others (monuments 94, 150 and 160) experienced a decrease in the number
of units caused by demolitions and renovations in Ponte Vedra (monuments 15 to 27), and the
removal of mobile home parks (monument 150). Areas of former mobile home parks, when
replaced with single-family homes result in lower densities, and when replaced with multifamily
(greater than 8 units per building) or commercial, higher impervious areas.
Descriptive statistical for the two geomorphic units in St. Johns County, north and south of
the St. Augustine Inlet (Appendix G) show that in the north part of St. Johns County from Ponte
Vedra to Vilano Beach the average number of dwelling units increases from 5.6 in 1972 to 15.5
in 1999 for the 83 9-ha sample areas. The a mean increase of 9.9 units which was lower than the
county wide increase of 10.6 dwellings. In the south part of St. Johns County, known as Anastasia
Island, from St Augustine Beach to Matanzas Inlet, dwelling units increases from 11.5 in 1972 to
24.9 in 1999 for the 44 9-ha sample areas. The standard increased from 12.5 to 25.9, indicating
that by 1999 there was a greater range in the number of dwelling units by sample area. Anastasia
Island has a higher average dwelling unit count per 9-ha sample area than the county wide average
for each time period.
Dwelling Units per Hectare (UH)
The dwelling units per hectare variable is a measure of residential density. It is the ratio of
the number of units in each 9-ha sample area to the hectares available for development. The
hectares unavailable for development include water bodies, conservation areas and parks.
Brevard County residential density increases from 3.2 du/ha in 1972 to 5.0 du/ha in 1997 for the
138 9-ha sample areas (Table 5-5). In Brevard County decreased density occurred where the
single-family units were converted to buildings with greater than 8 units, and land that was
removed from availability for development. The Brevard County Park System was funded by a
sales tax 1986, and had a goal of coastal property acquisition reducing the total available hectares
in the density calculation. Increases in residential density are consistent with the total number of
units (UN) unless the available area decreased.


117
On Anastasia Island, total units in the proposed future land use plan, for 2015 are a
function of beach width and dune height as was the case in Brevard County. In this case the dune
height variable dynamic; the change from 1972 to 1999. A positive value for orientation is also a
determining factor in the total units. Higher total units planned for 2015 would be anticipated to
occur where the beach width in the earlier time period was higher. The negative coefficient for
change in dune height indicates that higher numbers of units are planned where the dune height
change over time was low. Potential higher numbers of units are, therefore, planned in more
suitable areas with wider beaches and low levels of dune change
St. Johns County South, Monument 141 to Monument 198-1999 Future Land Use
Units (FLU a)
FLU,3= -195.593 + 0.478 BWa-5.080 DH^ 1.041 OR
(N=50, R2=0.6114)
FLU t3 = 1999 Potential Future Land Use, Comprehensive Plan (units)
BWa = 1986 Beach Width (m)
DH,3-i = Change in Maximum Dune Height 1972 to 1999 (m)
OR = Shoreline Orientation (degrees from north)
Hypothesis 3: Temporal Lag of Geomorphic and Human Variables.
This hypothesis contemplates that geomorphology in one time period will influence human
variables in later time periods (Nordstrom and Psuty, 1980; Van Der Wal, 2004). When St.
Johns County is divided by geomorphic unit, over 65 percent of the variation in the density
planned in 2000 for the 2015 future land use plan can be explained by a non-linear relationship
with the value of the beach width in 1986, on Anastasia Island. It would be anticipated that
historically wider beaches would be considered by planning officials as suitable for higher
densities.
St. Johns County South, Monument 141 to Monument 198-1999 Future Land
Use Density (FLUD^)
FLUDt3= 1.953 + 0.000001(BWe)3
(n=53, R2=0.659)
FLUD a = 1999 Future Land Use Density, Comprehensive Plan (units/hectare)
(BW ,2)3 = Cubed Value of 1986 Distance from NGVD to Maximum Dune Height (m)


201
U. S. ARMY CORPS OF ENGINEERS, 1972. Brevard County beach erosion control project.
Jacksonville Army Engineer District, Jacksonville, FL. Report EIS-FL-72-5590-F, 32 pp.
U. S. ARMY CORPS OF ENGINEERS, 1992. Brevard County, Florida shore protection study.
Jacksonville District, Jacksonville, FL. 53 pp.
U. S. ARMY CORPS OF ENGINEERS, 1993. Canaveral Harbor, Florida, sand bypass system.
Jacksonville District, Jacksonville, FL. 26 pp.
U. S. ARMY CORPS OF ENGINEERS, 1997. St Johns County, Florida shore protection study.
Jacksonville District, Jacksonville, FL., numbered in sections.
U. S. ARMY CORPS OF ENGINEERS, 1997a. Beach erosion control study on Brevard County,
Fla. Jacksonville District, Jacksonville, FL, Serial 99, 38 pp.
U. S. DEPARTMENT OF THE ARMY, Chief of Engineers, 1966. Beach erosion control study
of St. Johns County, Florida. U. S. Army Engineer District, Jacksonville, FL. 58 pp.
U. S. DEPARTMENT OF THE ARMY, Chief of Engineers, 1967. Beach erosion control study,
Brevard County, Florida. U. S. Army Engineer District, Jacksonville, FL. 42 pp.
U. S. DEPARTMENT OF INTERIOR, 1983. Final Environmental Impact Statement:
Undeveloped Coastal Barriers. Coastal Barriers Task Force.
VAN DER WAL, D., 2004. Beach-dune interactions in nourishment areas along the Dutch coast.
Journal of Coastal Research, vol. 20, nO. 1pp. 317-325.
VERNBERG, F. J., VERNBERG, W. B., and SIEWICKI, T., editors, 1996. Sustainable
Development in the Southeastern Coastal Zoe._University of South Carolina Press,
Columbia, S. C, 519 pp.
VELES, H. A., and GOUDIE, A. S., 2003. Interannual, decadal and multidecadal scale climatic
variability and geomorphology. Earth-Science Reviews, vol. 61, no. 1/2, pp. 105-131.
VILES, H., and SPENCER, T. 1995. Coastal Problems: Geomorphology, Ecology, and Society at
the Coast. Edward Arnold, London, 350 pp.
VITEK, J. D., GLARDINO, T. R., and FITZGERALD, J. W., 1996. Mapping geomorphology: a
journey from paper maps through computer mapping to GIS and virtual reality.
Geomorphology, vol. 16, no. 3, pp. 233-249.
* VON DER OSTEN, K., 1993. A construction and development guide to the coastal areas of
Florida. Masters Thesis, Department of Building Construction, University of Florida,
Gainesville, 47 pp.
WALMSLEY, D. J., EPPS, W. R., and DUNCAN C. J., 1998. Migration to the New South Wales
North Coast 1986-1991: lifestyle motivated counterurbanism. Geoforum, vol. 29, no. 1 pp.
105-118.


CHAPTER 4
METHODOLOGY
This research is divided into two areas of inquiry; the influence of the actual
geomorphology and the impact of geomorphic variability, on planned and actual coastal
development in two regions of Florida over a 27-year period. The actual geomorphology affords
temporal analyses of impacts. Geomorphic variability enables spatial distributions and patterns to
be investigated along the shore. The two regions investigated have experienced different storm
and hurricane influences (Appendix A) and are governed by separate policy making entities.
The availability of geomorphology data obtained from the State of Florida, Department of
Environmental Protection (FDEP) is shown in Table 4-1. From these data the variables shown in
Table 4-2 and Appendix B are derived. The maximum dune height (DH), distance of maximum
dune height from National Geodetic Vertical Datum (NGVD) (DHBW), beach width index (BW),
the distance from the monument to the maximum dune height (MDH), are shown in Figure 4-1.
Long-term shoreline change (LT), shoreline orientation (OR) the presence of reinforcement
structures (SW), the erosion status (ER) and past renourishment activities (RN) are also included
in the analyses as independent variables. These variables characterize the time-specific
conditions.
Development variables include land use from local comprehensive plans (FLU), the future
land use plan densities (FLUD), the number of residential dwelling units (UN) (of 8 or less
dwelling units per structure), units per hectare (UH), percentage impervious area (PIM), and
hectares of commercial land use (C). The distance to the nearest access point to the coastal area
by causeway or major highway (ACC) and distances incorporating a direction component
(DACC), the position of the shore parallel highway (ROAD) and the geographic location (POS)
are also included in the analyses as dependent variables.
44


116
drawn from this result is the lower the long-term change, or erosion are associated with higher
impervious areas. However, as discussed earlier, Brevard County has a stable shoreline, with
only the area between monument 154 and 163 experiencing long-term erosion and of < 0.2 m
from 1870 to 1999, so a low value of LT represents a stable shoreline. In 1997 sample areas with
a high percentage of impervious area occur when the orientation is higher or orientated north-
south. It would be anticipated that highly impervious sample areas would be more suitable where
the total beach width change was low. Almost 60 percent of the determination of the 1997
impervious area, therefore, is a function of the orientation, in areas with stable historical
shorelines and small absolute change in beach width over the study period
Hypothesis 2b proposes an adaptation of Bush and others (1999), assuming that future land
use outcomes are the result of the dynamic characteristics of the physical environment. The total
units in Brevard County have been demonstrated to have a negative relationship with the 1972
beach width weighted by road position. The result below shows that higher total units are
associated with that variable and the long-term change, a dynamic variable in association with the
structures dummy variable. Higher total units are proposed in the future land use plan where
there are shoreline protection structures and accretion, and wider beaches where the road is
further from the shore. An example of an area with these characteristics is Cocoa Beach. There
is a sea wall present, the long-term trend is accretion, and there is a large area between Highway
A1A and the shore and perpendicular streets.
Brevard County, Entire County-1997 Future Land Use Units (FLU,3)
FLU a = 267.215 + 287.849 LTSW 0.614 BW.2 ROAD
(n=l 13, R2=0.351)
FLU ,3 = Potential Units, Comprehensive Plan (2000)
LTSW = Long term Change, 1870-1999, (m) Structures Dummy (1-structures present, 0-no
structures)
BW a ROAD-1986 Distance from Monument to NGVD (m) weighted by the position of the
parallel access (3-<100m inland, 2-100m to 200m inland, l->200m inland, 4 more than 1 parallel
access road)


23
requirements was made by Brevard County in 1988. Each Comprehensive Plan must be updated
every 10 years. Therefore, the study areas have plans from three time periods, the 1970s, late
1980s and late 1990s. Each plan delimits the existing last use and proposed future land use
restrictions at a parcel level. Use of parcel data provides the ability to use detailed information
and to combine it to consider cumulative impacts on the coast (Hart, 2000). The public policy of
the local jurisdiction, illustrated by the existing adopted future land use restrictions are
investigated in this research.
Research Hypotheses
Schumm (1991) uses examples to illustrate the potential errors that can be made when
attempting to extrapolate from the present to the future, or past in earth sciences. Schumm
maintains that the use of multiple hypotheses will eliminate problems with interpretation of
natural systems. He notes multiple hypotheses assist with specific procedural problems that may
be encountered in the development of explanations of phenomena and the extrapolation of
research finding to analogous and homologous situations (Schumm, 1992, pp. 34). There are
four main hypotheses investigated in this research.
Hypothesis 1: Local geomorphologv at each time interval impacts human variables at the same
interval
Hypothesis la: The local geomorphology influences the actual development. This
hypothesis is illustrated by a relationship between actual geomorphology, and the human
variables at that time (Conway and Nordstrom, 2003). An example of this is the impact of the
beach width on the number of units. A wider beach indicates a more stable coastal area that may
be suitable for more units, than an area with a narrow foreshore.
Hypothesis lb: The local geomorphology influences the land use control decision-making.
This hypothesis proposes that future land use plans are developed by considering
geomorphological conditions, such as the suitability of land use for development noted by Hails
(1977). An example of this hypothesis is an area with large dunes being designated as suitable


15
Dolan (1976) considers seasonal beach profile variations are of minor significance because
the change is confined to the shoreface. Unless significant winter storms breach the primary dune,
the area of wave runup is the dynamic portion of the profile, constrained by the first topographic
berm structure. During high-energy storms, erosion will cause the beach width to increase
providing a larger area over which wave energy can dissipate. A barrier island with no
obstructions to sediment transference can withstand periodic storms (Meesenburg, 1996). Another
shortcoming of profile data is that the profile may not extend far enough to incorporate all aspects
of the sediment budget. Sediment loss from aeolian forces that extend inland beyond the profile
will not be accounted for. Similarly sediment that is transported beyond the beach face offshore
may be considered lost to the system.
Population and the Coast
Having established the physical environment in which this research occurs, it is important
to review the policy direction and ultimate development of the human environment in coastal
reaches. Fifty percent of the worlds population lives within 1 kilometer of the coast (Goldberg,
1994), 75 percent of the United States population lives within one hours drive of the coast and in
Florida 80 percent of the population lives in the coastal counties (Finkl, 1996). Coastal counties
comprise 20 percent of the nation's land area, contain almost half the population and by 2010 will
contain more than 127 million people (H. John Heinz Center, 2000). Lins (1980) determined that
even in the mid 1970s 37 percent of the Atlantic and Gulf coasts of the Untied States contained
development and by 1983 741 kilometers or approximately 63 percent of the Florida coastline
was developed (U. S. Department of Interior, 1983).
Patterns of development are measures of spatial arrangement. Locations with the same
population density may not have the same spatial arrangement of land uses (Vemberg et al.,
1996). The distinction between the size, nature, and arrangement of settlements and the specific
pattern of the community is important. The location of a community in relation to the
environment, and on a smaller level, the specific layout of a community, represents spatial


119
that hurricane impacts were the equivalent of 50 years of coastal erosion in one season. These
areas were identified as having long-term (LT) erosion (Figure 4-2, Figure 4-3) and narrow beach
widths (Appendix I) in this research.
In Brevard County, maintenance renourishment is proposed to be accelerated at Cocoa
Beach (monument 1 to monument 53), where dune heights (DH) were low, structures were
present (SW) and beach width was narrow in this research (Appendix I). In the vicinity of
Melbourne Beach (monuments 118 to 138) additional renourishment is proposed, in an area that
has narrower beach width (BW, DHBW) than adjacent areas. Dune restoration is recommended
for the Satellite Beach area (monuments 85 to 118) and south Brevard County (monuments 138 to
218). Although dune heights in southern Brevard County were higher than northern Brevard
County, the trend was a decrease from the 1972 recorded maximum height (Appendix I). This
area of Brevard County is also the only area that had long-term shoreline changes (LT) that were
negative (Appendix F). Post hurricane data and recommendation (DEP 2004a, DEP 2004b) can
be used to confirm that areas that were prone to erosion and dynamic change during the study
period were the areas that received impacts during the 2004 hurricane season. This illustrates the
relevance of the research and importance of the consideration of historical data in long-range land
use planning.


95
Table 5-5. Descriptive statistics, density (UH), and future land use density (FLUD)
Standard
Kolmogorov-
Count Mean
Deviation
Min.
Max. Smirnov
0.05
Normality
Units per Hectare (Brevard County)
UH
138
3.2
5.1
0.0
36.5
0.2603
0.075
Reject
UHa
138
4.3
5.5
0.0
36.5
0.2098
0.075
Reject
UHa
138
5.0
5.8
0.0
36.5
0.1889
0.075
Reject
UHa-i
138
1.1
2.4
-1.5
20.7
0.2412
0.075
Reject
uh.2
138
0.6
1.5
-4.0
10.0
0.2390
0.075
Reject
UHa.,
138
1.8
3.3
-3.4
30.7
0.2041
0.075
Reject
Future Land Use (Brevard County)
FLUD,,
124
21.2
11.9
3.0
30.0
0.3994
0.079
Reject
FLUDa
125
22.3
22.0
0.0
70.4
0.2007
0.079
Reject
Units per Hectare (St. Johns County)
UH
138
1.4
1.8
0.0
8.2
0.1983
0.076
Reject
UH,2
138
2.2
2.4
0.0
12.8
0.1749
0.075
Reject
UHa
138
3.5
3.2
0.0
20.9
0.1291
0.075
Reject
UHa-,
138
0.8
1.4
-1.2
7.4
0.1907
0.075
Reject
UH,3.2
138
1.3
2.3
-7.3
11.3
0.2027
0.075
Reject
UHa.,
138
2.1
2.8
-3.2
15.4
0.1552
0.075
Reject
Future Land Use (St. Johns County)
FLUD,,
137
1.3
1.2
0.0
4.1
0.1720
0.075
Reject
FLUDa
138
2.3
1.8
0.0
9.1
0.0860
0.075
Reject
FLUDa
138
6.3
3.00
0.0
15.0
0.1987
0.075
Reject
Units per Hectare (St. Johns County, Monument 1 to 121)
UH
79
1.4
1.7
0.0
7.7
0.2275
0.099
Reject
UHa
83
2.1
2.2
0.0
7.9
0.2020
0.097
Reject
UHa
83
3.5
2.9
0.0
11.3
0.1375
0.097
Reject
UHa.,
83
0.8
1.1
-0.5
5.1
0.2330
0.097
Reject
UHaa
83
1.4
2.6
-7.3
11.3
0.2123
0.097
Reject
UHa.,
83
2.2
2.7
-3.2
11.3
0.1694
0.097
Reject
Future Land Use (St. Johns County, Monument 1 to 121)
FLUD,,
83
1.4
1.2
0.0
3.4
0.2116
0.097
Reject
FLUDa
83
2.0
1.4
0.0
6.9
0.1083
0.097
Reject
FLUDa
83
6.9
2.6
0.3
15.0
0.2465
0.097
Reject
Units per Hectare (St. Johns County, Monument 140 to 195)
UH
45
1.7
1.9
0.0
8.2
0.1806
0.131
Reject
UHa
44
2.7
2.8
0.0
12.8
0.1442
0.132
Reject
UHa
44
3.7
3.9
0.0
20.9
0.1873
0.132
Reject
UHa-,
44
1.0
1.8
-1.2
7.4
0.1493
0.132
Reject
UH.3.2
44
1.0
1.7
-1.1
8.1
0.2182
0.132
Reject
UHa.,
44
2.1
3.1
-1.2
15.4
0.1839
0.132
Reject
Future Land Use (St. Johns County, Monument 140 to 195)
FLUD,,
43
1.6
1.3
0.0
4.1
0.2162
0.134
Reject
FLUDa
44
3.2
2.1
0.0
9.1
0.1223
0.132
Accept
FLUDa
44
6.3
3.0
0.0
14.8
0.1986
0.132
Reject


102
distance and direction to access (DACC). This indicates that areas with wider beaches are closer
to the access points to the coast.
Table 5-9. Beach width and future land use in St. Johns County
Future Land Use
Beach Width (BW)
Density (FLUD)
1972 ()
1986 (a)
1999 ()
1972-1999
1972
0.437
0.171
-
-
1999
0.340
0.374
0.317
0.342
95% confidence interval, -
denotes no significance
Table 5-10. Beach width and future land use in St. Johns County (monuments 141 to 198)
Future Land Use
Beach Width (BW)
(FLUD)
1972
1986
1999
1972
0.468
NA
NA
1999
0.541
0.730
0.637
95% confidence interval, NA=temporal antecedence,
The Beach Width Factor (BWf) has positive relationships with the discrete time frames for
units (UN), impervious area (IMP, PIM) and hectares of commercial activities (C) supporting
Hypothesis 2a. BWf has a value of between 1 and -1. Values closest to 0 indicate dynamic areas
where the net change is smaller than the total change. An area can be defined as dynamic if the
measure, such as beach width, has varied over time. If the net change over time is small, the
original and final shoreline positions are close to each other. Therefore, a low beach width factor
indicates a dynamic area. Negative values for BWf are influenced by the negative net change
because the total change is an absolute, and indicates a net reduction in beach width, or erosion.
A positive relationship between BWf and the dependent variables indicates that more intense
development occurs where the beach width factor is higher and positive, indicating accretion.
Using the Spearman Rank analyses in St. Johns County the BWf indicates that during the study
period decisions concerning development of the coastline have been made by appropriately
assigning higher densities and intensities of use where the beach was stable or experiencing
accretion. The total units in adopted in land use plans also shows that future planning will occur
in areas that are more suitable (Hypothesis 2b).


108
(C) in the three time periods (Hypothesis 2a). This indicates that higher amounts of impervious
surface and percentage of impervious surface, and commercial development occur in 9-ha sample
areas with higher long-term change values, representing coastal accretion. In Brevard County the
LT variable is negative only between monuments 154 to 163 (Figure 4-3 and Appendix F). The
higher the long term change value the higher the potential units and densities planned for in the
1970 future land use and the most recent future land use plan supporting Hypothesis 2b. This
indicates an appropriate connection between the intensity and planned future unit densities and
the understanding of the long-term coastal change.
Table 5-20. Long term change, development and future land use variables, Brevard County
Long Term Change (LT)
Year IMP PIM C FLUD
1972(tl) 0.3165 0.2464 0.2786 0.3172
1986 (a) 0.3528 0.2837 0.2716 NA
1997 (t3) 0.1781 0.3165 0.3015 0.3037
95% confidence interval
In St. Johns County the number of units in the 1970s (UN,i) and 1980s (UNt2) show a
significant positive relationship with the long-term coastal change (LT). Although similar to
Brevard County, the relationships between the amount and intensity of impervious area, the
indicators of more intense development being associated with a higher long-term coastal change
value are less consistent. The areas of the St. Johns County coast that experience higher levels of
change over time are also areas where local policy makers, through the adoption of future land
use, have designated as suitable for high densities. The location of the sample area from the north
(POS) showed that the long term change was more likely to be higher the further from monument
1, or the northernmost point.
Table 5-21. Long term change, development and future land use variables, St. Johns County
Year
IMP
Long Term Change
PIM C
FLUD
1972 ()
0.2528
-
-
0.1966
1986(a)
0.3249
0.2631
-
0.3748
1999 (,3)
0.2786
0.2291
0.1901
0.1958
95% confidence interval


101
impervious area. The BWtot variable is an absolute value so it does not distinguish between
accretion and erosion. A large value for the total beach width change must be considered in
conjunction with the net change (BWt3.i) and beach width factor (BWf), which is not supportable
in bivariate analyses.
In St. Johns County, there are a higher number of the Beach Width (BW) test statistics at
0.05 significance, and the patterns are similar to Brevard County (Appendix H). It should be
noted that the interpretation of these data should be made with caution. In St. Johns County the
analyses produced a spurious result for BWt3 (beach width in 1999) and IMPti (impervious area in
1972). It is unlikely that the 1972 impervious area is a function of beach width in 1999 and is an
example of temporal antecedence. This is noted in the following tables by the designation NA.
This is an example of potential feedback between independent and dependent variables that
provides potential for further research. The dependent variables in the discrete time periods show
more interaction with the beach width than in Brevard County (Hypothesis la). For example, a
positive value for the UNa, IMP^, PIM|2 and Ca with BW,2 indicates that in 1986 higher numbers
of units, impervious area and hectares of commercial development in each 9-ha sample area occur
where the beach is widest in 1986 (Table 5-8).
Table 5-8. Beach width and impervious area in St. Johns County
Impervious Area Beach Width (BW)
(IMP)
1972 (>
1986()
1999()
1972-1999 (.i)
1972
0.183
0.334
0.400
0.425
1986
NA
0.460
0.512
0.411
1999
NA
NA
0.476
0.397
95% confidence interval, NA=temporal antecedence.
Similar to Brevard County, the future land use and beach width also have positive
associations, indicating that the plans for higher densities were made for areas where the beach
width is widest (Table 5-9). The relationship between beach width and future land use is more
pronounced for Anastasia Island, when those data are considered without the rest of St. Johns
County (Table 5-10). The BW variables show a consistent negative relationship between the


140
Table E-l.
Continued
EW
Monument Date
Northing Northing
NS Change Easting Easting
change
Number
Set
(position 2)
(in m) 1 (position 2)
(in m) 2
38
Aug-72
1445928.00
625797.50
39
Aug-72
1444940.00
625847.00
40
Aug-72
1443979.00
625875.00
41
Jan-80
1443027.00 1443027.00
0.00 625906.50625906.50
0.00
42
Aug-72
1442029.00
625926.00
43
Jan-80
Monument replaced > 3m from original
44
Jan-80
Monument replaced > 3m from original
45
1993
1439089.00 1439089.00
0.00 626001.20626201.80
-61.14
46
Aug-72
1438130.00
626030.50
47
Aug-72
1437135.00
626144.00
48
Aug-72
1436195.00
626235.00
49
1993
Monument replaced > 3m from original
50
Jan-80
Monument replaced > 3m from original
51
1985
1433308.00 1433307.00
0.30 626427.10626467.00
-12.16
52
Jan-80
Monument replaced > 3m from original
53
Jan-80
1431532.00 1431535.00
-0.91 626539.60626564.00
-7.44
54
Jul-83
1430542.00 1430545.00
-0.91 626673.60626690.00
-5.00
55
Jan-80
Monument replaced > 3m from original
56
Jan-80
1428589.00 1428594.00
-1.52 626993.50627018.50
-7.62
57
Jan-80
1427747.00 1427751.00
-1.22 627105.60627132.40
-8.17
58
Jan-80
1426773.00 1426773.00
0.00 627256.00627256.00
0.00
59
Jun-85
Monument replaced > 3m from original
60
Jun-85
1424801.00 1424802.00
-0.30 627557.20627579.00
-6.64
61
Jun-85
1423811.00 1423815.00
-1.22 627692.80627709.00
-4.94
62
Jan-80
1422824.00 1422827.00
-0.91 627835.60627855.00
-5.91
63
Jan-80
1421857.00 1421862.00
-1.52 627973.10628007.00
-10.33
64
Jan-80
1420892.00 1420891.00
0.30 628132.00628131.90
0.03
65
Jan-80
1419915.00 1419917.00
-0.61 628255.80628271.80
-4.88
66
Aug-72
1418930.00
628402.50
67
Jan-80
1418062.00 1418068.00
-1.83 628519.10628532.00
-3.93
68
Jan-80
Monument replaced > 3m from original
69
Aug-97
Position of NGVD is landward of original monument position
70
Aug-97
Monument replaced > 3m from original
71
Aug-97
Monument replaced > 3m from original
72
Jan-80
Monument replaced > 3m from original
73
Aug-97
1412305.00 1412309.00
-1.22 629154.50629302.60
-45.14
74
Aug-97
Monument replaced > 3m from original
75
Aug-72
1410446.00
629438.50
76
Jan-80
Monument replaced > 3m from original
77
Jan-80
1408603.00 1408603.00
0.00 629686.00629686.00
0.00
78
Jan-80
1407611.00 1407617.00
-1.83 629809.40629831.50
-6.74
79
1993
Monument replaced > 3m from original
80
1993
Monument replaced > 3m from original
81
Aug-97
1404749.00 1404746.00
0.91 630238.50630270.40
-9.72
82
Jan-80
1403779.00 1403787.00
-2.44 630410.10630439.50
-8.96


16
patterns at contrasting scales. This work concentrates on the influence of geomorphology on the
macrosettlement or location within the confines of the physical environment.
In coastal areas settlement patterns do not necessarily conform to established settlement
norms. The physical environment and transportation access supplies a set of limitations or
controls. Coastal development of barrier beaches reflects a recognized style that is limited by
topography (Kostof, 1991). Montreal has a linear pattern determined by the location of the river
and Reps (1965, pp. 68) states the general form of this city a narrow linear pattern was
strongly influenced by topography. Coastal development is similarly influenced by topography
and patterns also conform to the linear pattern recognized by Reps.
Contemporary Coastal Settlement Patterns
Spatial patterns are particularly relevant in coastal areas because although population
densities may not be increasing, urbanization of land is occurring (Davidson-Arnott and
Kreutzwiser, 1985). The transition from industrial to post-industrial cities, and from modernism
to post-modernism has caused urban form to decentralize. Polynucleated areas with amorphous
suburbs have eclipsed the former metropolitan concentrations driven by industrial growth.
Distinct patterns of tourist-driven growth have been identified (Meyer-Arendt, 1990)
Vemberg and others (1996) identify the predominant pattern of coastal development in the
southeastern United States to be urban concentrations with adjacent low-density areas. The
population density of an area many not change even when the settlement patterns vary. Over the
last 30 years the number of metropolitan areas nationally has increased, while the average density
has decreased (Vernberg et al., 1996). A study of coastal counties in the southeastern United
States using aerial photography and satellite images showed that sparsely populated counties were
becoming populated with low density residential developments (Vernberg et al., 1996). Thus,
more land is consumed and the urban area expands without a change in the population density.
In coastal areas, the segments of population that are expanding most rapidly are whites and the
elderly (Vemberg et al., 1996). Vernberg states low-density residential use along the shoreline


123
Higher total units were proposed in the future land use plan where there are shoreline protection
structures and accretion, and wider beaches in areas where the road was further from the shore.
Table 6-2. Bivariate analyses of dynamic geomorphology and human variables
Brevard County
BWq-]
Positive
UN UH,m, IMPq.1, PIM,2,
BW10t
Positive
UN,,., UH., PIM.,
MDH ,ot
Positive
IMPtit t2f t3, PIM,i 2 t3, Cti t2, t3 FLUD,i FLUD ,3
LT
Positive
IMP,, a u PIM a o C,, FLUD FLUDo FLUDC
DH,1 ,2. ,3
Positive
UN. -2, UH. n-¡
St. Johns County
BW.3.1,
Positive
IMP,, IMP,,, IMPe FLUD FLUD
BWf
Positive
UN a, 0, IMP ii. t2, o. PIM a, 13, FLU a, FLU a
LT
Positive
IMP,, a PIM,, a C FLUD,, FLUD,, FLUD,,
Northern St. Johns County, Ponte Yedra to Vilano Beach
MDH,,., MDH,,.,
Positive
FLU
Anastasia Island, St. Johns County
LT
Positive
UNt2, t3, t2-l, t3-2, t3-l UH tl, t2, t3, t2-l, t3-2, t3-l, FLU t3, FLUD o
MDH,,., MDH,,.,
Positive
FLU t3,FLUDo
In Brevard County higher intensity of development is associated with lower maximum
dune height. However the dynamic variables show that the largest changes in units and density of
units have occurred in areas where the maximum dune height is largest. Therefore, when the
actual geomorphology is considered, the existing pattern of development is more intense where
dunes are lowest. The dynamic geomorphology variables show that the most change in units and
density occurs where the maximum dune height is highest, indicating that the existing situation
may not be the most suitable in terms of dune development, but increases in development
intensity are occurring in more appropriate areas of Brevard County based on dune height and
change in dune height over time as a measure of dune stability and development suitability. The
St. Johns County total units in the proposed future land use plan, for 2015 are a function of beach
width and dune height. Similar to other results, the dune height coefficient, is negative. Higher
total units planned for 2015 would be anticipated to occur where the beach width in the earlier
time period was higher. However, a negative coefficient for change in dune height indicates that
higher numbers of units were planned where the dune height change over time was low or
negative.


20
repair and the operation, maintenance and construction of military facilities are exempted. In
Southern Brevard County between monuments 157 and 164 there is a CBRA designated area.
Coastal management at all levels is complicated by the conflicting mandates of the various
agencies. Nationally the Corps of Engineers permits dredge and fill and coastal structures, while
the Environmental Protection Agency protects wetlands. Neuman (1999) illustrates the
complications using an example of barrier island bridge construction. The construction may be
warranted by traffic counts by the Department of Transportation, encouraged by tourism goals of
the Department of Commerce and the local jurisdiction, and permitted for construction by the
Corps of Engineers. The Department of Environmental Protection may deny the project because
of endangered species protection. States have a variety of ways of controlling the coastal zone,
while remaining consistent with the Coastal Zone Management Act. North Carolina and
California have Commissions authorized to enact coastal legislation. New Jersey manages the
coast through the executive branch and uses a process of cross acceptance (Neuman, 1999).
Coastal zone management is integrated so that planners, politicians, academics, and citizens
develop policy collaboratively. Regional programs, such as for the Chesapeake Bay are also used
to manage specific resources.
In Florida, as in many other states and at the Federal level, coastal zone management is
decentralized. In 1992 the Department of Community Affairs, created a Coastal Zone
Management Office within the Secretary's Office. This was to address the fringe nature of
coastal management in the realm of state government (Bemd-Cohen et al., 1993, pp. 41).
Previously the Florida Coastal Management Program had been located in Department of
Environmental Protection (Bernd-Cohen et al., 1993). The State Department of Community
Affairs is the Department charged with land use and resource planning and enforcement of the
States growth management plan. The move realigned coastal management in Florida with the
policy, land use and development activities, rather than environmental and data collection
functions of the Department of Environmental Protection. In this way the enforcement of growth


63
width index (NGVD to monument) (b) for consistency amongst all the data sets. The standard of
3 m in north south variation is assumed not to necessitate amendments in dune height variables
(Rahn, 2001). However, in cases where the maximum dune height occurs at the monument, the
maximum dune height recorded at or seaward of the new position is used and the maximum
height to NGVD is amended.
Table 4-6. Sample data changes for landward (west) relocation of monument
1972 | 1972 data are unchanged
1979-Monument relocated landward (west) 10 m in 1979
1986
Amend: (a) Monument to maximum dune height reduced 10
m
Beach width index (NGVD to monument) reduced 10 m
Maximum dune height revised to the Maximum height at or
seaward of the original monument position
1999
Amend: (a) Monument to maximum dune height reduced 10
m
(b) Beach width index (NGVD to monument) reduced 10 m
(c) Maximum dune height revised to the Maximum height
at or seaward of the original monument position
Figure 4-10. Profile revision diagram, monument moved seaward (to east)


57
structures may impact the Beach Width Index, by steepening the beach and reducing the distance
to NGVD. This variable is recorded categorically as structures present or absent only.
Table 4-5. Brevard County shoreline position records
Monument Range
Earliest Record
Most Recent record
1-77
1877
2001
82-84, 94
1877
1999
78-81,85-93,95-108
1877
1997
116-120,147,157, 164,169
1878
1999
108-114, 122-143, 148-154,
1878
1997
156,162-163,165
159
1878
1993
155, 158, 160-161, 170
1878
1986
182,186, 198
1879
1999
171, 172, 174-180, 183-185,
1879
1997
188-197, 199,200
Source: http://hightide.bcs.tlh.fl.us/counties/HSSD/readme/read.mel
Renourishment of the coast during the study period will affect geomorphic variables, but is
initiated and made necessary by human presence on the coast. This variable is recorded
categorically as renourished or not (RN) and areas of renourishment are outlined in Chapter 3.
Brevard County has practiced dune renourishment (Olsen, 1989; Brevard County Comprehensive
Plan, 1988; Foster et al., 2000), which is recorded as a separate variable, RND.
Geographic Location (POS) and Orientation (OR)
The geographic location variable is a measure of the position of the center of the 9-ha
sample area from of the monument, along the coast. A smaller number indicates a location
further north in the respective county. This variable in conjunction with the analyses of data by
geomorphic unit provides spatial context the statistical analyses. In Brevard County the


LD
1780
90 OS
. L25J3.
UNIVERSITY OF FLORIDA
3 1262 08556 6304


APPENDIX C: SAMPLE RAW DATA FROM THE DEPARTMENT OF ENVIRONMENTAL
PROTECTION
(http://www.dep. state. fl.us/beaches/data/his-shore.htm#ProfileData)
Brevard County Department of Environmental Protection Raw Data
Countv
Date of
monument
establishment
BREVARD
R-1
SEP-N07
Aug-72
13-Sep-7;
INE (OK EF)
Distance from
Monument
(feet)
R-2
-83
114
300
550
Aug-72
13-Sep-72
8.75
10.51
3.39
-1.84
Monument
number
-200
6.61
-150
6.78
-100
6.75
-50
6.7
-13
0
8.82
12
7.79
50
7.94
87
8.39
100
122
3.25
150
2.7
200
1.29
250
-0.65
300
350
-1.68
400
-2.2
450
-2.68
500
-3.06
550
642
-2.1
741
-3.6
870
-5.8
990
-8
1134
1254
-9
1413
-9.7
1545
-11.1
1650
-12.4
1785
1950
-14.5
2160
-15.1
2280
-15.5
2397
-16
2550
2700
-17.1
2844
-17.5
2997
-18.2
3150
-18.9
100
250
500
137


CHAPTER 1
INTRODUCTION
the historical dimension of geomorphology prevents it from being 'reduced to physics', and
secondly, the key role that human activities (which defy all rationality) play in modifying
the Earth's surface ensures a unique place among the sciences.
John D. Jansen, Gemorphlist, May 2002
Historically, the natural and physical features of the locale have influenced settlements.
Ancient cities were sited at river confluences, in flat areas of mountainous terrain and at strategic
defensive locations. Early coastal development began inland of passes giving settlers access to
the ocean. Although barrier islands were not the areas of choice for settlement because of their
isolation and lack of access, bridge construction allowed development of barrier islands. The
coastal zone is recognized as a dynamic environment, and extensive fluctuation of this
environment may make it inappropriate for intense development.
Development along the coastal barriers has been driven by a variety of issues. This
research investigates the level to which development is permitted and occurs in preferentially
safer, or more stable areas (with higher dunes or wider beaches). The work retrospectively
examined the interaction between natural and physical features (specifically the geomorphology)
and land use changes. The research evaluated the extent to which characteristics of the
immediate area (dune height, and beach width) influenced patterns of development. Aerial
photography and Geographic Information Systems are used in the evaluation of the dynamics of
the local environment and the impact on past, current, and future land use patterns in two counties
in coastal Florida.
The main goal was to determine the extent to which the local geomorphology of the coastal
environment shapes existing and future patterns of development. Dolan (1976, pp. 76) said that
planners and decision-makers responsible for the management of the shoreline resources must
1


9
Melbourne
10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190
Monument Number
X1972 1986 1997
Figure 1-3. Brevard County hectares of impervious area with trend, 1972-1997 (IMP,i, IMP,i, IMPti)


84
Table 5-2. Descriptive Statistics, maximum dune height (DH)
Standard Kolmogorov-
Count Mean
Deviation Min. Max.
Smirnov
0.05
Normality
Maximum Dune Height (Brevard County)
DH
136
5.0
1.0
2.6
7.2
0.0623
0.076
Accept
DU,2
131
5.0
1.0
3.0
7.3
0.0559
0.077
Accept
DH
131
5.1
0.9
3.0
7.4
0.0781
0.077
Reject
DHtf.i
129
0.01
0.7
-5.6
3.3
0.1874
0.078
Reject
DH.2
128
0.2
1.0
-2.3
6.8
0.2959
0.078
Reject
DHi3.,
125
0.1
0.4
-1.4
1.4
0.0875
0.079
Reject
DH,ot
125
0.7
1.2
0
10.9
0.2851
0.079
Reject
DHf
121
0.2
0.7
-1
1
0.1625
0.079
Reject
Maximum Dune Height (St. Johns, Entire County)
DH
170
5.5
2.0
2.6
10.3
0.0922
0.068
Reject
DHu
169
5.6
1.8
3.0
10.2
0.1172
0.068
Reject
DH,,
169
5.8
2.0
3.0
10.2
0.0998
0.068
Reject
DHa.,
170
0.1
1.3
-6.35
8.1
0.2879
0.068
Reject
DHa.2
170
0.2
1.1
-5.00
9.1
0.2569
0.068
Reject
DHa.,
170
0.3
1.6
-6.4
9.1
0.2572
0.068
Reject
DH,,
170
0.9
1.5
0.02
9.1
0.2731
0.068
Reject
DHf
170
0.1
0.8
-1.0
1.0
0.1816
0.068
Reject
Maximum Dune Height (St. Johns, North, 1 to 121)
DH
111
5.8
1.8
3.3
10.3
0.1017
0.084
Reject
DHa
110
5.8
1.8
3.3
10.2
0.1324
0.084
Reject
DH,3
110
5.9
2.0
3.2
10.2
0.1451
0.084
Reject
DHa.,
111
-0.03
0.7
-6.4
1.8
0.3150
0.084
Reject
DH,3_2
111
0.2
0.9
-1.0
9.1
0.2898
0.084
Reject
DHa.,
111
0.1
1.2
-6.4
9.1
0.2729
0.084
Reject
DHt0,
111
0.5
1.1
0.02
9.1
0.3152
0.084
Reject
DHf
111
0.0
0.8
-1.0
1.0
0.1728
0.084
Reject
Table 5-3.
Descriptive Statistics, maximum dune height (DH), Anastasia Island
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05
Normality
Maximum Dune Height (St. Johns, Anastasia Island, 141 to 195)
DH 48 5.1 2.4 2.6 9.6 0.1078
0.127
Accept
DHU
48
5.5
1.8
3.0
9.5
0.0906
0.127
Accept
DH,,
48
5.9
1.7
3.0
9.5
0.0764
0.127
Accept
DHi2.,
48
0.4
2.1
-5.0
8.1
0.2930
0.127
Reject
DH.2
48
0.4
0.9
-2.7
2.4
0.1630
0.127
Reject
DH.3-1
48
0.8
2.1
-5.0
6.9
0.1670
0.127
Reject
DH,0,
48
1.7
2.0
0.1
9.5
0.1848
0.127
Reject
DHf
48
0.3
0.8
-1.0
1.0
0.1961
0.127
Reject


156
Table G-l. Continued
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov 0.05 Normality
Future Land Use
FLU,j
125 110.7
131.035
0
562.31
0.1912
0.079 Reject
FLUCa
125 0.7
1.326
0
6.4
0.3504
0.079 Reject
Table G-2.
Descriptive statistics, dependent and :
independent variables, St. Johns County
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05
Normality
Monument to Maximum Dune Height
MDH 116 6.8 7.9
0.0
45.7
0.1856
0.082
Reject
MDHa
117
11.2
12.9
0.0
53.0
0.1867
0.081
Reject
MDH,3
116
13.1
15.3
0.0
72.2
0.1951
0.082
Reject
MDH,2.i
119
4.4
14.5
-45.7
53.0
0.2190
0.081
Reject
MDHa.2
119
1.7
11.4
-23.8
72.2
0.2646
0.081
Reject
MDH,,
120
6.1
16.9
-36.6
72.2
0.2288
0.080
Reject
MDH10t
120
14.3
16.1
0.0
72.2
0.1789
0.080
Reject
MDHf
120
0.1
0.8
-1.0
1.0
0.1822
0.080
Reject
Maximum Dune Height
DHBW 166 74.9
to NGVD
20.1
20.1
135.8
0.1557
0.068
Reject
D[IBW,2
168
88.2
31.2
19.5
190.6
0.1439
0.068
Reject
DHBW,J
166
77.1
31.4
22.4
170.9
0.1870
0.068
Reject
DHBWa.i
169
14.5
23.8
-76.5
139.5
0.1246
0.068
Reject
DHBW.3-2
169
-12.0
16.9
-64.2
53.2
0.0747
0.068
Reject
DHBWt3.,
169
2.6
25.4
-76.5
131.2
0.1806
0.068
Reject
DHBWtol
169
35.3
26.7
1.3
147.8
0.1574
0.068
Reject
DHBW,
169
-0.1
0.6
-1.0
1.0
0.0759
0.068
Reject
Number of Units
UN,i 138
7.2
10.2
0
55
0.2318
0.075
Reject
UNU
138
11.1
14.2
0
78
0.2111
0.075
Reject
UNa
138
17.8
19.6
0
127
0.1796
0.075
Reject
UNa-i
138
3.9
8.7
-9
58
0.2614
0.075
Reject
UNa.2
138
6.7
12.0
-11
60
0.2616
0.075
Reject
UNu.,
138
10.6
16.5
-11
94
0.2287
0.075
Reject
Hectares of Impervious
IMPtl 138 0.2
0.4
0.0
2.1
0.2955
0.075
Reject
IMPa
138
0.6
1.0
0.0
5.0
0.2500
0.075
Reject
IMPa
138
1.1
1.4
0.0
6.9
0.2228
0.075
Reject
IMPa.,
138
0.4
0.8
-0.4
5.0
0.2819
0.075
Reject
IMPa.2
138
0.4
1.0
-0.4
6.8
0.2732
0.075
Reject
IMPa.,
138
0.8
1.3
-0.1
6.7
0.2381
0.075
Reject


129
(such as location of structures) is subsequently reversed with the human variable ultimately
influencing the dune form in later time periods.
Final conclusions in this research would be lacking without the acknowledgment that the
2004 hurricane season was an important reminder that coastal research, even over a 30-year
timeframe, is incomplete. The historical record from 1871 to 2003 shows no incidence where
Florida was impacted by 4 hurricanes. Over 100 years of hurricane records does not adequately
capture long-term coastal influences serves as a reminder that catastrophic and unpredictable
events serve to complicate attempts at quantification and modeling the impacts of the coastal
environment on human behavior.
The dynamic nature of the coastline and its role in recreation, residential and
commercial development produces a dilemma. There is increasing demand for
undeveloped coastal land at the same time that coastal erosion is actually decreasing the
availability. Even shorelines that are stable are merely balanced between erosion and
deposition. This balance can be rapidly altered by a change in sediment supply, sea
level or the energy in the system, such as the level of storm activity. The physical
characteristics of the coast are not the only aspects to experience rapid and dramatic
change. In Florida each county and coastal municipality is governed by officials
charged with policy making and subject to removal at the whim of the electorate. This
aspect of coastal development will continue to frustrate quantification and modeling. As
a consequence, coastal land use planning requires an extensive array of data, the
understanding of policy implications and a long-term historical perspective. This work
broadens research on the interaction of the physical environment and human occupation
in the coastal zone. Determination of relationships between the physical parameters and
types of development provides tools to assist coastal managers, geomorphologists, land
use planners and public officials in endeavors to maximize access, while minimizing
unintended impacts in coastal areas.


53
Monument Number
Long Term Change (End Point and Rate Average with rolling average) j
Figure 4-3. Long-term shoreline change, Brevard County, with data ranges from 1877 to 2001


4
afforded convenience and economy, and became so popular that trailer parks along the shore
proliferated. In 1940, there were 3,500 trailer camps in the US (Lencek and Bosker, 1998). In
1972, both Brevard and St. Johns counties had mobile home and recreational-vehicle parks;
evidence that the coast was once considered a temporary venue. Ultimately it was not the
locomotive, automobile or affluence that opened the Florida coast to year-round vacationing and
permanent dwelling; it was the advent of air conditioning use. Air conditioning was available in
the 1930s, but was not in widespread use until the mid 1950s.
Research Purpose
Pressure is increasing between those who want to live on the coast and those who think it
should be preserved in its natural state (Ullmann et al, 2000). Most studies on human and coastal
interaction focus on human influence on natural systems rather than on the geomorphologys
influence in humans. This work considers the possibility that local land use policy and human
development variables are influenced by the coastal environment, or geomorphology. This
research quantifies the way in which coastal development has been influenced by the
geomorphology along the barrier shorelines of St. Johns County in northeast Florida and Brevard
County in east central Florida, over 27 years. Four hypotheses are considered.
1. Local geomorphology at each time interval impacts human variables at the same interval
2. The dynamic geomorphology impacts human variables
3. There are temporally lagged relationships between the actual and dynamic
geomorphology variables and the human variables.
4. The dependent variables will have different relationships with the independent variables
in the two separate study areas.


X 1972 1986 1999
Figure 1-6. St. Johns County impervious area variations, 1972-1999 (IMPtl, IMPl2, IMPt3)
Matansas Inlet


169
Table H-9. St Johns County Spearman Rank analyses (Ponte Yedra to Vilano Beach, Monument
1 to 120), Beach Width (BW) and ) and dependent variables at 0.05 significance
BW
BWa
BW,3
BW[2-1
BWo-i
BW.3-1
BWto,
BWf
LT
UN
-
-
0.4039
-
0.3170
0.4436
-
0.4017
0.2630
unq
-
-
0.3144
-
-
0.3299
-
0.2804
-
UN,3
-
-
-
-
-
-
-
-
-0.3652
UN.,
-
-
-
-
-
-
-
-
-
UNtf-2
-
-
-0.3027
-
-
-
-
-
-
UN0.,
-
-
-0.3247
-
-
-
-
-
-
UH
-
-
-
-
-
-
-
-
-
UHa
-
-
-
-
-
-
-
-
-
UH
-
-
-0.2808
-
-
-0.3625
-
-0.3892
-
UHq.,
-
-
-0.2755
-
-
-0.2755
-
-0.2809
-
UHu.2
-
-0.2641
-0.5023
-0.2513
-0.2698
-0.4781
-
-0.4755
-
UH0.,
-
-0.2578
-0.5390
-0.2528
-0.3171
-0.5457
-
-0.5392
-
IMP,,
-
-
0.4075
-
0.3316
0.4508
-
0.4104
-
IMP,,
-
0.2443
0.4424
-
-
0.3611
-
0.3469
-
IMP,
-
-
0.2205
-
-
0.2456
-
0.2668
-
IMP*,
-
-
-
-
-
-
-
-
-0.1206
IMP*,
-
-
-
-
-
-
-
-
-
IMP*,
-
-
-
-
-
-
-
-
-
PIM
-
-
-
-
-
-
-
-
-0.0181
PIM.2
-
-
-
-
-
-
-
-
_
pim,3
-
-
-
-
-
_
_
_
_
PIM*,
-
-
-
-
-
-
-
_
_
PIM.32
-
-0.2454
-0.3233
-
-
-0.2989
-
-0.2938
-
T6PIM
-
-
-0.3230
-
-
-0.3239
-
-0.2965
-
ACC
0.3419
-
-0.3229
-
-0.3408
-0.5314
-
-0.5454
0.5277
DACC
0.2437
-
-
-0.2741
-
-0.3572
-
-0.3957
-
POS
-
-0.3023
-0.7204
-0.4659
-0.5108
-0.8604
-
-0.8240
-
C
-
-
0.2926
-
-
0.3130
-
0.2877
-
Qi
-
-
-
-
-
-
-
-
-
ct3
-
-
-
-
-
-
-
-
-0.2578
Ct2-1
-
-
-
-
-
-
-
-
-
Ctf-2
-
-
-
-
-
-
-
-
-0.3905
Ct3-1
-
-
-
-
-
-
-
-
-
FLUD
0.2853
-
-0.5217
-0.3791
-0.4204
-0.7179
-
-0.7008
-
FLU, 2
-
-
-
-
-
-
-
-
-
FLUDC
-
-
-
-
-
-
-
-
-
FLUCa
-
-
-
-
-
-
-
-
-
FLU,3
-
-
-
-
-
0.3004
-
0.3544
-
FLUD.3
0.2909
-
-0.2992
-
-0.3700
-0.5325
-
-0.5146
_
FLUCa
-
-
-
-
-
-
-
-
-


APPENDIX I
TIME SERIES GEOMORPHIC VARIABLES


BIOGRAPHICAL SKETCH
Heidi Jane Lovelace Carter Lannon was bom in Sedgefield, England. She is the oldest of
four children, all of whom live on different continents. She lived in Wales, Lincolnshire, and
Gloucestershire before moving to Malta, where she received early schooling at Sacred Heart and
Stella Maris convents. Upon her return to England she attended Easton Royal Primary School.
She was sent to Clifton School for Girls in Bristol, where she was the swimming captain and
Deputy Head Girl. She attended the University of Ulster in Northern Ireland and received a BSc.
with Honours in Environmental Science, under Dr. Bill Carter.
Upon graduation Heidi received funding to attend the University of West Florida. She
worked with Dr. James P. Morgan and received a Master of Public Administration with an
emphasis in coastal zone management. Heidi worked as a civil servant in land use planning until
her decision to return to research under Dr. Joann Mossa at the University of Florida.
203


166
Table H-6. St Johns County Spearman Rank analyses, Dune Height (DH) and ) and dependent
variables at 0.05 significance
DH
DH
DH
DHa.,
DHa.,
DH,,.,
DH,0,
DHr
OR
UN
-
-
-
0.1840
-
0.2308
0.1894
0.1701
-
UN0
-
-
-
0.2529
-
0.2493
-
0.1673
-
UN,3
-
-
-
-
-
-
-
0.1737
-
UNq.,
-
-
-
0.1873
-
0.1799
-
-
-
UNu-2
-
-
-
-
-
-
-
-
-
UN,,.,
-
-
-
0.2353
0.0742
0.1756
-
-
0.1951
UH
-
-
-
-
-
-
-
-
-
UH,2
-
-
-
-
-
-
-
-
-
UH
-
-
-
-
-
-
-
-
-
uh,2.,
-
-
-
-
-
-
-
-
-
uh0.2
-
-
-
-
-
-
-
-
-
UH,,.,
-
-
-
-
-
-
-
-
0.2006
IMP,,
-0.1780
-
-
0.1968
-
-
-
0.1765
-
IMP,2
-0.1792
-
-
0.1902
0.2141
0.3157
0.2651
0.2793
-
IMP,,
-
-
-
-
0.2119
0.2594
0.2341
0.2236
-
IMP*,
-
-
-
-
0.2358
0.2493
0.1480
0.2305
-
IMP, ,.2
-
-
-
-
-
0.1856
-
-
-
IMP,,.,
-
-
-
-
0.1765
0.1765
-
0.1718
-
PIM
-
-
-
-
-
-
-
-
-
PIMo
-
-
-
-
-
0.1967
-
-
-
PIM
-
-
-
-
-
-
-
-
-
PIM,m
-
-
-
-
0.1786
0.1699
-
0.1838
-
PIM,m
-
-
-
-
-
-
-
-
0.1890
PIMa.,
-
-
-
-
-
-
-
-
-
ACC
0.1837
-
-
-0.1817
-0.1980
-
-
-
0.2122
DACC
-
-
0.3642
-
-
-
-
-
0.2337
POS
-
0.2374
0.2126
-
-
-
0.2064
-
-0.3997
c
-
-
-
-
-
0.1168
0.2247
0.0231
-
C
-
-
-
-
-
-
0.2269
-
-
Ca
-
-
-
-
-
0.0989
-
-
-
Ct2-1
-
-
-
-
-
-
-
-
-
Ct3-2
-
-
-
-
-
-
-
-
Ct3-1
-
-
-
-
-
-
-
-
-
FLUD
FLU, 2
0.3536
0.4350
0.4533
0.2272
-0.0416
0.1800
-0.1914
0.2616
-0.0488
-
FLUD,2
-
-
-
-
-
-
-
-
-
fluc,2
-0.1734
-0.1779
-
-
-
-
-
0.2082
-
FLU,,
-
-
-
-
-
0.1978
0.1487
0.0996
0.1908
FLUD
-
0.1772
0.2282
-
-
-
-0.1210
-0.0775
-
FLUCa
-0.1861
-0.1748
-0.1933
-
-
-
0.0722
0.1800
-


H-5. St Johns County Spearman Rank analyses, Beach Width (BW)) and dependent
variables at 0.05 significance 165
H-6. St Johns County Spearman Rank analyses, Dune Height (DH) and ) and dependent
variables at 0.05 significance 166
H-7. St Johns County Spearman Rank analyses, Monument to Dune Height (MDH) ) and
dependent variables at 0.05 significance 167
H-8. St Johns County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW) ) and dependent variables at 0.05 significance 168
H-9. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Beach Width (BW) and ) and dependent variables at 0.05
significance 169
H-10. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Dune Height (DH) ) and dependent variables at 0.05
significance 170
H-l 1. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Monument to Dune Height (MDH)) and dependent
variables at 0.05 significance 171
H-12. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach,
Monument 1 to 120), Maximum Dune Height to NGVD (DHBW)) at 0.05
significance 172
H-13. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140
to 198), Beach Width (BW)) and dependent variables at 0.05 significance 173
H-l4. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Dune Height (DH)) and dependent variables at 0.05 significance 174
H-l 5. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Monument to Dune Height (MDH)) and dependent variables at 0.05
significance 175
H-l6. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to
198), Maximum Dune Height to NGVD (DHBW)) and dependent variables at 0.05
significance 176
J-l. Hectares of commercial development (C ), St. Johns County, 1997 184
J-2. Future land use density (FLUD,i), Brevard County, 1972 185
J-3. Future land use units (FLU l3), Brevard County, 1997 185
J-4. Future land use units (FLU t3) Brevard County, 1997 186
J-5. Potential residential density, 1979 Comprehensive plan (FLUD,i) St. Johns County 186
xi


106
The actual value of MDH is a function of monument placement. The goal of monument
establishment was to ensure placement integrity over long time frames. The level of development
at the time of monument placement and subsequent replacement will determine location. For
example, placement location consistent with adjacent monuments may not be possible if the area
is already developed. Monument placement would then be more seaward and in the remaining
dunes, or landward adjacent to right-of-way. Subsequent to development, monument relocations
have caused historical data to be rendered obsolete where the replacement was sufficiently distant
from the original location (Appendix E). When the entire coastline of St. Johns County is
considered, the non-parametric Spearman Rank does not show any relationships between the
distance from the monument to maximum dune height and the dependent variables. When St.
Johns County is considered by geomorphic unit, the 2015 future land use (FLUo) has a positive
correlation with the time specific MDH. This is the only variable array that demonstrates the
relationship anticipated by Hypothesis lb and 2b. The density (FLUDo) however, is inconsistent
and positive on Anastasia Island and negative in northern St. Johns County. The analyses of this
variable suggest that the hypothesis is misspecified.
Maximum Height to NGVD (DHBW)
The maximum height to NGVD variable (DHBW) is a measure of beach width bounded
geomorphic variables, maximum height and position of NGVD. This variable is a combination of
the MDH and BW variables. In Brevard County the pattern of positive relationships between the
DHBWtot and human variables is not consistent with the DHBWf. As discussed earlier the use of
the absolute value of DHBWtot as an explanatory variable without the evaluation of the direction
and extent of beach width change is not possible. There are no significant relationships with
DHBWf in Brevard County. The relationships between future land use and DHBW in Brevard
County supports Hypotheses lb and Hypothesis 3. The wider the beach in 1986, the higher the
adopted total units, density and hectares of commercial development proposed for 2010.


192
BREVARD COUNTY COMPREHENSIVE PLANNING DIVISION, 1989. Brevard County,
Florida, Comprehensive Plan, Coastal Management Element. Brevard County, Florida, pp.
XVI-1-XVI-116.
BREVARD COUNTY PLANNING DEPARTMENT, 1972. An open space plan to 1995for
Brevard County. Brevard County, Florida, pp. XVI-l-XVI-116.
BROWN, A. C., and MCLACHLAN, A., 2002. Sandy shore ecosystems and the threats facing
them: Some predictions for the year 2025. Environmental Conservation, vol. 29, no.l, pp.
62-77.
BUCKINGHAM, W. T., and OLSEN, E. J., 1989. Sand source analyses for beach restoration,
Brevard County, Florida. Olsen and Associates, Jacksonville, FL. 83 pp.
BURT, J. E., & BARBER, G. E., 1996. Elementary Statistics for Geographers. The Guilford
Press, New York. 640 pp.
% BUSH, D. M., NEAL, W. J., YOUNG, R. S., and PILKEY, O. H., 1999. Utilization of
geoindicators for rapid assessment of coastal-hazard risk and mitigation. Ocean and
? Coastal Management, vol. 42, pp. 647-670.
BUTLER, D. R., and WALSH S. J., 1998. The application of remote sensing and geographic
information systems in the study of geomorphology: an introduction. Geomorphology, vol.
21, pp. 179-181.
BYRNES, M. R., and MATTESON M. W., 1995. Large-scale sediment transport patterns on the
continental shelf an influence on shoreline response: St Andrews Sound, Georgia to Nassau
Sound, Florida, USA. Marine Geology, vol. 126, pp. 19-43.
CARTER, L. J., 1974. The Florida Experience, Land and Water Policy in a Growth State. Johns
Hopkins University Press, Baltimore, 355 pp.
V CARTER, R. W. G., 1988. Coastal Environments: an Introduction to the Physical, Ecological
and Cultural Systems of Coastlines. Academic Press, New York, NY, 617 pp.
CARTER, R. W. G., and WOODROFFE, C. D., eds., 1994. Coastal Evolution, Late Quaternary
Shoreline Morphodynamics. University Press, Cambridge, 517 pp.
CHIU, T. Y., 1986. Coastal construction control line, review and reestablishment study for
Brevard County. Division of Beaches and Shores Resources Center, Florida State
University, Tallahassee, 43 pp.
CHORLEY, R. J., Editor, 1973. Directions in Geography, a Systems Approach. Methuen and Co.
London, 331 pp.
CLARK, J., 1976. The national interest in barrier islands and beaches: natural resource values in
Barrier islands and beaches. Technical proceedings of the 1976 Barrier Island Workshop,
Annapolis, Maryland, May 17-18, 1976, The Conservation Foundation, pp. 43-57.
CLARK, J. R., 1997. Coastal zone management for the new century. Ocean and Coastal
Management, vol. 37, no. 2, pp. 191-216.


Figure 5-5. Brevard County total units, 1972-1997, with potential units (UN,,, UNt2, UN0, FLU)
Sebastian Inlet


29
geographic area (Aubrey, 1993). For the past 3,000 years the rates have varied with some authors
favoring fluctuations while others recognize a steady rise in sea level (French et al., 1995; Pirkle
et al., 1970). It is generally accepted that sea level rise over the last 3,000 years has been between
1 and 5 mm annually (Davis, 1994a).
There are two theories that dominate research on barrier island formation (Field and
Duane, 1975). The coastal barrier beach of St. Johns County, north of St. Augustine inlet is a spit
extension. Gilbert (1885) and Fisher (1968) contend that spits, or thin strips of sediment, extend
from headlands in the direction of prevailing longshore drift. As sediment is pushed along the
coast by wave energy it elongates into spits that may eventually become detached if sediment
supply slows or if they are breached by storm waves. The detached spits will become vegetated
trapping additional sediment, building dune systems and stabilizing a barrier island. Anastasia
Island in St. Johns County is described as a barrier beach (FDEP, 2004a) and has several
alternative theories of origin. Otvos (1970) favors the notion of emergence of shoals from
underwater. There is some evidence that this occurs along the low energy Gulf Coast of Florida,
but is unlikely to be responsible in other cases, such as Anastasia Island or in Brevard County.
High wave energies along the eastern United States, for example, make it difficult to imagine
how this process would form barrier islands under those conditions.
Transgression, or drowning in-situ (Hoyt, 1967) hypothesizes that coastal ridges or sand
dunes formed, and were flooded as sea level rose after glacial melting. The ridges of sediment
then move onshore as sea level rises producing a lagoon behind the sediment. It seems unlikely
that any one theory is completely applicable for all conditions. The prevailing theory of barrier
island formation is multiple causality, or many causes that may be inter-related (Schwartz, 1971).
In parts of Florida, such as the Brevard County there are two series of barriers further suggesting
multiple causality. The earlier barrier is the Merritt Island system, which is fronted by the current
barrier islands and separated by Mosquito Lagoon, Banana River and Indian River Lagoon. This
series reflects two transgressions of sea level. However, the Brevard County barrier system is


XDHBWtl DHBWt2 DHBWt2 Monument Number
Maximum Height to NGVD (m)
x
co
a
x
CO
Q.
5
o
CD
Guana
h River State
P
Park
St Augustine Pass and
Anastasia State Park
B
OT > GO
(D C r-
0) o c
u- (/>
0)
3
Q.
i
-a
Z8I


107
Table 5-18. Lagged relationship between the 1986 distance from dune height to NGVD and
adopted future land use variables in Brevard County
Future Land Use variables (2010)
1986 Distance
from dune height
to NGVD
(DHBWtf)
Units (FLU t3)
0.3737
Density (FLUD^)
0.3907
Hectares of Commercial (FLUC ,3)
0.2774
95% confidence interval
In St. Johns County, neither the entire county, nor the geomorphic divisions, demonstrate
strong associations between the dependent variables and distance from dune height to NGVD
variable. This is consistent with the observations for the beach width (BW) and the distance from
the monument to maximum height (MDH) variables. However, northern St. Johns County
experienced a uniform decrease in the distance from the maximum height to NGVD in 1999
(Appendix I). The non-parametric analysis of this variable shows that there is a negative
relationship between the 1999 variable and the change in total units, unit density and adopted
future land use. The change in units and densities from 1972 to 1999 and 1986 to 1999, and the
proposed future land use, are inconsistent with the geomorphic condition, of width decrease and
Hypotheses la and 2a. This relationship would be expected in the case where the decrease in
distance from dune height to NGVD in 1999 was unanticipated.
Table 5-19. 1999 Distance from dune height to NGVD and change in human variables in St.
Johns County
Change in Human variables 1999 Distance
from dune height
to NGVD
(DHBWt3)
Units (UN t3.2) -0.3720
Units (UN t3_i) -0.3945
Density (UH 0.2) -0.4306
Density (UH m) -0.4148
Density (FLUDq) -0.2543
95% confidence interval
Long Term Change (LT)
In Brevard County there was a positive relationship between the long-term change (LT)
variable and the impervious (IMP), percent impervious area (PIM) and commercial development


CHAPTER 3
STUDY AREA
The two areas investigated are long inhabited and historically significant. Brevard County
was originally an important agricultural area and large producer of citrus crops. The coastal
development was initiated in the 1940s and boosted by the choice of the Cape Canaveral area for
the location of the National Aeronautic and Space Administration (NASA) facilities. The areas
are characterized by low-density development and incorporate a mix of single family homes,
multi-family condominia and commercial areas that were settled predominantly in the last thirty
to fifty years. Allen (1991) considers the Brevard County and adjacent areas the least intensively
studied in Florida. The northeast Florida region contains St. Augustine, the longest inhabited city
in the United States (Fernald and Purdum, 1992). Human habitation has continued from the rule
of the Spanish to the recently developed golf course communities of the Ponte Vedra area. Both
Brevard and St. Johns counties are located on the east coast of Florida, and although separated by
the false cape of the Cape Canaveral National seashore, a similar orientation to winds, waves and
tides exists from Nassau County to Jupiter Inlet. The two study areas are in this area and exist
with similar large-scale geomorphic conditions.
The story of South Floridas evolution from a crocodile and mosquito infested swamp to a
sybarites Shangri-la by the 1950s is a story of ambition, hype, and technological wizardry
pressed into service for the pleasure principle the saga of creating paradise from silt and
scratch. Lencek and Bosker, 1998, pp. 234.
In 1907 yellow fever was eradicated, providing a milestone for the colonization of Florida.
In 1927 the density of Florida was 1 person per 10 ha (Florida Department of Agriculture, 1928).
Large population centers at that time were Orlando, Jacksonville, Pensacola, Tampa and Miami.
The coast was considered a resource for the function of ports. Many of the settlements,
accessible only by water had origins as fishing villages. However, Tampa and Miami had their
26


5-6. St. Johns County total units, 1972 to 1999, with potential units (UN,i, UNg, UNt3, FLUt3). 97
6-1. Monument to maximum dune height hypotheses revision 126
D-l: Use of aerial photography and exclusion of areas unavailable for development 138
1-1. Brevard County Monument to highest point variations with trend, 1972-1997 (MDH,i, MDH
a, MDH) 178
1-2. Brevard County maximum height to NGVD with trend, 1972-1997 (DHBWtj, DHBWtl,
DHBW ) 179
1-3. Brevard County hectares of impervious area with trend, 1972-1997 (IMPtj, IMPtJ, IMP,i)180
1-4. St. Johns County Monument to highest point variations, 1972-1999 (MDHtj, MDH^, MDH
o) 181
1-5. St. Johns County maximum height to NGVD variations, 1972-1999 (DHBWt|, DHBW ,2,
DHBW) 182
1-6. St. Johns County impervious area variations, 1972-1999 (IMP,i, IMPt2, IMPt3) 183
xiv


145
Table E-2. Continued
Monument
Number
Date
Set
Northing Northing
(position 2)
NS
Change Easting Easting
(in m) (position 2)
1
EW
change
(in m)
2
40
Jan-79
2112517.35 2112517.35
0.00
388763.10 388763.10
0.00
41
Jan-79
2111481.57 2111481.57
0.00
388976.38 388976.38
0.00
42
Jun-72
2110457.78
389178.67
43
1995
Monument replaced > 3m from original
44
Jun-72
2108407.28
389591.89
45
Jun-72
2107393.56
389799.32
46
Jun-72
2106383.68
389992.19
47
Jan-79
2105379.92 2105379.92
0.00
390214.70 390214.70
0.00
48
Jan-79
2104374.91
390432.05
49
Jun-72
2103364.60
390640.87
50
Jun-72
2102343.64
390863.23
51
Jun-72
2101309.58
391028.73
52
Jun-72
2100261.02
391246.60
53
Jun-72
2099279.51
391422.34
54
Jun-72
2098258.55
391673.41
55
Jun-72
2097243.91
391873.84
56
Jun-72
2096230.22
392084.44
57
Jun-72
2095150.50
392298.10
58
Jun-72
2094155.21
392509.07
59
Jun-72
2093124.33
392740.47
60
Jun-72
2092077.59
392965.69
61
Jun-72
2091036.21
393185.75
62
Jun-72
2090014.32
393407.57
63
Jun-72
2088967.43
393626.06
64
Jun-72
2087935.98
393795.97
65
Jun-72
2086874.70
394012.75
66
Jun-72
2085847.39
394249.65
67
Jun-72
2084801.70
394430.91
68
Jun-72
2083775.51
394623.58
69
Jun-72
2082754.72
394837.02
70
Jan-79
Monument replaced > 3m from original
71
Jun-72
2080719.18
395188.19
72
Jun-72
2079709.52
395362.25
73
Jun-72
2078674.75
395565.70
74
Jun-72
2077642.82
395718.85
75
Jun-72
2076617.39
395911.18
76
Jun-72
2075588.83
396099.64
77
Jun-72
2074545.24
396311.07
78
Jan-79
2073501.24 2073501.24
0.00
396515.64 396515.64
0.00
79
Jun-72
2072415.14
396753.06


122
geomorphology on the land use control decision-making illustrating the hypothesis that future
land use plans were developed after consideration of actual geomorphological conditions.
The Brevard County adopted future land use density (FLUDt]) is a function of the 1972
dune height, long-term change and shoreline orientation. It may be concluded that higher
densities in 1972 were planned appropriately for long-term shoreline conditions, but in areas with
lower dunes. Similarly, the 1997 total proposed units (FLUo) is a function of the dune height
during that period (t3). The future land use is also a function of the 1972 distance from the
monument to maximum dune height. A separate 1997 total proposed units (FLU,3) variation is a
function of lower 1997 dune heights in conjunction with the 1986 beach width, weighted by the
road location. From a development perspective lower dunes are more desirable for enhanced
coastal visibility. However, lack of dune protection from erosion, waves and storms make areas
with lower dunes less geomorphically appropriate. Table 6-1 shows the St. Johns County non-
parametric associations between future land use and beach width. The density established in the
1972 future land use plan also has a functional relationship with multiple variables. Higher
densities in 1972 were planned in areas with wider beaches, oriented north-south and closer to
access.
Dynamic Geomorphology and Dependent Variables
The use of dynamic geomorphology indicators to evaluate the suitability of the coast for
development was successful if simple correlations between variables were considered. However,
when multivariate analyses were made, the observed numbers of units, density, impervious area,
and hectares of commercial development did not have significant interactions with the
geomorphology. While the dynamic geomorphology was not a determinant for the time specific
human variables, it was significant in future land use plans in both Brevard and St. Johns County.
The assumption that future land use outcomes are the result of the dynamic characteristics
of the physical environment is illustrated in Brevard County. The long-term change and beach
width weighed by the location of roads and presence and absence of coastal protection structures.


128
Table 6-3. Pro
posed development suitability
matrix
Dune Height
Beach Width
High
Low
Wide
Narrow
Long-term
Accretion
1
2
i
2
Long-term
Erosion
2
3
2
3
l=Most appropriate for development, 2=Moderate appropriateness,
3=Least appropriate for development
In States with developed coastal management programs such as North Carolina and New
Jersey coastal profile data area also available, although not at the detail or consistency of the data
in Florida. The availability of LIDAR technology and data enables the profile characteristics
used in this research to be determined. Historical data used in this research can be combined with
LIDAR source data to expand the time series and be used as a tool for land use planners.
Potentially valuable data to the extension of this research includes the use of property appraisal
data at the county level. Each county is required to collect data on building type, construction,
effective year built, and value, for taxation purposes. Building permit activity and type of
construction data can be used to expand the human variables. Spatial presentation of residuals
from the regression analyses is a technique that could be incorporated in this research to
demonstrate the effectiveness of the model at each point along the coast. This technique would
visually demonstrate areas unsuitable for development. The use of 9-hectare sample areas was
defined as the most appropriate based on the 300m separation of data points. Further research
with varied sample area sizes could test the suitability of the 9-hectare area. The potential for
dummy variables can be expanded, and a potential dummy variable that accounts for
development potential is vacant land. Similarly, the potential for redevelopment could be
controlled with a dummy variable to evaluate the influence of newly adopted planning
mechanisms such as tax increment incentives. These extensions of this research will be valuable
in the evaluation of feedback loops occurring between human and physical variables. It is
anticipated that the impact of the physical features (such as dune height) on human variables


112
interaction with other variables more appropriately than in the non-parametric statistical analyses.
A stepwise regression of dependent variables was performed to identify potential relevant
variables. Multiple regression analyses were performed for Brevard County sample areas, the
entire St. Johns County data and the St. Johns County data by geomorphic area. The regression
results are presented by hypothesis and a summary of the regression results is provided for each
hypothesis (Appendix J).
Hypothesis 1: Local Geomorphology and Human Variables at each Time Interval
Hypothesis la suggests that the local geomorphology influences the human variables at that time
(Conway and Nordstrom, 2003; McMichael, 1977; Miller, 1980). The total number of hectares of
commercial development measured in 1999 for the entire coastline of St Johns County is the only
dependent variable that has a functional relationship with actual geomorphic variables
St. Johns County, Entire Coastline-1999 Hectares of Commercial Development (C^)
C = -7.674 0.022 BW,,., 0.347 DH0 + 0.056 OR + 0.001 (DHBW t3)3
(N=121, R2 = 0.400)
Cg = 1999 Commercial Area (ha)
BW t3_i = Change in Distance from NGVD to Maximum Dune Height 1972 to 1999 (m)
DH,3 = 1999 Maximum Dune Height (m)
OR = Shoreline Orientation (degrees from north)
(DHBW ,3)3= Cubed Value of 1999 Distance from NGVD to Maximum Dune Height (m)
Higher hectares of commercial activity in St. Johns County area explained by lower change
in beach width from 1972 to 1999, lower dunes in 1999 and a wider beach (DHBW) in 1999.
The shoreline orientation north-south (OR of 180) rather than northwest-southeast (OR of less
than 180) is associated with higher levels of commercial development. Geomorphically higher
levels of development, denoted by the hectares of commercial development, would be expected to
have a positive relationship with the beach width (DHBW), or be higher where the beach was
wider, and be higher where the change in beach width was lower. As was noted in the non-
parametric analyses, higher intensity development occurs where dunes are smaller. Potential
hypotheses for this result include the preference for development in areas with smaller dunes for


27
origins in the export of citrus products. St. Augustine was a minor port. The channel and harbor
in St. Augustine were reported to be 1.8 to 2.4 m deep. Cape Canaveral was predicted to become
a port of importance because of rail connections, the protection afforded and the piers and
availability of land for terminals. Agriculture, forestry and expansion of the cement and fruit
exporting industries were identified as the goals for the future of Florida (Florida Department of
Agriculture, 1928).
The main attractions of Florida were described as climate and scenery (Florida Department
of Agriculture, 1928). Tourism was identified in terms of hunting and fishing, ironically only for
men. One of the unique features of the state was identified as the beaches. They were considered
unique because they contained rare metallic minerals. The fact that beaches were flat and hard
and suitable for vehicular traffic was recognized as a novelty. The indication that a small number
of coastal areas had made preparations for tourism at in the 1920s was illustrated through the
increase in hotels and rooming houses and the number of golf courses. It was recognized that
winter visitors will come here, and in gradually increasing numbers (Florida Department of
Agriculture, 1928, pp. 161). In contrast, in 1981 eighty six percent of tourists visiting Florida
participated in coastal-related activities (South Florida Regional Planning Council, 1989).
Geomorphological Characteristics of the Florida Coast and Study Area
Beaches and sand dunes are vital for tourism and recreation in Florida. These areas are
also vital for dissipation of wave energy, protection from coastal storms and storage of sediments.
The coastline of Florida varies from narrow sandy spits to coral reefs, and from remote wildlife
sanctuaries to thriving urban areas. The 1,900 km of coastline in Florida is the longest in the
coterminous United States. Floridas wide continental shelf, sediment supply and wave energy
contribute to a coastline fringed with barrier islands and tidal inlets. The area inland of the barrier
island, is composed of tidal lagoons, linked together, and deepened by dredging to form a
navigable route, the intracoastal waterway, around the entire state. There are 1,250 km of sandy


19
100-year storm and anchored to a pile foundation. Excavation seaward of the CCCL is not
recommended but may be permitted.
Table 2-4. Coastal and
growth management legislation that impacts the Florida coast
Year
Name
Legislation
1968 (Federal)
The National Flood Insurance
Act
Insures structures from hazards with
backing of the Federal Government
1972 (State)
The Coastal Construction
Control Line (CCCL)
Established to reduce the potential for
structural damage and beach erosion
1972 (State)
State Comprehensive
Planning Act
First Statewide growth management
legislation
1972 (Federal)
Coastal Zone Management
Act
Establishment of national coastal
management coordination and
funding for State coastal program
1974 (Federal)
The Disaster Relief Act
Federal disaster assistance
administered by the Federal
Emergency Management Agency.
1978 (State)
The Florida Coastal Zone
Management Act
Resolution of conflicts between
agencies concerning coastal land and
water
1982 (Federal)
The Coastal Barrier
Resources Act (CBRA)
Prohibits federal assistance on
designated undeveloped coastal
barriers that comprise the Coastal
Barrier Resource System
1985 (State)
The Florida Coastal Zone
Protection Act
Building regulations in coastal areas.
Structures must be designed to
withstand 100-year storm wind
speeds and erosion impacts.
1985 (State)
Local Government Comp.
Planning and Land
Development Regulation Act
Requires Florida cities and counties to
develop comprehensive plans and
land development regulations
1991 (State)
Florida Beach and Shore
Preservation Act
Requires all construction,
reconstruction or shoreline protection
to have a coastal construction permit
from DEP with a 15.25m setback line
from mean high water, the average
high of high waters over 18 years.
1999 (State)
The Coastal Construction
Control Line (CCCL)
Authority of individual counties to
permit structures and erosion controls
Sources: Bellomo et al., 1999; South Florida Regional Planning Council, 1989; Vernberg et al.,
1996; Von der Osten, 1993
As noted in Table 2-4 the Coastal Barrier Resources Act (CBRA) prohibits federal
assistance on designated undeveloped coastal barriers that comprise the Coastal Barrier Resource
System. Private property rights are still in effect and development can occur, but without Federal
subsidies for transportation networks, and flood insurance. Existing jetties and channels, road


165
Table H-5. St Johns County Spearman Rank analyses, Beach Width (BW)) and dependent
variables at 0.05 significance
BW
BWa
BWa
BWa.,
BWa.2
BWa.,
BW*,
BWf
LT
UN
0.2060
0.3999
-
-
-
0.1840
0.2060
0.3999
0.2608
UNa
0.1838
0.2750
-0.1189
-0.0557
0.0725
0.2529
0.1838
0.2750
0.1900
UNU
0.2324
0.3092
0.2500
0.2620
-
-
0.2873
0.1892
-
unq.,
-
-
-
-
-
-
-
-
-
UNa.2
-
-
-
-
-
-
-
-
-
UN,3.,
-
-
-
-
-
-
-
-
-
UH
-
0.2239
0.2066
0.2029
-
0.2192
-
0.2113
-
UHa
-
-
-
-
-
-
-
-
-
UHa
-
-
-
-
-
-
-
-
-
UHa.,
-
-
-
-
-
-
-
-
-
UH.3.2
-
-
-0.2085
-0.1378
-
-0.1751
-
-
-
UHa.,
-
-
-0.1994
-
-
-
-
-
-
IMP,,
0.1835
0.3345
0.3985
0.3097
0.2804
0.4247
-
0.4125
0.2528
IMPa
0.3873
0.4597
0.5115
0.3817
0.1964
0.4111
0.3383
0.3996
0.3249
IMPa
0.4251
0.4818
0.4761
0.3735
0.1226
0.3972
0.3896
0.3531
0.2786
IMPq.i
0.4174
0.3883
0.3807
0.3007
-
-
0.3121
0.2463
0.3551
IMPa.2
0.2022
0.1749
-
-
-
0.1735
-
-
-
IMP0.,
0.4267
0.3816
0.3538
0.2769
-
0.2851
0.3188
0.2092
0.2536
PIM
-
0.2350
0.2323
0.2046
-
0.2345
-
0.2280
-
PIM,2
0.2668
0.3243
0.3291
0.2641
-
0.2388
0.2385
0.2026
0.2631
PIMa
0.3403
0.3661
0.3162
0.2624
-
0.2217
0.3039
-
0.2291
PIMC.,
0.3063
0.2812
0.2456
0.2166
-
-
-
-
-
PIMa.2
-
-
-
-
-
-
-
-
-
PIMa_,
0.3478
0.2842
0.2203
0.1936
-
-
-
-
-
ACC
-0.4153
-0.4123
-0.4938
-0.2703
-0.3424
-0.4327
-0.2921
-0.4396
-
DACC
0.1909
-
-
-
-0.1781
-0.1829
-
-0.2008
-
POS
0.4149
0.2175
0.2154
-
0.2062
-
-
-
0.2296
c
0.1789
-
-
0.1799
0.2101
-
0.1965
-
cQ
0.3524
0.3608
0.3945
0.2593
-
-
0.3044
0.2484
-
Ca
0.3859
0.3753
0.3657
0.2655
-
0.2611
0.2878
0.2167
0.1901
Ct2-1
0.3775
0.3816
0.3703
0.2736
-
0.2402
-
0.2274
-
Ct3-2
-
-
-
-
-
-
-
-
-
03-1
-
-
-
-
-
0.2143
0.2510
0.1842
0.1720
FLUD
0.4366
0.1713
-
-
-
-0.1719
0.1759
-
0.1966
FLUC
0.3456
0.5516
0.5311
0.5649
-
0.5641
0.4264
0.5510
0.4314
FLUDa
0.2363
0.3814
0.2995
0.4159
-
0.3304
0.2995
0.2600
0.3748
FLUCa
-
-
-
-
-
-
-
-
-
FLUa
0.3400
0.3739
0.3166
0.3416
-0.0973
0.2559
0.3505
0.2433
0.2175
FLUDa
0.2737
0.2320
-
0.1778
-0.3726
-
0.2501
-
0.1958
FLUCa
-
-
-
-
-
-
-
-


Copyright 2005
by
Heidi J. L. Lannon


142
Table E-l. Continued
Monument Date
Number Set
Northing Northing
(position 2)
NS Change
(in m) 1
: Easting Easting
(position 2)
EW
change
(in m) 2
128
Aug-72
1361873.00
641084.60
129
Jan-80
1360881.00 1360881.00
0.00
641479.00641485.00
-1.83
130
Jun-85
1359937.00 1359935.00
0.61
641763.00641753.20
2.99
131
Aug-97
1359104.00 1359096.00
2.44
642111.00642132.90
-6.68
132
Aug-72
1358374.00
642423.50
133
1993
1357367.00 1357367.00
0.00
642818.00642818.00
0.00
134
Jun-85
1356417.00 1356417.00
0.00
643230.70643230.70
0.00
135
Jun-85
1355516.00 1355516.00
0.00
643581.30643581.30
0.00
136
1993
Monument replaced > 3m
from original
137
Jan-80
Monument replaced > 3m
from original
138
Aug-97
1352802.00 1352811.00
-2.74
644652.50644741.60
-27.16
139
Aug-72
1351748.00
645011.00
140
Aug-72
1351077.00
645378.00
141
Aug-72
1350124.00
645745.50
142
Aug-72
1349406.00
646044.00
143
Aug-72
1348492.00
646410.90
144
Jun-85
Monument replaced > 3m
from original
145
Aug-97
Monument replaced > 3m
from original
146
Aug-97
Monument replaced > 3m
from original
147
Jan-80
1344983.00 1344983.00
0.00
647893.40647893.40
0.00
148
Aug-72
1344095.00
648282.50
149
Aug-97
Monument replaced > 3m
from original
150
Aug-97
Monument replaced > 3m
from original
151
Aug-97
Monument replaced > 3m
from original
152
Aug-97
Monument replaced > 3m
from original
153
Aug-97
Monument replaced > 3m
from original
154
Aug-72
1338832.00
650508.00
155
Aug-72
1337608.00
651052.00
156
Aug-72
1337148.00
651274.50
157
Jan-80
1336077.00 1336077.00
0.00
651732.00651732.00
0.00
158
Aug-72
1335353.00
652034.40
159
Jan-80
1334497.00 1334497.00
0.00
652399.00652399.00
0.00
160
Aug-72
1333463.00
652850.50
161
Aug-72
1332714.00
653298.50
162
Aug-72
1332110.00
653470.00
163
Aug-72
1331027.00
654042.00
164
Aug-72
1330330.00
654410.50
165
Aug-97
1329464.00 1329461.00
0.91
654860.00655000.40
-42.79
166
Aug-72
1328338.00
655854.50
167
Aug-97
Monument replaced > 3m
from original
168
Aug-97
Monument replaced > 3m
from original
169
Jun-85
1325623.00 1325623.00
0.00
656480.50656480.50
0.00
170
Jan-80
1324727.00 1324727.00
0.00
656970.00656967.50
0.76
171
Jan-80
1323888.00 1323884.00
1.22
657359.00657355.50
1.07
172
Aug-72
1322966.00
657757.00


202
WALSH, S. J., BUTLER, D. R., and MALANSON, G. P., 1998. An overview of scale, pattern,
process relationships in geomorphology: a remote sensing and GIS perspective.
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WANG, H., and LIN, L., 1992. Sebastian Inlet model studies. In Florida Shore & Beach
Preservation Association, New directions in beach management, Proceedings of the 12th
Annual National Conference on Beach Preservation Technology, February 12-14, 1992,
Florida Shore & Beach Preservation Association, Tallahassee, FL., 468 pp.
WILLIAMS, J. M., and DUEDALL, I. W., 1997. Florida Hurricanes and Tropical Storms. The
University Press of Florida, Gainesville, Florida, 146 pp.
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LIST OF REFERENCES
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Singapore Journal of Tropical Geography, vol. 1, no.2, pp. 1-10.
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AUBREY, D. G., 1993. Coastal erosions influencing factors include development, dams, wells
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BALSILLIE, J. H., 1985. Establishment of methodology for Florida growth management: 30 year
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BEATLEY, T., BROWER, D. J., and SCHWAB, A. K., 1994. An Introduction to Coastal Zone
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BODGE, K. R., 1989. Wave refraction and littoral drift along Brevard County, Florida. Prepared
for the Board of County Commissioners Brevard County, FL. 53 pp.
BODGE, K. R., 1992. Inopportune timing of oceanfront structures. In Florida Shore & Beach
Preservation Association, New directions in Beach Management, Proceedings of the 12th
Annual National Conference on Beach Preservation Technology, February 12-14, 1992,
Florida Shore & Beach Preservation Association, Tallahassee, FL. 468 pp.
BODGE, K. R., and SAVAGE, R. J., 1989. Economic Analysis of Beach Restoration along
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191


47
baseline for the FDEP surveys and is consistent throughout the two study areas and the entire
study period.
Table 4-1. Geomorphic data availability by study area
Study Area
Data Availability
Brevard County
1972, 1983-, 1986, 1993-, 1997
St. Johns County
1972, 1984-, 1986, 1993-,1999
~ Data are incomplete or only available every 3 monuments
Table 4-2. Independent (geomorphic) variable details
Independent Variables
Name
Beach Width Index
BW
Maximum Dune Height
DH
Monument to Maximum Dune Height
MDH
Beach Width to Maximum Height
DHBW
Long-term Shoreline Change
LT
Geographic Location
POS
Orientation
OR
Distance to Access Point
ACC
Distance and Direction to Access Point
DACC
Presence of Structures
SW
Renourishment
RN
Dune Renourishment (Brevard County
RND
only)
Temporal Scale
Name
Actual
1972
ti
1986
t2
1999 (1997 Brevard)
t3
Dvnamic
Change from 1972 to 1986
t2-l
Change from 1986 to 1999(1997 Brevard)
t3-2
Change from 1972 to 1986(1997 Brevard)
t3-l
Total Change (Absolute Value)
tot
Change Factor (Ratio Net to Total)
f
Appendix A contains source and measurement data for each variable.
The monument is a fixed position on the profile. The monument location varies in certain
instances. When a monument is lost it is replaced by the State of Florida. If the monument was
lost as a result of storm activity or erosion the replacement may be in a new location. The beach
width index from the monument to the NGVD is a measure of relative beach width, and is
measured in meters. The beach width index variable illustrates the changes in width over time.


125
time was low. Potential higher numbers of units are, therefore, planned in more suitable areas
with wider beaches and low levels of dune change. This pattern of variables is consistent
throughout all hypotheses, with the dune height influencing Brevard County dependent variables
and the beach width being more important in St. Johns County.
Inaccurate Assumptions and Hypotheses Misspecifications
The statistical analyses compiled in this research produce a determination of factors that
influence development. There are instances where geomorphological appropriateness may not be
consistent with the development perspective. An example of this anomaly is the dune height
variable. Areas more geomorphically appropriate for higher density and intensity of development
would be those with higher dunes. Higher dunes provide storage areas for sediment and
protection against erosion and storm damage. However, the same areas may be considered less
desirable for development because high dunes may detract from access and coastal vistas. In both
jurisdictions the negative relationship between human variables and dune height was noted. This
conclusion is not characterized as a hypothesis misspeciflcation, but as an unforeseen result. The
results of the analyses are counterintuitive to practical geomorphological considerations for
development. However, the preference for development in areas with lower dunes, while
potential geomorphic folly, is a conclusion that is not unanticipated.
The distance from the monument to maximum dune height was selected as a variable to
provide a measure of the impact of the dune field Allen (1991, pp. 6) used a similar measure in
research at Canaveral National Seashore and stated an accurate indicator of the true coastal
trend is that given by dune Crestline changes. However, the explanatory power afforded by
this variable is contrary to the hypotheses proposed in Chapter 2. Revised hypotheses for the
distance from the monument to maximum dune height (MDH) variable are proposed. If the
highest point on the profile to the monument is an indicator that the highest dune is furthest
inland, a series of dunes seaward of this point would provide a buffer and sediment supply for
storm activities. A low change in the position compared to the monument was hypothesized to be


87
In St. Johns County, dune height variations are more pronounced than in Brevard County.
Dunes are higher on average and increase in average maximum height from 5.5m in 1972 to 5.8m
in 1999. Maximum dune heights are lowest in Ponte Vedra and at St. Augustine Beach.
Historically the dunes in Ponte Vedra were removed to ensure adequate views of the ocean.
Maximum dune heights increase from 1972 to 1999. From monument 35 to 121, dune heights
have been stable. The low dune heights at St. Augustine Beach are a function of erosion and
placement of rock revetments at the coast. This area and the area to the north in Anastasia State
Park have been subject to overwash and dunes are limited. Although dune height varies spatially,
in northern St. Johns County, temporally there has been very little change in maximum dune
height. The positive value of 0.1 for the Dune Height Factor (DHf), which is a measure of the
total over net change, shows that an overall increase in height, but the closer this factor is to zero
the larger the difference in net and total changes demonstrating dynamic change over time. The
DH in northern St. Johns County and Anastasia Island are very similar, increasing from 1972 to
1999, but Anastasia Island is normally distributed. Northern St. Johns County experienced a
large increase from 1986 to 1999, whereas Anastasia Island dune height increases are consistent
in both 1972 to 1986 and 1986 to 1999.
Monument to Maximum Dune Height (MDH)
The descriptive statistics and spatial display for this variable are presented in Appendix G
and Appendix I. Actual MDH values are not necessarily an indicator of a wide or narrow dune
field. A high MDH value may represent a wide stretch of dunes, or a monument placed further
inland. However, changes between time periods are a measure of the geomorphic stability of the
dunes in relation to a stationary point, the monument. An increase in the MDH over time
represents a seaward movement of the maximum dune height. Without an indication of beach
width the seaward movement of maximum height is assumed to indicate erosion, because the
highest point on the profile is now more seaward. The landward movement of the MDH is
hypothesized as indicating a prograding dune field. This variable is important in the evaluation of


30
also unusual near the False Cape area, where a clear inflection point occurs. The barriers in the
Brevard County areas have been classified as perched by Tanner (1960). That means that the
sediment that is at the surface covers an original barrier from a previous geologic age.
Sediments
Coastal sediments in Florida are composed of quartz and calcium carbonate. The calcium
carbonate is from shell fragments and oolite, or granular limestone grains (Johnson and Barbour,
1990). On the Atlantic Coast of Florida the amount of shell fragments, derived from coquina, or
rock formed from shells, increases towards south Florida. The calcium carbonate volume
increases from less than 10 percent in the Jacksonville area, to over 40 percent in Miami (Giles
and Pilkey, 1965). However, the areas of central Atlantic Florida have also been found to have
sediment variations. Sediment in Brevard County is described as having a composite mean grain
size between 0.13 to 0.25mm, and 0.19 mm on average (U. S. Army Corps of Engineers, 1992).
Stapor and May (1982) found that Jacksonville Beach, Anastasia Island, and False Cape, in
Brevard County are composed of fine grained quartz sand, compared to the coarser sand with
larger amounts of shell material in the intervening areas (Buckingham and Olsen, 1989). Foster
et al. (2000) describe the sediment north of St. Augustine Inlet and south of Matanzas Inlet as
crushed shell hash, the source of which is nearshore coquina rock. The source of the
noncalcareous coastal sediments is from rivers draining areas above the coastal plain, not local
rivers (Giles and Pilkey, 1965). Swift (1975) has determined that the sediments were deposited
offshore and were transformed during sea level rise, forming the origins of todays beaches and
barrier islands. Sediments come from the erosion of coastal deposits in Virginia and North
Carolina (Tanner, 1960).
Dunes
Dunes are elevated areas of unconsolidated sediment that are formed and maintained by
wind transportation of sand. Dunes need four criteria to form and flourish: a sediment source;
strong onshore winds; a gentle beach gradient; and, low humidity (which Florida does not


176
-0.2979
-0.2954
-0.3154
Table H-16. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to 198),
Maximum Dune Height to NGVD (DHBW)) and dependent variables at 0.05
significance
DHBW,| DHBW,2 DHBW,3 DHBW*, DHBW,3.2 DHBWa-i DHBWm DHBWf
UN - - - -
UNC ... -
UN0 - - - -
UN*, ----- - -
UNa.2 ..... -
UN*, -----
UH - 0.3208 -
UHo ...
UHo ...
UH*, -----
UHo-2 -----
UHo-i ----- 0.3100
IMP,, - 0.3128 -
IMPC .....
IMPU -----
IMP*, -----
IMP,j.2 - 0.3047 -
IMP*, -----
PIM -----
PIMC .....
PIMa -----
PIM*, -----
PIMa-2 -----
PIMa., -----
ACC -----
DACC -----
POS - - 0.3471
C - .
Ca .... .
Co .... .
Ca-i ... .
Ct3-2 - - -
Ca-i - .
FLUD 0.5151 0.4742 -
FLU0 -----
FLUD.2 -----
FLUQ, -----
FLUa
FLUDa
FLUCa
0.4096
0.3578 0.4196
0.4477 0.4337
-0.4607 -


APPENDIX J: REGRESSION RESULTS, BREVARD AND ST. JOHNS COUNTY
Hypothesis 1: Local geomorphology at each time interval impacts human variables at the
same interval
Hypothesis la: The local geomorphology influences the actual development. (Conway
and Nordstrom, 2003; McMichael, 1977; Miller, 1980).
Table J-l. Hectares of commercial development (Ct3), St. Johns County, 1997
Ho n Tntarpont O \/anokla O \/on'nkla O
Dep.
Variable
R3
Intercept
Pi
Variable
P2
Variable
P3
Variable
Ca
N=121
0.400
-7.674
-0.022
BWfl.,
-0.347
DHU
0.056
OR
P4
Variable
0.001
(DHBW
a)3
Dependent Variable C,3
Adjusted R-Squared 0.4001
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
-7.673884
3.727084
-2.0590
0.041719
Reject Ho
0.532736
BWa,
-2.170779E-02
7.487879E-03
-2.8991
0.004471
Reject Ho
0.819962
DH ,3
-0.346913
9.058836E-02
-3.8296
0.000208
Reject Ho
0.966967
OR
5.626662E-02
2.147139E-02
2.6205
0.009944
Reject Ho
0.738595
(DHBWt3)3
1.493633E-06
2.071765E-07
7.2095
0.000000
Reject Ho
1.000000
T-Critical
1.980448
F-Ratio
21.1738
0.000000
1.000000
N=121
Ct3 = 1999 Commercial Area (hectares)
BW t3_i = Change in Distance from NGVD to Maximum Dune Height 1972 to 1999 (m)
DH t3 = 1999 Maximum Dune Height (m)
OR = Shoreline Orientation (degrees from north)
(DHBW g)3= Cubed Value of 1999 Distance from NGVD to Maximum Dune Height (m)
Hypothesis lb: The local geomorphology influences the land use control decision
making. (Hails, 1977).
184


88
the impact of impervious areas and structures on the function of the dunes. In Brevard County,
similar to dune height, the highest variation occurs adjacent to Cocoa Beach and Satellite Beach.
The average MDH decreases from 1972 to 1997, with value of-2.1m, showing the maximum
height moved closer to the monument, or inland. The MDHt3.i moved seaward of the monument.
The maximum dune height has moved seaward in northern St. Johns County, and on
Anastasia Island, indicated by a reduction in the MDH, or distance from the monument to the
position of the maximum dune height (Appendix I). Between monuments 60 and 90 the dune
field may be described as stable, with small changes between 1972 and 1986, 1986 and 1999, and
1972 and 1999. Monuments 90 to 121 have migrated landward with lower MDH from 1972 to
1999. Similarly in Summer Haven the maximum dune height has moved inland, possibly due to
aggressive sand fencing by property owners noted by Foster (2002). The average MDH increases
countywide as the maximum dune height moves seaward, although the total seaward movement is
only 2.3m in northern St. Johns County, compared to 16.35m on Anastasia Island.
Maximum Dune Height to NGVD (DHBW)
The descriptive statistics and spatial display for this variable are presented in Appendix G
and Appendix I. The maximum dune height to NGVD is a measure of beach width bounded by
geomorphic characteristics. This variable is sensitive to the location of the maximum dune height
and dune renourishment or sand fencing will impact the resulting DHBW value. In Brevard
County this index shows that the wider and more dynamic areas are adjacent to Cocoa Beach.
Satellite Beach is also more dynamic than adjacent areas. The profiles with large changes from
1972 to 1997 are also those with the largest increase in 1986. South of Indiatlantic, with the
exception of a few areas that experienced extreme beach width increases in conjunction with
landward movements of the maximum dune height, the area has seen only small changes. The
range increase over time (Appendix G) indicates increasing extremes with areas changing more
than in previous time periods. The pattern of beach width decrease from 1986 to 1997 (BW^) is
also reflected in this variable, showing the beach width decreased in conjunction with the seaward


21
management could be extended to coastal issues. Coordination of multi-jurisdictional coastal
issues, or the designation under the Areas of Critical State Concern legislation (Tin, 1976) can be
facilitated at the state level.
Land use authority in Florida is delegated to the County and municipal level and as a
consequence interactions between development and the coast occur at the local level. In this way
the use of county jurisdictional boundaries makes sense for the human variables. Although
much federal and state legislation has been enacted to assist the management and regulation of
coastal development and redevelopment, local government regulatory tools and programs provide
the most significant opportunities... (South Florida Regional Planning Council, 1989, pp. 65).
In Florida, homestead exemption, which exempts the first $25,000 of value from ad
valorem taxation, is available for primary residences. In rare cases, such as mobile homes on
small lots with taxable values of less than $25,000, there is no assessment of taxes. In the past,
before appreciation of the value of coastal property this form of development was prevalent to
northeast Florida. In St. Johns County the changes in land use from the 1970s to the 1980s
shows several examples of trailer park conversions to large commercial endeavors. In 1997 the
Save Our Homes Amendment was enacted. This amendment has important attributes that impact
residential development, particularly in coastal areas. The constitution of the State of Florida was
amended after residents in southwest Florida objected to rapid property tax increases as coastal
property appreciated. Statewide, property that is owner occupied and with residents claiming a
homestead exemption, is limited to 3 percent increases in ad valorem taxes annually. When
property transactions occur the residual property taxes are levied. This has made analyses of
taxable value as an indicator of property appreciation inappropriate.
Land Use Planning in Florida
Settlement patterns are influenced by the market and government regulations, such as
zoning, transportation and tax policy. Growth management legislation throughout the country
struggles with the degree to which public policy should restrict the free market through land use


46
Actual Geomorphology Variables
The coastline of Florida has been surveyed by the Division of Beaches and Shores, State
Department of Environmental Protection (FDEP) since the early 1970s (Clark, 1999).
Monuments are situated along the coastal counties of Florida approximately every 300 m and are
typically set within the dunes. The FDEP collects data for a variety of reasons, such as to assess
local conditions, evaluate the coastal construction control line and for special purposes.
Complete data sets are available in each decade of the research (Table 4.1). Partial data sets for
counties are collected for post-storm evaluation, and pre- and post-construction. Data from
contracted surveys are also included on the FDEP website, but are not used in this research. An
example of the format of the raw data is shown in Appendix C.
Beach Width Index (BW)
Beach width variations reflect areas along a barrier island that are more dynamic, those that erode
and recover more than adjacent areas. This variable has been used by Davidson-Arnott (1988)
and Gares (1988). Beach width is an important variable in the selection of locations for
development. During Hurricane Hugo beaches of over 30 m wide afforded greater protection to
structures, and 84 percent of coastal structures that were destroyed had a beach width of 15 m or
less (Bush et al., 1999). The FDEP beach profile data are modified to represent beach width
(BW). The distance from the survey monument to the water (using the National Geodetic
Vertical Datum, NGVD) is calculated. NGVD is defined as the National Geodetic Vertical
Datum, as established by the National Ocean Survey in Chapter 62 of the Florida Administrative
Code1. NGVD provides a suitable zero point for this research because NGVD is used as a
1 In the United States 75,159 km of leveling was standardized in 1929. A fixed elevation was
assigned to 26 points on a network that defined elevations in the United States and Canada as the
mean sea level datum of 1929. This was commonly referred to as mean sea level and was
confused with mean water level until 1979. It was renamed the National Geodetic Vertical
Datum of 1929.


42
shoreline protection structures. St. Johns County contains two areas with shore-parallel structures
in Ponte Vedra and St. Augustine Beach (St. Johns County, 2002). At St. Augustine Beach, piles
of rock stabilize the point at which Highway A1A turns west (monument 141). Previously
Highway A1A continued further north on Anastasia Island until it was threatened by erosion
during hurricane Dora. There are no extensive bulkheads or seawalls from Ponte Vedra to
Vilano Beach, although individual homeowners have made small-scale private attempts (St.
Johns County, 2002).
Renourishment of the Shoreface
Brevard County has had several renourishment projects during the study period, which are
shown in the Table 3-2. Brevard County has 115.2 km of coastline (including the Cape
Canaveral National Seashore, that is not part of this research) and 16.7 km has been renourished
(Esteves, 1997). There are also instances where individual homeowners have attempted informal
and unpermitted shoreline protection methods. Localized small-scale protection, sand fencing or
netting, and planting of dune vegetation are not considered coastal structures and not included in
this variable.
Table 3-2. Renourishment projects in Brevard County during 1972 to 1997 study period
Monument/
Location
Alongshore
Distance (km)
Date
Volume (m3)
(Not in research area)
Unknown
1972
152,900
1 to 33
Approx 3
1974-75
2,075,889
119-134
Approx 4.5
1980-81
412,938
50-76
Approx 6
1985
550,512
City of Cocoa Beach
Unknown
1986
30,580
City of Cape
Canaveral/Cocoa Beach
Unknown
1992
99,398
City of Cape
Canaveral/Cocoa Beach
Unknown
1993
152,920
City of Cape
Canaveral/Cocoa Beach
Unknown
1995
567,333
Source: Brevard County Comprehensive Plan, 1988, Sudar et al., 1995. Esteves, 1997,
Pilkey and Clayton, 1997.
There has been no large-scale renourishment activity in the portion of St. Johns County
examined during the study period (Pilkey and Clayton, 1997). However, of the 66.1 km of


121
parametric analyses the Beach Width (BW), Dune Height (DH) and Long Term Change (LT)
variables were important.
Actual Geomorphology and Human Variables
The influence of the local geomorphology on the human variables at specific time periods
was noted in both jurisdictions. The dune height and distance from the monument to maximum
dune height influenced the impervious area and future land use designations in Brevard County.
In St. Johns County the two measures of beach width, from the monument and from the
maximum dune height to NGVD, were positively correlated with the future land use designations
and impervious area, as was the distance from the monument to maximum dune height (MDH)
(Table 6-1). Beach width has been described as the most important independent variable from the
public perception of coastal management (Foster 2002). Beach width is the most reliable
indicator of coastal condition of the independent variable measurements (Foster 2002). Coastal
visitors may consider dunes impediments to access or visibility, but the width of the beach is
considered a positive aspect.
Table 6-1. Summary of bivariate analyses of actual geomorphology and human variables by
jurisdiction
Independent
Relationship
Dependent Variables
Variables
Brevard County
DH,i , t3
Negative
IMP c, u. FLUDu, FLU,3, FLUD a, FLUC 0
MDHti, t2, t3
Negative
(IMP, PM, C) a, a, FLUD FLU a FLUD a
St. Johns County
BW. BW BW
Positive
IMP,, IMP,, IMP,, FLUD,, FLUD,,
St. Johns County, Ponte Vedra to Vilano Beach
DHBW
Negative
UN a-2, UN e-i UH0-2 UH a., FLUD 0
BWuBWoBW,,
Positive
FLUD,, FLUD a
MDH0 MDH,,
Positive
FLU a
Anastasia Island, St. Johns County
MDH,; MDH
Positive
FLU a
The total number of hectares of commercial development measured in 1999 in St Johns
County an example of a dependent variable that has a functional multivariate relationship with
actual geomorphic variables. This research found examples of the influence of local


174
Table H-14. St Johns County Spearman Rank analyses (Anastasia Island, Monument 140 to 198),
Dune Height (DH)) and dependent variables at 0.05 significance
DH
DHo
DH,3
DH,,.,
DH.3.2
DH0,
DH,0,
DHf
OR
UN
-
-
-
-
-
-
0.4161
-
-
UN*
-
-
-
0.4443
-
0.3131
0.4774
-
UN
-
-
-
0.5030
-
0.3834
0.4837
0.3377
0.3150
unq.,
-
-
-
0.4160
-
0.3581
0.3939
-
-
UN.2
-0.3135
-
-
0.3508
-
0.3045
-
-
-
UNo.,
-0.3527
-
-
0.5145
-
0.3902
0.3817
0.3450
-
UH
-
-
-
-
-
0.4450
-
-
UH.2
-
-
-
0.4203
-
-
0.4664
-
-
UH
-
-
-
0.4817
-
0.3621
0.4857
0.3009
-
UH.2-,
-
-
-
0.3792
-
0.3317
0.3764
-
-
UH.2
-0.3250
-
-
0.3745
-
0.3198
-
-
-
UHo-i
-0.3625
-
-
0.5122
-
0.3882
0.3805
0.3390
-
IMP,,
-
-
-
-
-
-
0.5003
-
IMP,2
-
-
-
-
-
-
0.4425
-
-
IMPt,
-
-
-
-
-
-
0.3037
-
-
IMP.|
-
-
-
-
-
-
0.3786
-
-
IMP, j.2
-
-
-
-
-
-
-
-
-
IMP,3.,
-
-
-
-
-
-
-
-
-
PIM
-
-
-
-
-
-
0.5271
-
-
PIM
-
-
-
-
-
-
0.3751
-
-
PIM.3
-
-
-
-
-
-
-
-
-
PIMU.,
-
-
-
-
-
-
0.3141
-
-
PIM.3.2
-
-
-
-
-
-
-
-
-
PIMo.,
-
-
-
-
-
-
-
-
-
ACC
-
-0.3097
-
-
-
-
-
-
-
DACC
-
-
-
0.4345
0.3201
0.4943
0.5833
0.3260
-
POS
0.7594
0.7550
0.6435
-0.4356
-0.3938
-0.5083
-0.5046
-0.4638
-0.9479
c
-
-
-
-
-
Ca
-
-
-
-
-
-
-
-
-
Co
-
-
-
-
-
-
-
-
-
Ct2-1
-
-
-
-
-
-
-
-
-
Co-2
-
-
-
-
-
-
-
-
-
Co-1
-
-
-
-
-
-
-
-
-
FLUD,i
-
-
-
-
-
-
-
-
-
FLUo
-
-
-
-
-0.3514
-
-
-
-
FLUD.2
-
-
-
-
-0.3651
-
-
-
-
FLUC,2
-
-
-
-
-
-
-
-
-
FLU
-
-
-
-
-
-
-
-
0.3191
FLUDo
-
-
-
-
0.3018
0.3756
-
0.3259
-
FLUCo
-
-
-0.3013
-
-
-
-
-
0.4454


164
Table H-4. Brevard County Spearman Rank analyses, Maximum Dune Height to NGVD
(DHBW)) and dependent variables at 0.05 significance
DHBW,,
DHBWa
DHBWa
DHBWa.
, DHBWa-2
DHBWa.
, DHBW,0,
DHBWf
UN
-
0.2506
-
-
-
-
0.2602
-
UN.2
-
0.2599
-
-
-
-
0.2855
-
UNa
-
0.2392
-
-
-
-
0.1951
-
UNa.,
-
-
-
-
-
-
-
-
UN.2
-
-
-
-
-
-
-
-
UNa-i
-
-
-
-
-
-
-
-
UH
-
0.2680
-
-
-
-
0.2875
-
UH(2
-
0.2562
-
-
-
-
0.3030
-
UHa
-
0.2358
-
-
-
-
0.2204
-
UHa-,
-
-
-
-
-
-
-
-
UHlV2
-
-
-
-
-
-
-
-
UH,3.,
-
-
-
-
-
-
-
-
IMP,,
-
0.2644
-
-
-
-
0.2583
-
IMP,,
-
0.3328
-
-
-
-
0.2874
-
IMP,,
0.1738
0.3632
0.2119
-
-
-
0.2172
-
IMP.,
-
0.2560
-
-
-
-
0.1793
-
imp0.2
-
-
-
-
-
-
-
-
IMP.|
-
0.3205
0.2391
-
-
-
-
-
PIM
-
0.3237
-
-
-
-
0.3112
-
PIM
-
0.3785
-
-
-
-
0.3633
-
PIM0
0.1760
0.4146
-
-
-
-
0.3084
-
PIMe.,
-
0.2333
-
-
-
-
0.1995
-
PIMu-2
-
-
-
-
-
-
-
-
PIMa-,
-
0.3050
-
-
-
-
-
-
ACC
-
-0.2798
-
-0.1865
-
-
-0.3219
-
DACC
-
-
-
-
-
-
0.3075
-
POS
-0.1723
-0.4049
-0.3425
-
-
-
-0.3997
-
Qi
-
0.2269
-
-
-
-
0.2446
-
Cq
0.1832
0.2772
-
-
-
-
0.2255
-
03
0.1809
0.3012
0.1801
-
-
-
0.1743
-
Q2-1
-
0.2126
-
-
-
-
-
-
Ct3-2
-
-
-
-
-
-
-
-
03-1
-
0.2493
-
-
-
-
-
-
FLUD,,
-
0.4077
-
-
-
-
0.3694
-
FLUa
-
0.3737
-
-
-0.1885
-
0.2890
-
FLUDa
0.1923
0.3907
-
-
-0.2011
-
0.3732
-
FLUCu
0.1448
0.2774
-
-
-
-
0.2784
-


14
minimize the effect of storm influences. Seasonal variations include profile shape, which may
vary significantly in winter months when high wave energy may cause the development of
longshore bars with sediment that would otherwise be part of the terrestrial profile (Foster and
Savage, 1989). The prevailing philosophy is that winter waves denude (and summer waves
restore) the beach profile in a natural system (Carter, 1988; Guan-Hong et al., 1995). A1 Bakri
(1996) analyzed beach profiles in Kuwait and noted the tendency for the profile volume to
increase in summer and decrease in winter. The volume of material in the profile is not used as a
variable in this research. It was considered that the volume varies seasonally on shorter
timeframes than data by decade can reflect. The profile data timescales were considered too
coarse to provide a useful measure of volume. Additionally, Rahn (2001) found no relationships
between subaerial volume variations in developed or undeveloped areas.
Table 2-3. Beach-profile research; geomorphic and human variables
Variable
Study
Beach width
Clark, 1999; Rahn, 2001; Shideler and Smith, 1984;
Stanczuk, 1975; Wright, 1991.
Dune height
Gares, 1987; Nordstrom et al., 1990; Rahn, 2001;
Shideler and Smith, 1984; Stanczuk, 1975.
Profile gradient
Allen, 1991: Meesenburg, 1996.
Position of dune crest
Allen, 1991; Gares, 1987; Olivier and Garland, 3003;
Rahn, 2001; Stanczuk, 1975.
Profile volume
Al Bakri, 1996; Allen, 1991; Gares, 1987; Rahn, 2001.
Barrier island width
Stanczuk, 1975; Stone et al., 1985; Stone and Salmon,
1988.
Impacts of erosion and flooding
Balsillie, 1985; Clark, 1999; Dean and Malakar, 1999;
Fenster and Dolan. 1996; Gares, 1990.
Seasonality
Dolan, 1976; Stanczuk, 1975.
Storms
Webb et al., 1997; Meesenburg, 1996.
Long-term shoreline change
Bodge, 1992; Foster, 1992; Foster, 2002; Foster et al.,
1989; Foster at al., 2000; Olsen, 2003.
Human data
Bellomo et al., 1999; Finkl and Charlier, 2003; Foster,
1992; Foster et al., 1989;
Coastal Development
Al Bakri, 1996; Bush et al., 1999; Rahn, 2001; Smith,
1994; Stanczuk, 1975.
Foredune grading
Hails, 1977.
Sand mining
Carter, 1988; Davis and Barnard, 2000; Hails, 1977.
Structures
Collier et al., 1977
Vehicular traffic, trampling,
vegetation, and fences
Carter, 1988; Viles and Spencer, 1995.


185
APPENDIX J. Continued
Table J-2. Future land use density (FLUD,i), Brevard County, 1972
Dep.
Variable
R2
Intercept
P>
Variable
P2
Variable
P3
Variable
FLUDu
(n=109)
0.649
-89.915
-4.066
DH
-21.147
LT
0.821
OR
Dependent Variable
FLUD
Adjusted R-Squared
0.6488
Independent
Regression
Standard
Variable
Coefficient
Error
Intercept
-89.91521
24.67579
DHtl
-4.065736
1.308955
LT
-21.14734
3.318424
OR
0.821133
0.1204817
T-Critical
1.982597
F-Ratio
68.1320
N=109
T-Value Prob Decision Power
(Ho: B=0) Level (5%) (5%)
-3.6439 0.000418 Reject Ho 0.950599
-3.1061 0.002433 Reject Ho 0.868188
-6.3727 0.000000 Reject Ho 0.999993
6.8154 0.000000 Reject Ho 0.999999
0.000000 1.000000
FLUDn = Potential Residential Density, 1974 Comprehensive Plan (units per hectare)
DH,i = 1972 Dune Height (m)
OR = Shoreline Orientation (degrees from north)
Table J-3. Future land use units (FLU p), Brevard County, 1997
Dep.
Variable
R2
Intercept
P.
Variable
P2
Variable
FLU a
(n=106)
0.479
547.346
-71.231
DHa
-1.337
MDH
Dependent Variable FLU a
Adjusted R-Squared 0.4789
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
547.3455
51.36757
10.6555
0.000000
Reject Ho
1.000000
DHi3
-71.23122
11.37088
-6.2644
0.000000
Reject Ho
0.999989
MDH,i
-1.337258
0.391753
-3.4135
0.000907
Reject Ho
0.922598
T-Critical
1.982383
F-Ratio
51.0849
0.000000
1.000000
N=109
FLU = Potential Units, 1999 Comprehensive Plan
DH,3= 1997 Dune Height (m)
MDH,i = 1972 Distance from Monument to Maximum Height (m)
(DHBW |3-i)2 = Squared value of 1972 to 1997 Change is Distance from NGVD to Maximum
Dune Height (m)


104
impervious areas cannot act to absorb energy and the sediment may be carried seaward of the
dune face. There is also a positive relationship between the change (1986 to 1997) in the number
of density of units (UNt-2, UH.2) and the actual geomorphology of the dune height at the
discrete time periods. Areas where the maximum dune height is higher are also areas where
subsequent increases in the number and intensity of units are larger (Hypothesis 3).
Table 5-14. Dune height and human variable change (1986 to 1997) in Brevard County
Human Variables Maximum Dune Height (DH)
(1986 to 1997) 1972 1986 1997
Total Units (UN) 0.3021 0.2246 0.2806
Units Density (UH) 0.2942 0.2179 0.2731
95% confidence interval
When the entire coastline of St. Johns County is considered the data do not show
significant relationships between the maximum dune height and the dependent variables. There
are no significant temporal relationships by time period with dune height and units, density,
impervious variables, commercial development of adopted future land uses. Although the
dynamic changes in dune height on Anastasia Island show some positive relationships with the
number of units and units per hectare, these data are inconclusive because the pattern does not
prevail for each time period (Appendix H).
Monument to Maximum Dune Height (MDH)
The changes in the distance from the monument to maximum dune height (MDH) between
time periods are a measure of the geomorphic stability of the dunes in relation to a stationary
point, the monument. In Brevard County the actual distance from the monument to maximum
height has a negative relationship with the impervious area and adopted future land use densities
during each discrete time period (Tables 5-15, 5-16). Therefore, the lower the distance between
the monument and the maximum dune height, the higher the impervious area and densities.
This is counter to what was hypothesized in Hypotheses 1 a and 1 b, where a positive value
for the distance to the maximum height was considered an indicator of a wide dune field and an
area more appropriate for development.


APPENDIX F: BREVARD COUNTY LONG TERM CHANGE DETERMINATION
Table F-l. Brevard County Ions term change determination
Monument
End
Point
(m)
Rate Averaging
(Olsen 1989)
(m)
Difference
(m)
Average of
Olsen and End
Point
(m)
(LT) Adjacent
Average
(m)
i
1.23
1.52
0.29
1.38
1.36
2
1.16
1.52
0.36
1.34
1.10
3
0.88
0.30
-0.57
0.59
0.97
5
0.86
0.61
-0.25
0.73
0.85
6
1.03
0.91
-0.12
0.97
0.95
7
1.21
1.07
-0.15
1.14
1.14
8
1.40
1.22
-0.18
1.31
1.13
9
10
0.49
1.37
0.88
0.93
1.12
11
0.30
1.68
1.37
0.99
0.99
12
0.28
1.68
1.39
0.98
0.97
13
0.19
1.68
1.48
0.94
0.96
14
0.41
1.52
1.11
0.97
0.94
15
0.30
1.52
1.23
0.91
0.93
16
0.44
1.37
0.94
0.90
0.90
17
0.40
1.37
0.97
0.89
1.08
18
1.54
1.37
-0.17
1.46
1.24
19
1.51
1.22
-0.29
1.36
1.36
20
1.48
1.07
-0.41
1.27
1.29
21
22
1.41
1.07
-0.35
1.24
1.26
23
1.27
0.91
-0.36
1.09
1.03
24
1.17
0.76
-0.41
0.97
0.93
25
0.67
0.76
0.09
0.72
0.86
26
27
28
29
1.16
0.61
-0.55
0.89
0.80
30
1.11
0.46
-0.65
0.78
0.74
31
1.08
0.30
-0.78
0.69
0.71
32
0.98
0.30
-0.68
0.64
0.63
33
0.79
0.30
-0.48
0.55
0.43
34
0.07
0.15
0.08
0.11
0.35
150


J-6. Percent impervious area (PIM^) Brevard County, 1997 187
J-7. Future land use units (FLU 13) Brevard County, 1997 187
J-8. Future land use units (FLU ,3) St. Johns County south, Monument 141 to
Monument 198, 1999 188
J-9. Future land use density (FLUD^) St. Johns County south, Monument 141 to
Monument 198, 1999 188
J-10. Future land use density (FLUDn) (also hypothesis lb) Brevard County, 1972 189
J-l 1. Potential residential density, 1979 Comprehensive plan (FLUD,i) (also
hypothesis lb) St. Johns County 189
J-12. St. Future land use density (FLUDti) Johns County north, Monument 1 to
Monument 120,1972 190
xii


37
jet stream winds. The position of the jet stream each season affects the number and type of
winter storms (Davis and Dolan, 1993). The Department of Environmental Protection surveying
patterns show that winter storms have impacted the study areas. DEP performs post-storm
condition surveys and from these records there have been storms that impacted the
geomorphology sufficiently that resurveying was performed, usually in small segments of a
county. In Brevard County winter post-storm resurveying was carried out in 1973, 1981, and
1985. The DEP records indicate winter storm activity in 1981 and 1984 in northeast Florida.
Reesman (1994) notes that winter storms impacted the northeast Florida region in 1932, 1947,
1962 and 1973. The U. S. Army Corps on Engineers (1992) lists 28 storms that impacted St.
Johns County between 1977 and 1993. It should be noted that the resurveying of areas is also a
function of the state budget. State funding inconsistencies necessitate caution in concluding that
geomorphic impacts occurred only during these events.
Development History
The land uses in Brevard County have evolved from citrus production to high-density
residential and commercial uses. Figures 3-3 and 3-4 show the development patterns at the same
position in Brevard County. In 1950 Cocoa Beach was approximately half built out and in 1972
was 75 percent built out (Bodge, 1992). The 1972 aerial photography shows there was no
development adjacent to the Port Canaveral Inlet jetty. In the City of Cape Canaveral roads are
perpendicular to the shore and residential and multifamily development was present. In 1985,
95 percent of the Cocoa Beach was built out (Bodge, 1992). Between Cape Canaveral and the
residential area in south Cocoa Beach high-rise residential, commercial and large impervious
parking areas were present. Residential lot sizes in Cocoa Beach are small and development is
dense. There were large structures and areas of impervious surface, such as the Pam Am world
headquarters, which had been redeveloped into high-density condominia by 1997. Patrick Air
Force Base was renovated between 1986 and 1997 and the base housing was redeveloped at
higher densities. South of the Base infill and development on vacant lots has occurred. Brevard


80
over time from 108.5m in 1986 to 227.2m in 1997. The negative value for mean beach width
from 1986 to 1997 of-3.4m illustrates that the beach width on average decreased from 1986 to
1997. The absolute change (BWtot) has a mean of 28.0 m. However the range of BW,ot is large,
from just over a meter to over 300m. The negative values for the minimum beach width indicate
that there are areas where the beach width decreased in each of the time periods. The BW
descriptive statistics in Brevard County indicate that there is no simple trend in the geomorphic
variable. North of Patrick Air Force Base (monument 60), Brevard County is more dynamic,
with more extreme temporal change. The beach is consistently wider in 1986 in Brevard County,
south of Patrick Air Force Base. The BW variation, indicated by the range in values, increases
over time.
Beaches in St. Johns County (Figure 5-1) are widest and show more variation from 1972 to
1999 on Anastasia Island. Trends are similar to Brevard County, with accretion in 1986 north of
St. Augustine Pass. In the Vilano Beach area the 1999 beach width is the most narrow. Beach
width rapidly increased at monument 121 at the north jetty at St. Augustine pass. Matanzas Inlet
has rock revetments adjacent to A1 A, but no jetties. The sample areas south of Matanzas Inlet
have the narrowest beaches in St. Johns County. The rocks that were adjacent to monument 141
in St. Augustine Beach in 1999 were exposed. In St Johns County BW accretion north of St
Augustine Inlet from 1972 to 1986, is similar to Brevard County.
Maximum Dune Height (DH)
The highest point recorded on each of the coastal profiles is the maximum dune height
(DH), and this may occur at the monument. In Brevard County the maximum dune height
increases southward (Figure 5-2). South of Port Canaveral Inlet in Cocoa Beach the maximum
dune height is 3 to 4m, compared to over 6m south of monument 150. The dune heights are most
dynamic at Cocoa Beach and Patrick Air Force Base. The average dune height increases from
5.0m in 1972 to 5.1m at 1997 and the DH,i and DHa are normally distributed (Table 5-2).


126
important, as an indicator of a stable dune field. However, dune progradation seaward of the
monument beyond the original highest point would be reflected in an increased distance from the
monument over time (Figure 6-1). The conclusion of the use of the MDH variable is that the
original bivariate hypothesis was misspecificed and the validity of the revised hypotheses are
supported by the non-parametric results for Brevard County for MDH relationships to dependent
variables.
The two counties differ geographically and by geomorphic unit. This research illustrates
the importance of consideration of coastal features by geomorphic unit, not political jurisdiction.
In Brevard County the multiple coastal municipalities necessitate coordination to ensure
consistency with the adjacent coastline. Geomorphic units within political boundaries should be
planned for separately with consideration for specific physical characteristics. In this way
planning in St. Johns County should not just overlay the entire coastal area, but should be tailored
to the units north and south of the passes. Hart (2000, pp. 43) observes that coastal management
issues often influence broad geographic areas that cross political boundaries. In Florida the
function of the Regional Planning Councils and State Department of Community Affairs is the
ensure vertical consistency between municipal, county, regional and state planning.


94
area in St. Johns County in 1999 is over 133 units. In St. Johns County residential densities were
extremely low at less than 2 du/ha in 1972, increased in 1986 and again in 1999.
The 1999 average density for all sample areas in St. Johns County is 6.3 du/ha compared
to Brevard Countys 22.27 du/ha. Maximum densities established by the 1999 comprehensive
plan are 15 du/ha in St. Johns County, compared to 70 du/ha in Brevard County. There are
instances in St. Johns County such as Vilano Beach, central Anastasia Island and Summer Haven,
where the number of units in 1999 exceeds the adopted future land use levels. Future land uses
are established considering existing conditions, but can be established at lower levels. Vilano
Beach is participating in a Florida Department of Community Affairs waterfront redevelopment
program and has reconsidered development levels. Also, the use of the mid-range of the proposed
densities in this research underestimates to total potential units.
Impervious Area (IMP) and Percent Impervious Area (PIM)
The impervious area (IMP) is the total number of hectares that are impervious in each 9-ha
sample area. The total impervious area (IMP) is divided by the available area for development to
derive the percentage impervious area (PIM). Similar to the total units (UN) and density (UH), to
percentage impervious area (PIM) is affected by the amount of the sample area available for
development. The average number of impervious hectares increases from 1.4 in 1972 to 2.5 in
1997 for the 138 9-ha sample areas in Brevard County increasing by 0.8 ha and 0.4 ha in the first
and second time periods. The PIM increased from 21.6 percent to 39.6 percent and the increase
was more rapid between 1972 and 1986. There were 9-ha sample areas containing no impervious
area and others experienced a decrease in impervious hectares. Decreased impervious hectare
values are consistent with the redevelopment at higher dwelling units densities, such as
redevelopment of a dwelling unit with a reduced floor area ratio from the addition of another
floor to the structure. This increases the total units without impacting the original building
footprint.


160
APPENDIX H: NON-PARAMETRIC STATISTICS (SPEARMAN RANK) ROW WISE
CORRELATIONS, BREVARD AND ST. JOHNS COUNTY.
Table H-l. Brevard County Spearman Rank analyses, Beach Width (BW) and dependent
variables at 0.05 significance
BW,i BW,2 BWi3 BW, BW,,.; BW_i BW,0, BW,LT
0.1750 -
UN -
UN0 -
UNo -
UNi2., - 0.2022
UNu.2 - 0.2478
UNo., - 0.3057
UH ....
UH.2 -
UH0 - -
UHq.i - 0.1779
UH,3.2 - 0.2394
UH,3.i - 0.2789
IMP,, ....
imp,2 ....
IMP,, ....
IMPa.i - 0.2794
IMP.3.2 - 0.2916
IMPa., - 0.3258
PIM
PIMa ....
PIM ....
PIM,2., - 0.2163
PIM.3.2 - 0.2825
PIM,,., - 0.2593
ACC - -0.1885
DACC -0.2265 -0.2078 -
POS 0.1858 -
-0.2666
-
:
:
:
-0.1800
-
-
-
-
-0.2615
_
_
_
_
0.2047
-
0.3699
-
0.3165
-
-
0.3656
-
0.3528
-
0.1922
0.3566
-
0.1781
-
0.1860
-
-
0.2188
-
0.2350
-
-
0.2437
-
0.2660
-
-
0.3106
0.1894
-
0.3528
-
0.2464
-
-
0.2998
-
0.2837
-
0.2902
-
0.3165
-
0.2285
-
-
0.2111
_
_
-0.3701
_
-0.1878
-
-
0.3234
-
-
-
-0.2736
-0.5891
-
-0.5590
160


7
needed to determine the extent of coastal evolution. Responses of the shorelines of the world
would be simpler to evaluate if there were some observable and straightforward explanation for
most changes (Carter and Woodroffe, 1994, pp. 2).
Table 2-1. Importance of scale in spatial and temporal research
Macro scale
Brown and McLachlan, 2002; Clark, 1976; Clark,
1997; Phillips, 1988; Phillips, 1997; Viles and Goudie,
2003; Viles and Spencer, 1995.
Micro scale
Abumere, 1980; Conway and Nordstrom, 2003; Gares,
1987; Nordstrom et al., 1999; Nordstrom et al., 2002;
Sherman and Bauer, 1993.
Long Term
Carter, 1988; Dean, 1999; Dolan et al., 1991; Foster,
1992; Foster and Savage, 1989; Nordstrom, 1996;
Pilkey, 2003; Schumm, 1991; Van Der Wal, 2004;
Viles and Goudie, 2003.
More immediate
Byrnes et al., 1995; Dolan et al., 1991; Gares, 1990;
Haggett et al., 1977; Phillips, 1997; Phillips, 2005;
Schwartz, 1971; Shideler and Smith, 1984.
Multiple Causality
Butler And Walsh, 1998; Phillips, 2005; Phillips,
1997; Schwartz, 1971; Walsh et al., 1998.
Caution is important in extrapolating results before determining landscape behavior over
time, because the landform may not be responding to a single input into the system. The
importance of time in evaluating coastal systems cannot be overstated. In evaluating of coastal
variables, selecting the wrong study period for the process can cause totally inaccurate results
(Dean, 1999; Dolan et al., 1991; Foster, 1992; Foster and Savage, 1989). In Australia initial 4-
week study of longshore drift (Schumm, 1992) produced results that were inconsistent with the
local coastal features. By extending the study period, longshore drift in the opposite direction
was also noted. Similarly Nordstrom (1994) notes that the historically multidirectional drift
pattern along the coastline of New Jersey has been rendered unidirectional by the impacts of
human development. Those studying the New Jersey coastline over short periods of time (not
considering the pre-1935 shoreline) conclude that the drift system is to the south only, being
unaware that the choice of time period influences the conclusions. Evaluation of the impacts and
longevity of renourished shorelines requires extensive temporal investigation. Van Der Wal


134
Table B-l. Continued
Variable Description
Name
Units
Data Sources
Total Dune Height to NGVD
Change
DHBW,0
m
Modified DEP data, derived from Annual
Dune Height to NGVD Factor
DHBWf
Between -
1 and 1
Dune Height to NGVD data
Long Term Change
LT
m
http://hightide.bcs.tlh.fl.us/counties/HSSD/r
eadme/read.mel, Olsen 1989 (Brevard)
Foster et al., 2000 (St. Johns)
Shoreline Orientation
OR
In degrees
from
North (0)
GIS from County and Coastal Construction
line
(http://www.dep.state.fl.us/beaches/data/gis-
data.htm#GIS Data)
Presence of Structures
SW
Nominal
Bodge and Savage, 1989, Foster et al.,
2000., St. Johns County, 2002,
DEP Erosion Designation
ER
Nominal
http://www.dep.state.fl.us/beaches/data/gis-
data.htm#GIS Data, Clarke (2002)
Renourishment
RN
Nominal
Olsen, 1989, Brevard County
Comprehensive Plan, 1988, Foster et al.,
2000
Dune Renourishment
RND
Nominal
Brevard County Comprehensive Plan, 1988,
FDEP 2000a,
1972 Number of Units
UN.i
Units
DEP Aerial Blue Line 1972, 1:1200 scale
1986 Number of Units
UNtf
Units
DEP Aerial Blue Line 1986, 1:1200 scale
1999 (1997)Number of Units
UN,3
Units
Brevard County DOQQ, 1997, St. Johns
County DOQQ, 1999, use of Mr. Sid and X
tools
1972 to 1986 Number of Units
UN*.,
Units
1986 to (1997) 1999 Number
of Units
UN, J.2
Units
Derived from Annual Unit Data
1972 to 1999 Number of Units
UN,3-,
Units
1972 Units per Hectare
UH
du/ha
1986 Units per Hectare
UHa
du/ha
Derived from Annual Unit Data and GIS
1999(1997) Units per Hectare
UH,j
du/ha
1972 to 1986 Units per Hectare
UH.,
du/ha
1986 to 1999(1997) Units per
Hectare
UH,3.2
du/ha
1972 to 1999 (1997)Units per
Hectare
UH.3-1
du/ha
1972 Impervious Area
IMP,,
la
DEP Aerial Blue Line 1972, 1:1200 scale
use of Mr. Sid and X tools
1986 Impervious Area
imp,2
la
DEP Aerial Blue Line 1986, 1:1200 scale
use of Mr. Sid and X tools
(1997) 1999 Impervious Area
IMP,,
a
Brevard County DOQQ, 1997, St. Johns
County DOQQ, 1999, use of Mr. Sid and X
tools
1972 to 1986 Impervious Area
IMP,2.,
la
Derived from Impervious Area Data


72
Table 4-10. Hypothesis la, actual geomorphic and human variable relationships.
Actual Geomorphology
(Each Time Period)
Hypothetical
Relationship
Human Variable
(Same Time Period)
1972
1972
Beach Width Index (BWtl);
Dune Height (DH,i);
Distance Monument to Maximum
Positive
Impervious Area, (IMP,i),
Percent Impervious Area (PIM,i)
Number of Dwelling Units
Dune Height (MDHt]);
Distance NGVD to Maximum
(UN,i), Dwelling Units per
Hectare (UHn), Commercial
Dune Height (DHBW)
Long Term Shoreline Change (LT)
Positive
Hectares (C,i)
Impervious Area, (IMP^-IMP^),
Percent Impervious Area (PIM,r
PIMo) Number of Dwelling
Units (UNtr UN,3), Dwelling
Units per Hectare (UHt]- UHt3),
Commercial Hectares (C,|-C)
Hypothesis lb: The local geomorphology influences the land use control decision-making.
This hypothesis proposes that future land use plans are developed by considering
geomorphological conditions (Hails, 1977). The hypothetical relationships between the 1999
geomorphology in St. Johns County and the 2001 proposed future land uses for the 2015 horizon
are shown below. The hypotheses would be the same for the two other discrete time periods.
Table 4-11. Hypothesis lb, actual geomorphic and future land use variable relationships.
Actual Geomorphology
Hypothetical
Land Use Control Variable
(Each Time Period)
Relationship
(Adopted For Each Time
Period)
1999
2001
Beach Width Index (BW,3);
Positive
Future Land Use total units
Dune Height (DH,3);
and density (2015 horizon)
Distance Monument to Maximum
Dune Height (MDHo);
Distance NGVD to Maximum Dune
(FLU), (FLUD)
Height (DHBW)
Long Term Shoreline Change (LT)
Positive
Future Land Use Density
(FLU* FLUo), (FLUD-
FLUD)
Hypothesis 2: The dynamic geomorphology impacts human variables
Hypothesis 2a: The dynamic geomorphology indicators influence the actual human
variables. Local coastal geomorphology that varied over decades indicating a dynamic area
would be negatively correlated to human variables (Lundberg and Handegard, 1996; McMichael,


Ill
width (BW) at the specific time periods is a significant variable in St. Johns County (Hypotheses
la and lb) but only the dynamic beach width variable impacts dependent variables in Brevard
County (Hypothesis 2). The distance from the monument to maximum dune height (MDH) is
significant in Brevard County (although not consistent with hypotheses) and the separate
geomorphic units of St. Johns County, but not the entire county. The impact of a temporal lag on
dependent variables (Hypothesis 3) is present Brevard County, but not in St. Johns County.
Similarities between the two study areas include association between accretion and the location of
higher numbers of units, density, impervious area and future land uses
Table 5-25. Summary of non-parametric results by hypothesis, Anastasia Island, St. Johns County
Hypothesis
Independent
Variable
Relationship
Dependent Variables
la-Actual geomorphology and
development
No relationships
lb-Actual geomorphology and
adopted future land use
MDH.2,
MDH,;,
Positive
FLU ,3
2a-Dynamic geomorphology
and development
LT
MDHcm,
MDH,3-,
Positive
Positive
UNt2, t3, t2-l, 13-2,0-l, UH ,|, ,2, t3,
t2-l,t3-2, t3-l
FLU a, FLUDt3
2b-Dynamic geomorphology
and adopted future land use
3-Temporal lag between the
actual and dynamic
geomorphology and the human
variables
LT
Positive FLU ,3> FLUD t3
No relationships
Multivariate Statistical Analyses
Regression analyses are used to evaluate the multiple interactions of variables and to
measure and model the dimensions of the impacts of variables (Appendix J). Independent
variables were transformed to investigate non-linear relationships. The nominal and categorical
data, such as the presence of absence of structures, renourishment, and FDEP designated areas of
erosion (Clark, 1999) were used as dummy variables for analyses. Similar to the non-parametric
analyses the Beach Width (BW), Dune Height (DH) variables were important. The combination
of the Beach Width and Dune Height was evaluated by an interactive variable (DHBWDH).
These analyses enabled the use of the categorical and ordinal variables to be evaluated for


69
for Brevard County (Brevard County Board of County Commissioners, 1981). Brevard County
has five incorporated coastal municipalities and Patrick Air Force Base. The 1981
Comprehensive plan included land use designations for all incorporated areas and was used to
determine the FLUD,i Digital land use data from the 1988 plan (Brevard County Comprehensive
Planning Division, 1989) was not available for Brevard County. Digital information for the most
recent comprehensive plans was obtained from Brevard County, Cape Canaveral, Cocoa Beach,
Satellite Beach and Melbourne (FLU^, FLUDt3 and FLUC,3). Indiatlantic is a small coastal
municipality and data were not obtained because it contained no monuments with continuous
geomorphic data.
Figure 4-12. Determination of total impervious area (IMP) in 9-ha sample area


76
each variable, for both Brevard and St Johns counties, were developed. The lack of normality
noted in the independent geomorphic variables prompted further analysis by geomorphic unit.
Brevard County was divided north and south of Patrick Air Force Base, and by orientation. St.
Johns County data were divided by geomorphic unit. The county was divided into two areas -
Ponte Vedra to Vilano Beach, and Anastasia Island (St. Augustine Beach to Matanzas Inlet). The
Summer Haven monuments (199 to 208) south of Matanzas inlet were not included.
The importance of spatial variation of variables along the coast is captured utilizing spatial
location of the 9-ha sample areas. The statistical inferences determined by the variables cannot
be isolated without consideration of the spatial implications (Burt and Barber, 1996;
Fotheringham and Brunsdon, 2004). The variables ACC, DACC, and POS serve as a proxy for
location. The variable POS is the distance along the coast from north to south. The influence of
the spatial dimension is further expanded by the distance to access (ACC) and direction and
distance to access (DACC) variables. These variables are weighted forms of location of the
sample area. ACC is a linear measure of the distance north or south, to the closest access or
bridge to the barrier island. In northern St. Johns County access is north into the adjacent county.
There is no access to the west between the county boundary and the Vilano Beach bridge at St.
Augustine Pass. In Brevard County access is limited to causeways to the barrier islands. The
DACC variable adds a direction component to the distance to the access point. A negative
DACC value represents that the nearest access point is to the south of the monument. The
orientation of the seaward axis of the 9-ha sample area to north (OR) is a further spatial derivative
to enhance the statistical analyses. St. Johns County is also divided by geomorphic unit into two
parts to recognize the importance of separate analyses for geographically distinct areas.
Geographically weighted regression can also be considered for the evaluation of variables at
varied spatial scales, from global, regional and local (Mei et al., 2004). This research does not
consider what has been defined as mixed geographically weighted regression.


43
coastline, 2.8 km have been renourished (Esteves, 1997) in Anastasia State Recreation Area. The
park was renourished in 1963 when 38,230 m3 of sediment was added (Dean and Donohue,
1998). In 2000 renourishment began at St Augustine Beach (monuments 140 to 147) and in 2001
at Summer Haven (monuments 200 to 207). Renourishment using sediment dredged from St.
Augustine Inlet was carried out in Anastasia State Park in 2002 (Dean and Donohue, 1998).
While Anastasia State Park is not included in the study area because it is excluded from
development as a State Park, sediment from renourishment projects enters the coastal system on
Anastasia Island, downdrift of the park.
Table 3-3. Recent renourishment projects, Brevard County.
Monument
Location
Alongshore
Distance (km)
Date
Volume
(m3)
3-54.5
15.13
Oct. 2000-April 2001 2,435,720
53-60
4.99
Dec. 2000-April 2001 454,670
122.5-139
4.86
Feb-April 2002
899,000
118.3-123.5
1.51
March-April 2003
175,840
Source: Olsen (2003)
Table 3-4. Recent renourishment projects, St. Johns County.
Monument
Distance (km)
Date
Volume (m3)*
Location
140-147 St
Unknown
2000
Unknown
Augustine Beach
132-152
6.12
Sept. 2001-Jan
848,930
2003
Summer Haven
Unknown
2001
Unknown
*Excludes Anastasia State Recreation Area.
Source: FDEP (2004a), Dean and Donohue (1998).


APPENDIX G: DESCRIPTIVE STATISTICS, BREVARD AND ST. JOHNS COUNTY
Table G-l. Descriptive statistics, dependent and independent variables, Brevard County
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05 Normality
Monument to Maximum Dune Height
MDH||
146
49.0
28.1
0
111.9
0.1037
0.073 Reject
MDII,,
142
47.1
29.5
0
152.4
0.0728
0.074 Accept
MDHt3
142
52.4
30.1
0
152.4
0.0803
0.074 Reject
MDH^.i
139
-2.1
21.3
-71.0
82.3
0.1626
0.075 Reject
mdh.2
136
5.2
23.2
-57.9
110.3
0.1997
0.076 Reject
MDHij.,
139
3.22
27.5
-69.2
129.2
0.1952
0.075 Reject
MDH[0,
133
26.7
29.6
0
137.2
0.1912
0.076 Reject
MDHf
133
-0.01
0.8
-1
1
0.1368
0.076 Reject
Maximum Dune Height to NGVD
DHBW
148
49.2
27.0
4.1
149.9
0.1920
0.072 Reject
dhbw,2
141
57.2
23.6
24.3
157.9
0.1966
0.074 Reject
DHBWu
140
49.9
21.7
19.5
199.9
0.1910
0.075 Reject
DHBWt2.,
141
8.4
24.8
-76.1
82.4
0.1258
0.074 Reject
DHBW.3.2
135
-7.3
24.6
-108.2
72.9
0.1550
0.076 Reject
DHBW.3.,
141
1.6
28.9
-115.2
155.3
0.1803
0.074 Reject
DHBWt01
137
34.3
32.7
0
155.3
0.1766
0.075 Reject
DHBWf
135
0.2
0.7
-1
1
0.1031
0.076 Reject
Number of Units
UN
138
17.7
24.2
0
176
0.2249
0.075 Reject
UNC
138
24.0
27.6
0
176
0.1854
0.075 Reject
UN0
138
28.1
28.6
0
176
0.1555
0.075 Reject
UNa.,
138
6.2
10.9
-10
58
0.2265
0.075 Reject
UN.3.2
138
4.1
9.4
-23
50
0.2291
0.075 Reject
UNo.,
138
10.4
14.3
-22
58
0.1867
0.075 Reject
Hectares of Impervious
IMP,,
138
1.4
1.6
0
8
0.1858
0.075 Reject
IMP,2
138
2.2
2.0
0
8
0.1534
0.075 Reject
IMP,3
138
2.5
2.0
0
8
0.1253
0.075 Reject
IMPe-i
138
0.8
1.0
-0.7
5.0
0.2024
0.075 Reject
IMP.3,2
138
0.3
0.7
-0.6
5.0
0.2470
0.075 Reject
IMP,,.,
138
1.1
1.2
-0.6
5.7
0.1576
0.075 Reject
Hectares of Commercial
Qi
138
1.0
1.6
0
8
0.2457
0.075 Reject
Ca
138
1.7
1.9
0
8
0.1775
0.075 Reject
Co
138
1.9
2.0
0
8
0.1558
0.075 Reject
Qm
138
0.6
1.0
-0.7
5
0.2668
0.075 Reject
Q3-2
138
0.3
0.7
-0.6
5
0.3100
0.075 Reject
Ct3-1
138
0.9
1.2
-0.7
5.8
0.1792
0.075 Reject
155


159
Table G-4. Descriptive statistics, dependent and independent variables, Anastasia Island
(Monuments 141-195), St. Johns County
Count Mean
Standard
Deviation
Min.
Max.
Kolmogorov-
Smirnov
0.05 Normality
Monument to Maximum Dune Height
MDH
39
6.7
8.9
0.0
45.7
0.2105
0.140 Reject
MDHa
39
16.4
19.2
0.0
53.0
0.2443
0.140 Reject
MDHu
39
23.0
21.3
0.0
72.2
0.1840
0.140 Reject
MDHt2.i
39
9.8
21.6
-45.7
53.0
0.2428
0.140 Reject
MDH[3.2
39
6.6
17.0
-23.8
72.2
0.3018
0.140 Reject
MDH0.|
39
16.4
23.4
-36.6
72.2
0.2024
0.140 Reject
MDH,ot
39
24.7
21.9
0.0
72.2
0.1713
0.140 Reject
MDHf
39
0.3
0.8
-1.0
1.0
0.2215
0.140 Reject
Maximum Dune Height to NGVD
DHBWn
44
99.5
18.5
47.5
135.8
0.1014
0.132 Accept
DHBWq
47
125.2
29.6
40.2
190.6
0.1161
0.128 Accept
DHBW,j
47
116.0
28.8
23.1
170.9
0.1439
0.128 Reject
DHBW^.i
48
31.3
34.9
-76.5
139.5
0.1243
0.127 Accept
DHBW,j.2
48
-8.9
21.9
-60.1
53.2
0.1036
0.127 Accept
DHBW,3.i
48
22.4
36.8
-76.5
131.2
0.1678
0.127 Reject
DHBW,ot
48
53.9
35.1
3.1
147.8
0.1183
0.127 Accept
DHBWf
48
0.4
0.6
-1.0
1.0
0.1583
0.127 Reject
Number of Units and Hectares of Impervious
UN
44
11.5
12.5
0.0
55.0
0.2333
0.132 Reject
UNU
44
18.3
18.9
0.0
78.0
0.1434
0.132 Reject
UN0
44
24.9
25.9
0.0
127.0
0.1664
0.132 Reject
UNo.,
44
6.8
13.0
-9.0
58.0
0.1394
0.132 Reject
UNo-j
44
6.6
11.0
-9.0
49.0
0.2199
0.132 Reject
UN0.,
44
13.5
20.7
-8.0
94.0
0.1582
0.132 Reject
IMP,,
45
0.3
0.5
0.0
2.1
0.2599
0.131 Reject
IMPi2
44
1.2
1.2
0.0
5.0
0.1502
0.132 Reject
IMPo
44
2.1
1.9
0.0
6.9
0.1439
0.132 Reject
IMPo-,
44
0.9
1.2
-0.4
5.0
0.2452
0.132 Reject
impu.2
44
0.9
1.6
-0.3
6.8
0.2687
0.132 Reject
IMPo-i
44
1.8
1.8
0.0
6.7
0.1643
0.132 Reject
Hectares of Commercial
C
44
0.1
0.4
0.0
1.5
0.4495
0.132 Reject
Co
43
0.9
1.2
0.0
5.0
0.2146
0.134 Reject
Co
43
1.7
1.9
0.0
6.8
0.2020
0.134 Reject
Ctf-l
44
0.7
1.2
-0.4
5.0
0.2358
0.132 Reject
Ct3-2
44
0.8
1.6
-0.3
6.6
0.3035
0.132 Reject
Ct3-1
44
1.5
1.9
-0.02
6.6
0.2139
0.132 Reject
Future Land Use
FLU,2
44
22.7
17.8
0.0
76.2
0.2007
0.132 Reject
FLUCo
44
0.2
0.4
0.0
1.6
0.2752
0.132 Reject
FLUo
44
42.7
26.3
0.0
133.0
0.1884
0.132 Reject
FLUCo
44
0.4
1.1
0.0
5.6
0.4836
0.132 Reject


98
The average number of impervious hectares increases from a 1972 value of 0.2 to a 1999
value of 1.1 ha for the 138 9-ha sample areas in St. Johns County. The percentage impervious
area increases over the 30-year period to a maximum of 18.3 percent in 1999. The increase in the
percent impervious area from 1972 to 1999 for the 138 9-ha samples was 14.4 percent. Similar to
Brevard County there are sample areas with no impervious area and decreasing amounts of
impervious area over time that result from redevelopment and changes in building type.
Table 5-6. Descriptive statistics, percentage of impervious area (PIM)
Count Mean
Standard
Deviation Min.
Max.*
Kolmogorov-
Smimov
0.05
Normality
Percentage Impervious (Brevard County)
PIM 138
21.6
24.4
0.0
88.9
0.1809
0.075
Reject
PIM,2 138
34.6
29.8
0.0
100.0
0.1418
0.075
Reject
PIM.3 138
39.6
30.3
0.0
100.0
0.1362
0.075
Reject
Percentage Impervious (St. Johns County)
PIM 134
4.0
6.1
0.0
36.1
0.2457
0.076
Reject
PIM,2 138
11.3
14.8
0.0
92.8
0.2163
0.075
Reject
PIM,, 138
18.3
21.1
0.0
100.0
0.1854
0.075
Reject
Percentage Impervious (St. Johns County, monument 1 to 121)
PIM,i 79
3.9
5.4
0.0
27.8
0.2249
0.099
Reject
PIM,2 83
8.2
10.1
0.0
41.0
0.1957
0.097
Reject
PIMt3 83
12.5
11.9
0.0
56.5
0.1352
0.097
Reject
Percentage Impervious (St. Johns County, monument 141 to 195)
PIM 44
5.1
7.5
0.0
36.1
0.2378
0.132
Reject
PIM,2 44
19.1
20.2
0.0
92.8
0.1490
0.132
Reject
PIMi3 44
32.6
28.9
0.0
100.0
0.1295
0.132
Accept
* The maximum impervious area was adjusted in areas where the total exceeded 100%
Commercial (C) and Commercial Future Land Use (FLUC) Variables
The average hectares of commercial property in the sample areas in Brevard County
increased from 1.0 ha in 1972 to 2.0 in 1997. There were sample areas without commercial
development, and with a reduction in the number of commercial hectares. Redevelopment of
commercial areas must meet Water Management District stormwater permit requirements that
necessitate increased pervious area that could be an explanation of decreases in commercial area.
The average hectares of commercial property in St. Johns County increased from 0.1 ha 1972 to
0.7 in 1997. The increase of 0.3 ha during each period is consistent, showing a steady rate of


CHAPTER 5
ANALYSES AND RESULTS
The descriptive statistics of the independent and dependent variables for each County are
provided in Appendix G. The results of the non-parametric statistical analyses are shown in
Appendix H. St. Johns County variable plots of beach width (Figure 5-1) and the variation in
long-term shoreline change and independent variables (Appendix I) illustrate the potential for
variables to be more appropriately analyzed by smaller geographic unit. St. Johns County was
divided into two areas Ponte Vedra to Vilano Beach, and Anastasia Island (St Augustine Beach
to Matanzas Inlet). Appendix I includes the graphic representation of variables by county that are
not included in this chapter. The regression analyses and results are shown in Appendix J.
Independent Variable Characteristics
Appendix G contains the independent geomorphic variable descriptive statistic summary.
Brevard County data were from 1972 (,i), 1986 (,2) and 1997 (o). St Johns County data were
collected for 1972 (,i), 1986 (,2) and 1999 (13). The variables are time specific (tl, t2, t3) and
dynamic (t2-l, t3-2, and t3-i).
Beach Width (BW)
The Brevard County beach width values of the 9-ha sample areas are normally distributed
in 1972 and 1997. The number of monuments with data decreases from 147 points in 1972 to
140 in 1997 indicating monument replacement. The beach is wider between Satellite Beach and
Indiatlantic (monuments 110 to 120), in the area south of Cocoa Beach and in southern Brevard
County (Table 5-1). Changes in beach width over time are more extreme in northern Brevard
County, north of monument 60, particularly adjacent to the Port Canaveral Inlet, where the jetties
have influenced accretion. The average beach width is highest in 1986 at 108.5m, but in the same
year a minimum beach width of 35.7m was also recorded. The maximum beach width increases
79


171
Table H-l 1. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach, Monument
1 to 120), Monument to Dune Height (MDH) ) and dependent variables at 0.05
significance
MDH
MDH, 2
MDH,3
MDH,2.,
MDHu.2
MDH,3.1
MDH,0,
MDHf
POS
UN
-0.3598
0.3599
-
0.3991
-
-
-
-
-0.4038
UN
-
0.3287
-
-
-
-
-
-
-0.2772
UNt
-
-
-
-
-
-
-
-
-
UNa-i
0.4571
-
-0.3996
-0.3430
-
-0.4802
-0.3471
-0.4105
-
UN.3.2
-
-
-
-
-
-
-
-
0.2476
UN.,
-
-
-
-
-
-
-
-
0.2665
UH
-
-
-
-
-
-
-
-
-
UHt2
-
-
-0.3058
-
-
-
-
-
-
UHo
-
-
-
-
-
-0.3136
-
-0.3371
0.5074
UHa.i
0.4944
-
-0.5052
-0.4758
-
-0.5801
-0.4724
-0.4949
0.3673
UH.2
0.3138
-
-
-0.3412
-
-
-
-
0.5676
UHj.,
0.4484
-0.3270
-
-0.4574
-
-0.4076
-0.3486
-0.3462
0.6572
IMP,,
-0.3831
0.3551
-
0.4036
-
-
-
-
-0.4051
IMP,2
-
0.6199
-
0.4688
-0.2987
-
0.4586
-
-0.3396
IMP,3
-
-
-
0.3444
-0.2592
-
0.4928
-
-0.2481
IMP, 2.,
-
0.3814
-
-
-0.4656
-
-
-0.3095
-
IMP,J.2
-
-
-
-
-
-
-
-
-
IMP, j.,
-
-
-
-
-
-
-
-
-
PIM
-
-
-
-
-
-
-
-
-
PIM
-
0.3620
-
-
-0.3106
-
-
-
-
PIMU
-
-
-
-
-
-
-
-
0.2671
PIM,2.,
0.3169
-
-0.3239
-
-0.4337
-0.3648
-
-0.3948
0.3868
pim.2
-
-
-
-
-
-
-
-
0.3968
PIM0.,
-
-
-
-
-
-0.3295
-
-
0.6367
ACC
0.4777
-0.4653
-0.2504
-0.6405
-
-0.4556
-0.5022
-0.4282
0.4872
DACC
0.2810
-0.2888
-0.4682
-0.4145
-
-0.5025
-0.4515
-0.4440
-0.3336
POS
0.5936
-0.5216
-0.2879
-0.6501
-
-0.5125
-0.4701
-0.4270
1.0000
Q,
-
-
-
0.3254
-
-
-
-
-
Cq
-
0.4596
-
0.3907
-
-
-
-
-
Cu
-
-
-
-
-
-
-
-
-
Q2-1
-
0.3881
-
0.3031
-
-
0.4241
-
-
Ct3-2
-
-
-
-
-
-
-
-
Ct3-1
-
-
-
-
-
-
-
-
-
FLUD
0.4898
-0.5425
-0.3559
-0.6188
-
-0.5086
-0.4194
-0.4453
0.9184
FLU, 2
-
-
-
-
-
-
-
-
_
FLUDa
-
-
-
-
-
-
-
_
_
FLUCa
-
-
-
-
-
-
-
-
-
FLUa
-
0.3878
0.3336
0.4982
-
0.3368
0.4125
-
-0.4860
FLUD.3
0.5157
-
-
-0.3453
-
-0.4239
-
-0.4490
0.5705
FLUC.3
-
-
-
-
-
-
-
-
-


58
dependent variable data are not available for Patrick Air Force base. Brevard County data were
considered as two separate areas; Cape Canaveral to the north point of PAFB, (monuments 1 to
71); and, south of PAFB to Sebastian Inlet (monuments 75 to 200). In St. Johns County
dependent and independent variables for the entire county are considered together and in separate
arrays representing the area north of St. Augustine pass (monuments 1 to 122) and Anastasia
Island (monuments 141 to 195). Using ArcGIS the orientation (OR) of the shoreline was digitally
obtained. Each 9-ha sample area was centered on the monument, using the meridian described
earlier. The axis of the meridian was oriented at right angles to the shoreline, determined from
the extent of the GIS land use coverage. Using the angle command the orientation of the leading
edge of the 9-ha sample was determined.
Distance (ACC), Direction (DACC) and Location (ROAD) of Access
The distance of the 9-ha sample area to the nearest access point to the mainland was
considered a potential determinant of development sequencing or geographic weighting, in that
sample areas closer to bridges or access point are likely to have developed before sample areas
further from access. The exact location of the monument was used to derive the distance to
access. In each county the location of causeways and access points was determined using GIS.
The DACC variable adds a direction component to the measurement of distance to the nearest
access point. A positive value represents that the nearest access is to the south and negative, to
the north of the monument.
In Brevard County there are five causeways. State Road 528 reaches the coast at Bennet
Causeway in Cape Canaveral, adjacent to monument 1. State Road 520 accesses the barrier
island between monuments 20 and 21. Pineda Causeway carries State Road 404 and reaches the
coast between monument 75 and 76. State Road 518 crosses the Indian River on Eau Gallie
Causeway at monument 105. The southernmost access to the barrier island in Brevard County is
US 192 at monument 123. In St. Johns County, monument 1 is considered the closest monument
to access to the north. At monument 35, Mikler Avenue also provides direct access to the west.


162
Table H-2. Brevard County Spearman Rank analyses, Dune Height (DH) ) and dependent
variables at 0.05 significance
DH DHe DH,j
DHa.,
DHaa
DHU.,
DH,ot
DHf
OR
UN
-0.2679 -0.3054 -0.2439
-
-
-
-
-
0.4059
UNa
-0.2093 -0.2424 -0.2043
-
-
-
-
-
0.3400
UNa
-
-
-
-
-
0.2172
UNa-,
.
-
-0.1933
-
-0.2402
-
-
UN0-2
0.3021 0.2246 0.2806
-
-
-0.2244
-
-
-0.2843
UN.,
0.1907 -
-
-
-0.2360
-0.2730
-
-
UH
-0.2826 -0.3096 -0.2544
-
-
-
-
-
0.4138
UHa
-0.2282 -0.2351 -0.2037
-
-
-
-
-
0.3162
UH
-0.1818 -
-
-
-
-
-
0.2173
UHa.,
-
-
-0.1888
-
-0.2168
-
-
UHo.2
0.2942 0.2179 0.2731
-
-
-0.2149
-0.1852
-
-0.2804
UH.3-,
-
-
-
-0.1839
-0.2699
-
-
IMP,,
-0.6065 -0.6680 -0.6234
-
-
-
-
-
0.7398
IMPa
-0.6203 -0.6436 -0.6405
-
-
-
-
-
0.7294
IMP,,
-0.6034 -0.6418 -0.6270
-
-
-
-
-
0.7246
IMPa.,
-0.2892 -0.2250 -0.2411
-
-
-
-
-
0.3706
IMPo.2
-
-
-
-
-0.2638
-
-
IMP,,.,
-0.2833 -0.2250 -0.2570
-
-
-
-0.2013
-
0.3976
PIM,,
-0.6100 -0.6510 -0.6208
-
0.2246
-
-
-
0.7148
PIMa
-0.6420 -0.6309 -0.6420
-
-
-
0.1851
-
0.7273
PIMa
-0.6361 -0.6332 -0.6406
-
-
-
-
-
0.7396
PIMa.,
-0.3141 -0.2327 -0.2501
-
-
-
-
-
0.3821
PIM,3.2
-
-
-
-
-0.2667
-
-
PIM,3.,
-0.3242 -0.2406 -0.2826
-
-
-
-
-
0.4228
ACC
0.6154 0.5899 0.5779
-
-
-0.2790
-
-0.1830
-0.7404
DACC
-0.6218 -0.5705 -0.6018
-
-
0.1824
0.1966
0.1459
0.7366
POS
0.8744 0.8440 0.8710
-
-
-0.2310
-0.2308
-
0.4059
c,,
-0.5759 -0.6040 -0.5972
-
0.2231
-
0.1891
-
0.3400
Ca
-0.5751 -0.5787 -0.5733
-
0.1878
-
0.2129
-
0.2172
Ca
-0.5709 -0.5876 -0.5759
-
-
-
-
-
-
Ct2-1
-0.2751 -0.2427 -0.2363
0.1045
-
-
-
-
-0.2843
Ct3-2
-0.1277 -0.1120 -0.1485
-
-
-
-
-
-
Ct3-1
-0.3181 -0.2664 -0.2954
-
-
-
-
-
0.4138
FLUD
-0.7220 -0.6777 -0.7131
-
-
0.2057
-
-
0.3162
FLUa
-0.5742 -0.5603 -0.5792
-
-
-
-
-
0.2173
FLUDo
-0.6357 -0.6210 -0.6499
-
-
0.2079
-
-
-
FLUC,3
-0.4402 -0.3710 -0.3848
-
0.1996
0.3003
-
0.2161
-0.2804


90
Table 5-4. Descriptive statistics, long-term change (LT), orientation (OR) and monument
position from north (POS), distance to access (ACC) and distance and direction to
access
(DACC)
Standard
Kolmogorov-
Count Mean
Deviation
Min.
Max.
Smirnov
0.05
Normality
Brevard County
LT
137
0.3
0.4
-0.2
1.51
0.2260
0.075
Reject
OR
125
168.6
13.6
152.0
195.0
0.1882
0.079
Reject
POS
138
28.9
17.8
0.0
58.3
0.1048
0.075
Reject
ACC
138
6.4
6.3
0
22.4
0.1952
0.075
Reject
DACC
138
-4.7
7.6
-22.4
7.9
0.1347
0.075
Reject
St. Johns, Entire County
LT
164
0.1
1.1
-7.3
2.4
0.2504
0.069
Reject
OR
168
167.0
4.8
153.0
183.0
0.1652
0.068
Reject
POS
136
34.7
21.2
0.0
67.7
0.1048
0.076
Reject
ACC
136
6.6
4.4
0.0
16.9
0.0904
0.076
Reject
DACC
136
0.1
7.9
-13.0
16.9
0.0929
0.076
Reject
St. Johns, North, Ponte Yedra to Vilano Beach, monuments 1 to 121
LT
110
-0.1
0.3
-0.5
2.0
0.2446
0.084
Reject
OR
110
167.3
2.4
157.0
171.0
0.2662
0.084
Reject
POS
81
19.6
12.5
0.0
38.3
0.1337
0.098
Reject
ACC
81
7.7
4.7
0.0
16.9
0.0721
0.098
Accept
DACC
81
2.2
8.8
-13.0
16.9
0.0678
0.098
Accept
St. Johns, Anastasia Island, monuments 141 to 195
LT
45
0.8
1.9
-7.3
2.4
0.2224
0.131
Reject
OR
47
167.2
8.1
155.0
183.0
0.1624
0.128
Reject
POS
44
54.7
5.1
44.8
62.5
0.0806
0.132
Accept
ACC
44
3.5
1.9
0.0
7.3
0.0710
0.132
Accept
DACC
44
-1.2
3.8
-6.5
7.3
0.1285
0.132
Accept
Access (ACC, DACC) Variables
The average distance to access to the mainland in Brevard County is 6.4km and the sample
area furthest from access is 22.4km (Table 5-4). The negative value for the DACC average
indicates more access in the north part of the study area. The average distance to access to the
mainland in St. Johns County is 6.6km and the sample area furthest from access is 16.9km. The
value for the DACC average is close to zero, indicating that that the direction to the nearest
access point is as likely to be north as south. When separated by geomorphic unit, however, it is
further to access points from northern St. Johns County (7.7km) than on Anastasia Island
(3.5km).


115
Associations between future land use and beach width occurred in St. Johns County. The
density established in the 1972 future land use plan has a functional relationship with the 1972
beach width, shoreline orientation and the distance and direction to access. Higher densities were
planned in areas with wider beach widths, oriented north-south and closer to access. The positive
DACC value indicates the direction to the closest access is to the south. Almost half of the
explanation for higher densities adopted in 1972 is a function of wider beaches, location close to
access points from the barrier island and orientation.
St. Johns County, Entire Coastline-Potential Residential Density, 1979
Comprehensive Plan (FLUD,i)
FLUD = 9.211 + 0.022 BW 0.058 OR + 0.085 DACC
(n=124, R2 = 0.498)
FLUD,i = Potential Residential Density, 1979 Comprehensive Plan (units per hectare)
BW u = 1972 Distance from NGVD to Maximum Dune Height (m)
OR = Shoreline Orientation (degrees from north)
DACC = Distance and Direction from Access Point
Hypothesis 2: The Dynamic Geomorphology and Human Variables
Hypothesis 2a proposes that the dynamic geomorphology indicators influence the actual
human variables and are negatively correlated to human variables (Lundberg and Handegard,
1996; McMichael, 1977; Miller, 1980). In Brevard County the long-term change (LT),
orientation (OR) of the shoreline and the 1972 to 1997 absolute change in the beach width
(Monument to NGVD) (BW,ot) were variables that influenced the percentage impervious area
(PIM) in 1997.
Brevard County, Entire County-1997 Percent Impervious Area (PIM,3)
PIM,3 = 379.003 -0.124 BWtot-39.611 LT +2.584 OR
(n= 110, R2 = 0.552)
PIMj3 = 1997 Percent Impervious Area (%)
BW tot = Total Beach Width Change, absolute value (m)
LT = Long term Change, 1870-1999, (m)
OR = Shoreline Orientation (degrees from north)
The 1997 percentage impervious area is explained by lower total beach width change, so a
less dynamic coastline, and areas where long-term change is lower. The conclusion that can be


199
PHILLIPS, J. D., 1997. Humans as geomorphological agents and the question of scale. American
Journal of Science, vol. 297, pp. 98-151.
PHILLIPS, J. D., 2005. Entropy analysis of multiple scale causality and quantitative causal shifts
in spatial systems. Professional Geographer, vol. 57, No. 1 pp. 83-93.
PILKEY, O. K., 2003. A celebration of the worlds Barrier Islands._ Columbia University Press,
New York, NY, 309 pp.
PILKEY, O. K., and CLAYTON, T. D., 1989. Summary of beach renourishment experience on
the US East Coast barrier islands. Journal of Coastal Research, vol. 5 1, pp. 147-159.
PILKEY, O. K., and DIXON, K. L., 1996. The Corps and the Shore. Island Press, Washington D.
C, 272 pp.
PIRKLE, E. C., YOHO, W. H., and HENDRY, C. W., Jr., 1970. Ancient sea level stands in
Florida. Geographical Bulletin No. 52, Bureau of Geology, Florida Department of Natural
Resources, pp. 1-33.
RABAC, B., 1986. The City of Cocoa Beach, the First Sixty Years. Apollo Books, Winona,
Minnesota, 179 pp.
RAHN, J. L., 2001. Coastal anthropogeomorphology; human development and beach profile
changes on two Florida panhandle barrier islands, 1973 to 1996. Ph. D. Dissertation,
University of Florida, Gainesville, FL., 378 pp.
REESMAN, A. R., 1994. Coastal hazards risk, vulnerability and property damage mitigation
recommendations, Fernandina Beach, Florida. Vanderbilt University Masters Thesis,
Nashville, TN, 82 pp.
REPS, J. W., 1992. The Making of Urban America, A History of City Planning in the United
States. Princeton University Press, Princeton, NJ, 574 pp.
ST. JOHNS COUNTY, 1979. St. Johns County comprehensive plan. St. Johns County
Department of Planning, St. Augustine, Florida, 142 pp.
ST. JOHNS COUNTY, 2002. Habitat conservation plan, coastal St. Johns County. St. Johns
County Department of Planning, St. Augustine, Florida, 99 pp, with appendices.
ST. JOHNS COUNTY GROWTH MANAGEMENT, 1993. St. Johns County comprehensive
plan. St. Johns County Department of Planning, St. Augustine, Florida, numbered in
sections.
SCHUMM, S. A., 1991. To Interpret the Earth: Ten Ways to be Wrong. Cambridge University
Press, Cambridge, England, 133 pp.
SCHWARTZ, M. L., 1971. The multiple causality of barrier islands. Journal of Geology, vol. 70,
pp. 91-94.
SHERMAN, D. J., and BAUER, B. O., 1993. Coastal geomorphology through the looking glass.
Geomorphology, vol. 7, pp. 225-249.


49
indication how the dune field characteristics have altered over time and reflects the importance of
the interaction of the foreshore and dune systems (Psuty, 1988).
Monument to Maximum Dune Height (MDH)
The Distance to Maximum Height is a measure from one geomorphic
characteristic, Maximum Dune Height to NGVD. The Monument to Maximum Height
measures a static point on the profile, the monument, to a dynamic geomorphic feature,
the Maximum Dune Height. Psuty and others (1988) found that the position of the dune
is less dynamic than other geomorphic features. They also showed that the inland
movement of dunes does necessarily exhibit a direct relationship with the dynamics of
the beach, so that landward migration of the dune may not necessarily indicate that the
foreshore is eroding. This variable is particularly important where the Beach Width
Index and NGVD to Maximum Dune height are impacted by structures. In locations
where shore-parallel structures are present, geomorphic changes in the profile seaward
of the structure will be impacted. On such profiles the Monument to Maximum Dune
Height may represent the part of the profile where sediment movement is occurring.
Long Term Shoreline Change (LT)
Historical shoreline change has been calculated at each monument by the State of Florida
and is intended to be used to assist in growth management and regulatory programs (Foster and
Savage, 1989, pp. 4434). Long-term shoreline change is influenced by longshore sediment
transport, sand supply, wave climate, geographic features such as estuaries and man-made
structures and nearshore reefs. The FDEP, using the end point, least squares, and rate averaging
methods, calculates long-term shoreline change between 1872 and 2000 (Foster et al., 1999,
Foster et al., 2000). These data were available for St. Johns County (Figure 4-2). Long-term
change rates for Brevard County were calculated using rate averaging and end point rates (Figure
4-4).


195
FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION, 2004a. Hurricane Frances
and hurricane Jeanne, post storm concisions and coastal impact report. Division of Water
Resources Management, Bureau of Beaches and Coastal Systems, October 2004,
Tallahassee, FL. 93 pp.
FLORIDA DEPARTMENT OF ENVIRONMENTAL PROTECTION, 2004b. 2004 Hurricane
recovery plan for Floridas beach and dune system. Division of Water Resources
Management, Bureau of Beaches and Coastal Systems, November 30, 2004, Tallahassee,
FL. 67 pp.
FOSTER, E. R., 1992. Thirty year erosion projections in Florida. Proceedings of 23rd
International Conference on Coastal Engineering, American Society of Civil Engineers,
NY, USA, pp. 2057-2070.
FOSTER, E. R., 2002. Proposed minimum standards for comparing shoreline results with data.
Florida Department of Environmental Protection, Office of Beaches and Coastal Systems,
February 2002, 9 pp.
FOSTER, E. R., and SAVAGE, R. J., 1989. Methods of historical shoreline analysis. Coastal
Zone 89, Proceedings of the Sixth Symposium on Coastal and Ocean Management,
American Society of Civil Engineers, NY, USA, pp. 4434-4448.
FOSTER, E. R., SPURGEON, D. L., and CHENG, J., 2000. Shoreline Change Rate Estimates,
St. Johns County. Report No BCS-00-03, Florida Department of Environmental Protection,
Office of Beaches and Coastal Systems, 72 pp.
FOTHERINGHAM, A, S., and BRUNSDON, C., 2004. Some thoughts on inference in the
analysis of spatial data. International Journal of Geographic Information Science, vol. 18,
no. 5, pp. 447-457.
FRENCH, J. R., SPENCER, T., and REED, D., 1995. Editorial- geomorphic response to sea-
level Rise: existing evidence and future impacts. Earth Surface Processes and Landforms,
vol. 20, pp. 1-6.
GALGANO, F. A., and LEATHERMAN, S. P., 1991. Shoreline change analysis: a case study.
Coastal Sediments 91, pp. 1043-1053.
GARES, P. A., 1987. Eolian sediment transport and dune formations on undeveloped and
developed shorelines. Doctoral Thesis, Rutgers, the State University of New Jersey, 394
pp.
GARES, P. A., 1988. Factors affecting eolian sediment transport in beach and dune
environments. Journal of Coastal Research, Special issue no. 2, pp. 121-126.
GARES, P. A., 1990. Predicting flooding probability for beach/dune systems. Environmental
Management, vol. 14, pp. 115-123.
GILBERT, G, K, 1885. The topographic features of lake shores. US Geological Survey, 5th
Annual Report, pp. 69-123.


TABLE OF CONTENTS
page
ACKNOWLEDGMENTS iv
LIST OF TABLES viii
LIST OF FIGURES xiii
ABSTRACT xv
1. INTRODUCTION 1
Research Purpose 4
2. LITERATURE REVIEW 5
Use of Spatial and Temporal Data in Geomorphology 6
Techniques and Data; GIS and Aerial Photography 9
Beach Profiles and Applicability 12
Population and the Coast 15
Contemporary Coastal Settlement Patterns 16
Legislated Incentives for Development 17
Land Use Planning in Florida 21
Research Hypotheses 23
3. STUDY AREA 26
Geomorphological Characteristics of the Florida Coast and Study Area 27
Barrier Islands 28
Sediments 30
Dunes 30
Tide, Wave and Longshore Drift Characteristics 31
Storms 33
Winter Storms 36
Development History 37
Inlets 40
Coastal Structures 41
Renourishment of the Shoreface 42
4. METHODOLOGY 44
Actual Geomorphology Variables 46
Beach Width Index (BW) 46
v


51
Table 4-4. Profile measurement metadata, monuments 1 to 209, St. Johns County
St. Johns County-1972
Date
Monument Number
Range
8/1/72
182-209
8/2/72
155-181
8/3/72
141-154
8/15/72
123-140
8/28/72
103-122
8/30/72
63-102
8/31/72
41-62
9/5/72
33-40
9/6/72
1-32
St. Johns County-1986
Date
Monument Number
Range
7/15/86
1-7
7/16/86
8-16
7/17/86
18-26
7/18/86
17
7/28/86
27-30
7/30/86
31-32, 36
7/31/86
37-40,44, 45
8/1/86
33-35,41-43,46-50
8/12/86
51,52,91-98
8/13/86
54-56
8/14/86
57-60
8/15/86
61,62
8/19/86
63,99-106
8/20/86
64-66
8/26/86
67-76
8/27/86
77-90
9/9/86
107-109,123-125
9/1086
110-117,126-135
9/11/86
118-122, 136-143
9/12/86
200-209
9/20/86
143 A
9/23/86
144-153
9/24/86
154-166
9/25/86
167-171
10/10/86
172-178
10/23/86
179-188
11/4/86
189-199
St. Johns County-1999
Date
Monument Number
Range
2/25/99
1-3,7-13
2/26/99
4-6,14-21
3/16/99
22-36, 58-68
3/17/99
37-57, 69-80
3/18/99
81-93,109-121
3/19/99
94-121
3/30/99
122-123
3/31/99
124-125
4/1/99
126-134
4/2/99
135-137
4/13/99
138-141, 147, 151-
154
4/14/99
142-146,148-150,
155-158
4/15/99
159-166
4/16/99
167-170
4/27/99
171-185
4/28/99
186-191
4/28/99
192-196, 197A, 198
4/30/99
197,199-207


71
** COMMERCIAL
HIGH DENSITY
RESIDENTIAL
LA INSTITUTIONAL
ALOW\MEDIUM
RESIDENTIAL
RIGHTS-OF-WAY
VACANT
WATER
Permitted
Density (mid
range) Area =
26 Potential
Residential
Units
Figure 4-13. Determination of future land use total units (FLU) in 9-ha sample area
Figure 4-14. Determination of future land use density of units (FLUD) in 9-ha sample area


xml version 1.0 encoding UTF-8
REPORT xmlns http:www.fcla.edudlsmddaitss xmlns:xsi http:www.w3.org2001XMLSchema-instance xsi:schemaLocation http:www.fcla.edudlsmddaitssdaitssReport.xsd
INGEST IEID E9GDC0Y26_8A5LXG INGEST_TIME 2014-11-05T21:40:28Z PACKAGE AA00014272_00001
AGREEMENT_INFO ACCOUNT UF PROJECT UFDC
FILES


186
APPENDIX J. Continued
Table J-4. Future land use units (FLUt3) Brevard County, 1997
Han Intpri1 pnt Q V orioKIp
Dep.
Variable
Intercept
P,
Variable
P2
Variable
FLU0
(n=105)
0.517
608.833
-76.111
DHjj
-0.388
BW
,, ROAD
Dependent Variable FLU o
Adjusted R-Squared
0.5173
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
608.8331
49.37215
12.3315
0.000000
Reject Ho
1.000000
DHo
-76.11123
9.874031
-7.7082
0.000000
Reject Ho
1.000000
BWtfROAD
-0.3883898
8.282633E-02
-4.6892
0.000008
Reject Ho
0.996375
T-Critical
1.983264
F-Ratio
57.2567
0.000000
1.000000
N= 105
FLU ,3 = Potential Units, 1999 Comprehensive Plan
DH t3 = 1997 Dune Height (m)
BW ^ROAD = 1986 Beach Width (m) weighted by the position of the parallel access (3-
<100m inland, 2-100m to 200m inland, l->200m inland, 4 more than 1 parallel access road)
Table J-5. Potential residential density, 1979 Comprehensive plan (FLUDti) St. Johns County
Dep.
Variable
R"
Intercept
P.
Variable
Pr
Variable
Pr
/ ariable
FLUD
(n=124)
0.498
9.211
0.022
BW
-0.058
OR
0.085
DACC
Dependent Variable FLUD,i
Adjusted R-Squared 0.4980
Independent
Regression Standard
T-Value
Prob
Decision
Power
Variable
Coefficient Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
9.21105 2.556698
3.6027
0.000458
Reject Ho
0.946737
BW u
2.233969E-02 3.589396E-03
6.2238
0.000000
Reject Ho
0.999987
OR
-5.830832E-021.532162E-02
-3.8056
0.000223
Reject Ho
0.965260
DACC
8.473538E-02 9.816629E-03
8.6318
0.000000
Reject Ho
1.000000
T-Critical
1.979764
F-Ratio
42.0016
0.000000
1.000000
N=124
FLUD,i = Potential Residential Density, 1979 Comprehensive Plan (units per hectare)
BW ,i = 1972 Distance from NGVD to Maximum Dune Height (m)
OR = Shoreline Orientation (degrees from north)
DACC = Distance and Direction from Access Point


81
Table 5-1. Descriptive statistics, beach width (BW)
Count Mean
Standard
Deviation
Min.
Kolmogorov
Max. Smirnov
0.05
Normality
Beach Width (Brevard County)
BW
147
98.8
27.6
41.4
149.9
0.0399
0.073
Accept
BWu
141
103.6
28.9
35.7
198.7
0.0833
0.074
Reject
BWu
140
101.8
31.9
40.6
267.8
0.0651
0.075
Accept
BW,;.,
142
5.5
24.1
-149.9
126.6
0.1947
0.074
Reject
BW.3-2
138
-3.4
28.4
-163.8
155.3
0.1968
0.075
Reject
BWo.,
143
2.2
29.2
-148.5
196.7
0.2090
0.074
Reject
BWI0|
138
28.0
39.7
1.2
305.1
0.2589
0.075
Reject
BWf
138
0.1
0.7
-1
1
0.1200
0.075
Reject
Beach Width (St. Johns, Entire County)
BW
165
79.7
19.6
35.4
140.6
0.1784
0.069
Reject
BW0
167
95.4
34.8
30.4
202.8
0.2011
0.068
Reject
BWt,
165
86.3
37.6
30.9
198.5
0.2247
0.069
Reject
BW0.,
164
15.4
20.1
-17.1
80.1
0.1141
0.069
Reject
BW.3.2
165
-9.7
14.8
-65.1
45.4
0.0761
0.069
Reject
BWi3.,
163
5.3
23.0
-55.7
76.1
0.1572
0.069
Reject
BW,0,
162
32.8
21.4
2.8
133.2
0.1386
0.069
Reject
BWf
162
0.01
0.7
-1.0
1.0
0.0966
0.069
Reject
Beach Width (St. Johns, North 1 to 121)
BW
111
71.8
8.3
49.0
99.1
0.0851
0.084
Reject
BWc,
110
81.4
117
58.3
139.5
0.0680
0.084
Accept
BW
110
68.7
12.6
44.9
132.7
0.1008
0.084
Reject
BW.,
no
9.7
12.5
-17.1
68.0
0.0809
0.084
Accept
BW,3.2
110
-12.7
13.4
-65.1
45.4
0.1303
0.084
Reject
BWU.,
110
-2.9
12.6
-29.4
35.2
0.0870
0.084
Reject
bwm
110
27.8
17.7
2.8
133.2
0.1282
0.084
Reject
BWf
110
-0.2
0.6
-1.0
1.0
0.0833
0.084
Accept
Beach Width (St. Johns, Anastasia Island, 141 to 195)
BW
43
106.1
16.2
62.7
140.6
0.0759
0.134
Accept
BW,,
46
140.4
31.5
49.4
202.8
0.0645
0.129
Accept
BWi3
46
136.6
32.5
63.9
198.5
0.0645
0.129
Accept
BWq.,
43
35.9
22.2
-10.7
80.1
0.0634
0.134
Accept
BWi3.2
46
-3.8
17.2
-50.5
36.0
0.0862
0.129
Accept
BW,3.,
43
31.2
24.8
-42.3
76.1
0.0996
0.134
Accept
BWI01
43
49.7
22.0
11.7
102.2
0.0940
0.134
Accept
BWf
43
0.6
0.5
-1.0
1.0
0.2310
0.134
Reject


2
have a basic understanding of the nature of the inshore zone. This work explores the extent to
which the understanding of the local geomorphology has policy direction and resulting
infrastructure and development. The existing concentrations and projected influx of coastal
residents make these patterns of development an important focus for geomorphologists, land
planners and coastal managers.
Florida has the longest shoreline in the coterminous United States, and it is fringed by
barrier islands. Florida has 1,176 km of coastal barriers (U. S. Department of Interior, 1983); 741
km (63 %) was developed in 1983. The coast of the United States has 295 barriers (Reesman,
1994) and Florida has 80 barrier islands containing 189,000 hectares of land (Leatherman, 1982).
Coastal development in Florida varies from the high-rise condominium canyons of
southeast Florida, to the 1950s beach shacks of the panhandle. Traditionally coastal development
began inland of passes giving settlers access to the ocean. Barrier islands were not the areas of
choice for settlement because they were isolated and lacked access. Once bridges were built
development progressed onto and along the barrier islands. The influence of the geomorphology
of the locale is important for coastlines containing a mix of single-family homes, multi-family
condominium and small commercial areas. The coastal geomorphology and development
patterns of two coastal areas (Brevard county in central Florida and St. Johns County in northeast
Florida) are investigated during three time periods. The two coastal areas investigated are long
inhabited and historically significant.
Use of the coast has evolved over time. This brief review of ancient development and
coastal habitation provides historical background for the 27-year study period (1972 to 1999).
Lencek and Bosker (1998) chronicled the evolution of coastal use, characterizing it as the
transformation of the beach from an alien inaccessible, and hostile wilderness devoted to
conquest, commerce and exploration, and the primal customs of tribal cultures, into a
thriving, civilized, pleasure- and recreation-oriented outpost of Western life. Lencek and
Bosker, 1998, pp. xx.


X1972 1986 1997
Figure 1-2. Brevard County maximum height to NGVD with trend, 1972-1997 (DHBW, DHBWu, DHBW,,)


65
adjacent areas to point or discrete data has been noted in Rahn (2001) and Mossa and McLean
(1997). In situations where monuments are placed precisely, the development variables in the 9-
ha sample areas will encompass the entire county coastline. However, the irregular spacing and
replacement of monuments causes the sample areas to be noncontiguous.
The areas unavailable for development and retained in their natural state, such as the areas
west of A1A in Guana River State Park, are excluded in the calculation of units per hectare and
percentage impervious area. The Intracoastal Waterway, canals or water bodies are also excluded
(Appendix D). Digital orthophotography was used for the Brevard and St. Johns counties in 1997
and 1999 and in the 1970s and 1980s variables were extracted from the 1:1200 aerial
photography. This photography and future land use data are analyzed in conjunction with the
monument locations using GIS.
Dwelling Units (UN) and Dwelling Units per Hectare (UH)
The number of units variable (UN) and the number of residential dwelling units per hectare
(UH) are derived for each monument with a continuous geomorphic record. These variables
include units of mobile homes, and multifamily units up to 8 units per building. The number of
units is determined from the aerial photography and field investigations. The number of hotel
rooms cannot be determined from the photography. Hotels, motels and condominiums are not
included in the calculation of units. These structures are included as commercial acreage in the
calculation by use. The number of units per hectare does not include any measure of commercial
activity.
Figure 4-11 shows that 18 units, in this example single-family residential, were recorded in
the 9-ha sample area for a UN of 18. The density is the number of units per hectares of
residential land. In this case if there are 3 hectares of residential land the 18 units in 3 ha
represents a UH of 6 units per hectare.


40
Atlantic
Avenue
Motel Pool
-Monument
32
Gas Station
4th Street N
Figure 3-4. Urbanization at monument 32, Brevard County, 1997
On Anastasia Island large condominia and hotels were beginning to be constructed on
previously vacant tracts. Single-family homes were also removed for these projects and two of
the three travel trailer parks were replaced with multi-story residential structures and associated
parking and amenities, such as pools and tennis courts. South of Matanzas Inlet homes were built
on the spit. By 1999 northern St. Johns County was developed with single-family homes, and the
influence of the Jacksonville metropolitan area is evident. Homes in this area are large and
smaller homes have been enlarged or replaced.
Inlets
Brevard County has two inlets, Port Canaveral to the north of the study area and Sebastian
Inlet that marks the boundary with Indian River County (Figure 3-1). Sebastian Inlet is man
made and has been maintained since 1948 by dredging and the installation of jetties (Wang and
Lin, 1992). The Port Canaveral Inlet was stabilized in the 1940s. It has been theorized that the


188
APPENDIX J. Continued
F-Ratio 31.5452 0.000000 1.000000
N=113
FLU t3 = Potential Units, 1999 Comprehensive Plan
LTSW = Long term Change, 1870-1999, (m) Structures Dummy (1-structures present, 0-no
structures)
BW t2 ROAD-1986 Distance from Monument to NGVD (m) weighted by the position of the
parallel access (3-<100m inland, 2-100m to 200m inland, l->200m inland, 4 more than 1 parallel
access road)
Table J-8. Future land use units (FLU o) St. Johns County south, Monument 141 to Monument
198, 1999
Dep.
Variable
R2
Intercept
Pi
Variable
P2
Variable
P3
Variable
FLUU
N=50
0.611
-195.593
0.478
BWC
-5.080
DH0.,
1.041
OR
Dependent Variable FLUt3
Adjusted R-Squared 0.6114
Independent
Regression
Standard
T-Value
Prob
Decision
Power
Variable
Coefficient
Error
(Ho: B=0)
Level
(5%)
(5%)
Intercept
-195.5933
62.59332
-3.1248
0.003046
Reject Ho
0.864424
BW a
0.4781096
5.995853E-02 7.9740
0.000000
Reject Ho
1.000000
DH t3.j
-5.080557
2.069582
-2.4549
0.017850
Reject Ho
0.671667
OR
1.04148
0.3812434
2.7318
0.008845
Reject Ho
0.762895
T-Critical
2.011741
F-Ratio
27.2269
0.000000
1.000000
N=50
FLU ,3 = 1999 Potential Future Land Use, Comprehensive Plan (units)
BW a = 1986 Beach Width (m)
DHt3-i = Change in Maximum Dune Height 1972 to 1999 (m)
OR = Shoreline Orientation (degrees from north)
Hypothesis 3: There are temporally lagged relationships between the actual and
dynamic geomorphology variables and the human variables. (Nordstrom, 1987;
Van Der Wal, 2004).
Table J-9. Future land use density (FLUDt3) St. Johns County south, Monument 141 to
Monument 198, 1999
Dep.
Variable
R2
Intercept
Pi
Variable
FLUDo
(n=53)
0.659
1.953
0.000001
(BW s)3


LIST OF FIGURES
Figure page
2-1. Study areas: Brevard and St. Johns counties, Florida 3
3-1. Coastal municipalities and geomorphic characteristics, Brevard County, Florida 32
3-2. Coastal municipalities and geomorphic characteristics, St. Johns County, Florida 35
3-3. Urbanization at monument 32, Brevard County. A) 1974. B) 1986 39
3-4. Urbanization at monument 32, Brevard County, 1997 40
4-1. Beach profile and geomorphic variables 45
4-4. Calculation of long-term shoreline change, end point and least square fit methods 54
4-5. Calculation of long-term shoreline change, rate-averaging method 54
4-6. Determination of highway location (ROAD) variable 60
4-7. Beach width dynamic geomorphology variable 61
4-9. Profile revision diagram, monument moved landward (to west) 62
4-10. Profile revision diagram, monument moved seaward (to east) 63
4-11. Determination of total units (UN) in 9-ha sample area 67
4-12. Determination of total impervious area (IMP) in 9-ha sample area 69
4-13. Determination of future land use total units (FLU) in 9-ha sample area 71
4-14. Determination of future land use density of units (FLUD) in 9-ha sample area 71
5-1. St. Johns County beach width variations, 1972-1999, (BWt), BW^, BW) 82
5-2. Brevard County beach width variations, with trend 1972-1997, (BWtl, BWt2, BWt3) 83
5-3. Brevard County maximum dune height variations, 1972-1997 (DH,i, DHo, DHo) 85
5-4. St. Johns County maximum dune height variations with trend, 1972-1999 (DHti, DHt2, DHt3)86
5-5. Brevard County total units, 1972-1997, with potential units (UN,i, UNg, UNg, FLU,3) 96
xiii


| X1972 Maximum Height D1986 Maximum HeigM~T999 Maximum Height
CO
Os
Figure 5-4. St. Johns County maximum dune height variations with trend, 1972-1999 (DH,i, DHt2, DHt3)


18
Individuals can therefore purchase or construct residences, speculate on rental income, and use
them as tax deductions if they are unsuccessful. Revisions to the federal tax code permitting the
one-time exemption of capital gains for homeowners over 55 may have also encouraged retirees
to relocate to coastal areas (Vernberg et al., 1996).
The National Flood Insurance Program was enacted by the National Flood Insurance Act
(Table 2-4) of 1968 (Von der Osten, 1993) provides flood insurance to property owners in areas
where the local government has adopted and enforces floodplain management standards to reduce
potential flood damage (Bellomo et al., 1999). Local governments may use zoning restrictions,
subdivision regulations, building code compliance and minimum elevations to mitigate potential
flood damage. Although it has been argued that the restrictions required to be adopted by local
governments to participate in the NFIP increase the cost of development in the coastal zone, the
availability of flood insurance serves to enable development that would otherwise be too costly to
insure (Von der Osten, 1993). In Florida, insurance under the National Flood Insurance Program
is a requirement for eligibility to request public disaster assistance funds (South Florida Regional
Planning Council, 1989)
The Coastal Construction Control Line (CCCL) is set to reduce the potential for structural
damage and beach erosion (Von der Osten, 1993). The CCCL are adopted on a county-by-county
basis, and state permits are required from the Florida Department of Environmental Protection
(DEP) for construction or excavation seaward of the line. The line is calculated by elevation in
relation to storm and hurricane tides, predicted maximum wave up rush, contours (including
offshore), vegetation, erosion trends, dune line, and existing development. There are also
exemptions to permits, most relevant to this research are the structures completed before the
establishment of the first line in 1972 (Von der Osten, 1993). Any changes to structures must be
contained within the original footprint. Structures that are justified to DEP and seaward of the
CCCL must be designed to withstand a 100-year storm event, wind velocity of 95.5 km/hr.
Structures must also be elevated above the calculated breaking wave crests or wave uprush of a


193
CLARK, R. R., 1999. Beach conditions in Florida -- A statewide inventory and identification of
the beach erosion problem areas in Florida. Beaches and Shores Technical and Design
Memorandum, 11th Edition, 88 pp.
COLLIER, C. A., ESHAGHI, K., COOPER, G., and WOLFE, R. S., 1977. Guidelines for
beachfront construction with special reference to the Coastal Construction Setback Line.
Florida Sea Grant, Report No. 20, 72 pp.
CONWAY, T. M., NORDSTROM, K. F., 2003. Characteristics of topography and vegetation at
boundaries between the beach and dune on residential shorefront lots in two municipalities
in New Jersey, USA. Ocean and Coastal Management, vol.46, no. 6-7 pp. 635-648.
CROWELL, M., HONEYCUTT, M., and HATHEWAY, D., 1999. Coastal erosion hazards
study: phase one mapping. Journal of Coastal Research, Special Issue 28, pp. 10-20.
CROWELL, M., LEIKEN, H., and BUCKLEY M. K., 1999. Evaluation of coastal erosion
hazards study: an overview. Journal of Coastal Research, Special Issue 28, pp. 2-9.
DAVIDSON-ARNOTT, R., and KREUTZWISER, R., 1985. Coastal processes and shoreline
encroachment: implication for shoreline management in Ontario. The Canadian
Geographer, vol. 29, no. 3, pp. 256-262.
DAVIS R. A., Jr., 1997. Regional coastal morphodynamics along the United States Gulf of
Mexico. Journal of Coastal Research, vol. 13, no.3 p. 595-604.
DAVIS, R. A., Jr., and BARNARD, P. L., 2000. How anthropogenic factors in the back-barrier
area influence tidal inlet stability: Examples from the Gulf Coast of Florida, USA.
Geological Society Special Publication, No.175, pp. 293-303.
DAVIS R. A., Jr., HIE, A. C., and SHINN, E. A., 1992. Holocene development on the Florida
peninsular. In Davis R. A., Jr., editor Quaternary Coasts of the United States: Marine and
Lacustrine Systems, SEPM, Society for Sedimentary Geology, Special Publication No. 48,
pp. 193-211.
DAVIS, R. E., and DOLAN, R., 1993. Noreasters. American Scientist, vol. 81, no. 5, pp. 428-
439.
DEAN, C., 1999. Against the Tide, the Battle for Americas Beaches. Columbia University Press,
New York, NY, 279 pp.
DEAN, R. G., and DONOHUE, K. A., 1998. The 1996 Beach Nourishment at Two Sites on St.
Augustine Beach: Monitoring Results and Interpretation. In Proceedings of the 11th
Annual National Conference on Beach Preservation Technology, Florida Shore and Beach
Preservation Association, Feb. 4-6. St. Petersburg, FL, 1998, pp. 43-60.
DEAN, R. G., and MALAKAR, S. B., 1999. Projected flood hazard zones in Florida. Journal of
Coastal Research, Special Issue 28, pp. 85-94.
DOLAN, R., 1976. Barrier beachfronts. Technical proceedings of the 1976 Barrier Island
Workshop, Annapolis, Maryland, May 17-18, 1976, The Conservation Foundation, pp. 76-
85.


56
Database (http://hightide.bcs.tlh.fl.us/counties/HSSD/readme/read.mel) and published long term
change rates (Olsen and Buckingham, 1989) and are shown in Appendix F. The Shoreline
Position Database directory contains 150 years of shoreline data for each county. For Brevard
County the earliest records are shown below. Where a span of years was indicated the latest
record was used. The end point method noted above was used to determine the long-term change
rates for Brevard County (Figure 4-3) and the extent of the record eliminates the extremes of
variability from the more recent data (McBride and Byrnes, 1997; Esteves, 1997).
The shoreline position from the monument to the mean high water (MHW) level is
indicated, which is a similar measure to the beach width variable in this research. The MHW
position has been determined by FDEP from USGS topographic maps, photography and FDEP
profile surveys. Inaccuracies noted include high wave activity (specifically in the 1980 data) and
sun glare that would influence aerial photo interpretation. Aerial photography is the basis of
maps since 1920. Before 1920 plane table surveying was used (Foster, 1996). The data from
1970 is not recommended for use in Brevard County without aerial verification. Not
withstanding the limitations, the extent of the long-term data are useful and the only known
source of long-term data (Galgano and Leatherman, 1991).
Olsen and Buckingham (1989) prepared rate averages from the earliest Brevard County
record to 1986. The rate average and end point rates for all points in Brevard County vary from
each other by 3 cm. The average value of the derived end point rate and rate average value was
determined. This value for each monument was averaged with the rates immediately to the north
and south, if available, as recommended by Foster and others (2000).
Coastal Structures (SW) and Renourishment Projects (RN, RND)
Each monument location is reviewed for the presences of shoreline protection structures
(St. Johns County, 2002; Bodge and Savage, 1989). Structures will impede the transfer of
sediment from the foreshore to the dune system (Carter 1988; Gares, 1987; Nordstrom, 1994) and
prevent the Dune Height variable from reflecting geomorphic processes. The presence of


67
impervious area, such as parking facilities, is calculated from the aerial photography using GIS.
The number of single-family units is converted to a standard impervious area. Florida
Stormwater Management professionals recognize 213.7 m2 per unit and 92.9 m2 per mobile
home as an estimate of impervious area, including buildings and driveways in the calculation of
fees (Sumwashe, 2000). In Brevard County the established Stormwater Management Utility
uses 232.3 m2 as a proxy for the impervious area for each single-family unit. The total recorded
impervious (IMP) area is converted to a percentage of the 9-ha area available for development
(PIM) adjacent to each monument.
Figure 4-11. Determination of total units (UN) in 9-ha sample area


9
Scale of investigation is as important as time period when analyzing of the coastal
environment. A small portion of a barrier island cannot be considered in isolation, any more than
a single barrier island can be considered without those adjacent to it (Schwartz, 1971; Shideler
and Smith 1984). Davis (1997) showed varied in shoreline dynamics along the Gulf of Mexico
coast. If only a small portion was considered the extrapolated results would have been erroneous.
Dolan and others (1991) showed the need to consider erosion rates when selecting an area. Gares
(1990) considered the whole coast of New Jersey, rather than a small area. This research was
used to mitigated conclusions about specific areas that may have been generalized or too specific.
Many of the geomorphic data used in this research are secondary, collected by the State of
Florida, and the importance of field evaluation cannot be underestimated (Lucas 1996). Aerial
photography and field verification are crucial to understanding local dynamics not reflected in
mere data analyses (Foster and Savage, 1989). The use of secondary data necessitates vigilance.
Users must investigate the suitability of the data for the interpretations made. In this research the
secondary data are considered robust because the organization that compiles the data (the Florida
Department of Community Affairs) is constant over time. Variation in data by local jurisdiction
is one factor affecting local responses to geomorphology; this variation may be an appealing
dynamic of the research.
Techniques and Data; GIS and Aerial Photography
Geographic Information Systems (GIS) are tools that enhance and broaden the
opportunities of geomorphology and together with field studies offer a robust synergistic design
to explore a host of research questions associated with landscape characterization and the linkage
of scale, pattern and process (Butler and Walsh, 1998, pp. 179.) GIS can be used to assess
landscape units spatially, to evaluate geomorphic patterns and spatial interactions, and to illustrate
spatial relationships among variables (Kriesel and Harvard, 2001). GIS coverages incorporating
remotely sensed and aerial data have expanded the geographic capacity for analyses in both
spatial and temporal contexts. Lucas (1996) describes coastal data as being four dimensional:


170
Table H-10. St Johns County Spearman Rank analyses (Ponte Vedra to Vilano Beach, Monument
1 to 120), Dune Height (DH)) and dependent variables at 0.05 significance
DH
DH,2
DH,j
dhi2.,
DH,3.2
DH,3.,
DH,ot DH,
OR
UN
-0.3624
-0.4425
-0.3680
-
-
-
-
-
UN
-0.2830
-0.3780
-0.2961
-
-
-
-
-
UNt
-
-0.2556
-
-
-
-
-
-
UNa.,
-
-
-
-
-
-
-
-
UNl3-2
-
-
-
-
-
-
-
-
UNa.,
-
-
-
-
-
-
-
-
UH
-
-
-
-
-
-
-
-
UHc
-
-
-
-
-
-
-
-
UHU
-
-
-
-
-
-
-0.2660-
-
UHa.,
-
-
-
-
-
-
-
-
UH,3.2
0.2451
0.3268
0.2901
-
-
-
-0.2445-
-
UHb.,
0.2835
0.3580
0.2898
-
-
-
-0.3642-
-
IMP,,
-0.3814
-0.4558
-0.3894
-
-
-
-
-
IMP
-0.4611
-0.4809
-0.4260
-
-
0.2634
-
-
IMPa
-0.3577
-0.3666
-0.2880
-
0.2851
0.3029
0.2586 0.3022
-
IMPa-i
-
-
-
-
-
-
-
-
IMP,3.2
-
-
-
-
-
-
-
-
IMP,3.,
-
-
-
-
-
-
-
-
PIM
-
-0.2917
-0.2784
-
-
-
-
-
PIM,,
-
-
-
-
-
-
-
-
PIM.3
-
-
-
-
-
-
-
-
PIMa.i
-
-
-
-
-
-
-
-
PIMa-2
-
-
-
-
-
-
-
-
PIMa.,
-
-
-
-
-
-
-
-
ACC
0.5417
0.5648
0.4367
-0.2534
-0.3294
-0.3395
-0.4954-0.3297
0.3536
DACC
0.3441
0.3352
0.3625
-
-
-
-0.3063-0.1192
-
POS
0.6289
0.6626
0.5504
-
-0.3712
-0.3954
-0.5528-0.3218
-
c
-0.3334
-0.3578
-0.3855
-
-
-
-
-
ca
-0.3180
-0.2667
-0.2991
-
-
-
-
-
Co
-
-
-
-
-
-
-
-
Ctf-l
-
-
-
-
-
-
-
-
Ct3-2
-
-
-
-
-
-
-
-
Co-i
-
-
-
-
-
-
-
-
FLUDtl
0.5726
0.5799
0.4931
-
-0.3110
-0.4183
-0.4592-0.3538
0.3339
FLUa
-
-
-
-
-
-
-
_
FLUDe
-
-
-
-
-
-
_
_
FLUCc
-
-
-
-
-
-
-
_
FLU,3
-0.2788
-
-
-
-
-
-
-
FLUD.3
0.3183
0.3795
0.3012
-
-
-0.3048
-0.3765
0.3876
FLUC,j
-0.2802
-0.2787
-0.2823
0.1577
-
-
0.3051
-


300
250
Monument
immediately adjacent
to Cape Canaveral
has experienced
.accretion
Cocoa
Beach
0 IhHI 11HH mi 111IHI Hll 111II11
Although beach width varies
alongshore, the_variation between the
1972, 1986 and 1997 points at each
monument, indicates a dynamic area
Satellite
Beach
Indialantic
in i mi 111 m nninnnn nun i ii i im i nnin 11 in i ni i in n nnni 11 u
mt+n
+4
10 20 30 40 50 60 70
80 90 100 110 120
Monument Number
130 140 150 160 170 180 190 200
X 1972 Beach width 1986 Beach width 1997 Beach width
Figure 5-2. Brevard County beach width variations, with trend 1972-1997, (BW,i, BW,2, BW0)


91
Dependent Variables Characteristics
The dependent variables were collected over the same three time periods as the
independent variables. Brevard County data were from 1972 (tl), 1986 (t2) and 1997 (t3). St
Johns County data were collected for 1972 (tl), 1986 (t2) and 1999 (t3). Future land use data
were collected from 1972 (tl), and 2000 (t3) plans for Brevard County and 1979 (tl) 1989 (t2)
and 2001 (t3), plans for St Johns County (Appendix B).
Number of Dwelling Units (UN)
The number of dwelling units variable represents the total units (in structures containing 8
units or less) present in the 9-ha sample areas in Brevard and St. Johns County. Figure 5-3 shows
the number of units for each time period and the potential units permitted by the FLU^. Cocoa
Beach, Satellite and Melbourne Beach have higher existing units and proposed future land uses
than the rest of coastal Brevard County. In southern Brevard County there are lower densities
and lower proposed future land use densities. The average number of dwelling units increases
from 17.7 in 1972 to a 28.1 in 1997 for the 138 9-ha sample areas (Appendix G) increasing by
10.4 units. The minimum number of units for each time period (,i to o) is zero, indicating there
were 9-ha sample areas without units. The -i to t3.i data shows negative values, indicating that
there were sample areas that experienced a decrease in the number of units. The decrease in the
number of dwelling units was caused by demolitions, reconstruction, density increases and the
removal of mobile homes (monument 143). Similarly, conversion to higher density structures
affects this variable. Structures with over 8 units were included in the impervious area variable.
The renovation of Patrick Air Force Base impacted the number of units and density. The UN^
data reflects the removal of Base housing and replacement at lower densities.
The average number of dwelling units increases from 7.2 in 1972 to 17.8 in 1999 for the
138 9-ha sample areas in St. Johns County (Appendix G), a mean increase of 10.6 units. The
standard deviations recorded for 1972 to 1999 are 10.2 to 19.6, indicating that by 1999 there was
a greater range in the number of dwelling units by sample area. Some 9-ha sample areas


41
stabilization of the inlet impacted stabilization of the foreshore in Coca Beach. However it is
unlikely that any influence downdrift extends beyond 0.62 km (Bodge, 1992). Port Canaveral
Inlet is dredged to a depth of 13 m, although during Hurricane Frances in 2004 shoaling
decreased the depth to 8 m (FDEP, 2004a). Dredge material is too fine for beach placement and
is disposed offshore (FDEP, 2000a). Subsequent to this study period the Department of
Environmental Protection adopted an inlet management plan to bypass beach-compatible sand to
nearshore-disposal areas adjacent to monuments 1 to 14 (FDEP, 2000a)
Figure 3-2 shows the two inlets in St. Johns County, St. Augustine Pass south of Vilano
Beach and north of Anastasia State Recreation Area, and Matanzas Inlet between Anastasia
Island and Summer Haven (FDEP, 2000b). St. Augustine Pass was dredged initially in 1940.
The inlet has jetties on the north built in 1941, and south, built in 1958 (McBride, 1987) and is
maintained by U. S. Army Corps of Engineers (Foster et al., 2000). At Matanzas Inlet a
revetment and bridge abutment, initially constructed in 1925, reinforces the south shore. This
inlet is not dredged. South of Matanzas Inlet the coast is protected by structures and designated
an area of critical erosion (Clark, 1999).
Coastal Structures
Structures will impede the transfer of sediment from the foreshore to the dune system
(Carter 1988, Gares, 1987, Nordstrum, 1994). Coastal armoring in the form of parallel structures
has been shown to increase scour and hasten the removal of sand in the foreshore (Beatley, et al.,
1994, Carter 1988, Pilkey and Dixon, 1996, Pilkey, and Clayton, 1989). Therefore, the presence
of structures may impact the beach width, by steepening the beach. Coastal structures are present
in St. Johns and Brevard Counties (Figure 3-1 and 3-2). Brevard County has an extensive length
of shoreline in Cocoa Beach that has a seawall. In 1950 there was about 300m of bulkhead at
Cocoa Beach (Bodge, 1992). In 1972 over 20 percent of the coast had bulkheads compared to 7
percent in 1950. By 1985, 95 percent of the Cocoa Beach area was built out and 48 percent had
bulkheads. Brevard County has many formal and informal (individual resident initiated)


SPATIAL AND TEMPORAL GEOMORPHIC VARIABILITY AND
COASTAL LAND USE PLANNING, NORTHEAST FLORIDA
By
HEIDI J. L. LANNON
A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
DOCTOR OF PHILOSOPHY
UNIVERSITY OF FLORIDA
2005


124
Influence of Geomorphic Variables on Subsequent Development
Nordstrom and others (1999) and Van Der Wal (2004) contemplate the geomorphology in
one time period influencing human variables in later time periods. This was supported by both
the non-parametric and parametric analyses. The non-parametric analyses showed that the lagged
effect of the change in dune height impacted the number of units, density and future land use
decisions in Brevard County. The distance from maximum dune height to NGVD in Brevard
County in 1986 is positively correlated with the future land use and density adopted in the 2000
future land use plan. On Anastasia Island, historically wider beaches appear to have been
considered by planning officials in the determination of areas suitable for that higher densities.
Variation by Location
The explanatory power of the individual variables in each part of the coastline was found
to vary and support the observations of Byrnes and others (1995). The 1972 future land use
(FLUD,i) is a function of the 1972 dune height, long-term change and shoreline orientation
density in Brevard County. On Anastasia Island in St Johns County, the 1972 beach width, an
opposite orientation to Brevard County and the proximity to access to the mainland were
significant variables. When the total proposed units in the future land use plan (FLUtj) are
considered, Brevard County total units are a function of the 1997 dune height and the 1972
distance from the monument to the maximum dune height. An explanation is that areas with low
dunes are areas existing with high densities and impervious area, such as Cocoa Beach, and future
land uses are adopted to be consistent with existing conditions. The influence of the 1972
variables is explained by use of the document titled An open space plan to 1995 for Brevard
County (Brevard County Planning Department, 1972) as the basis of coastal data for the
comprehensive plan (Kurt Easton, Brevard County planning consultant, personal communication,
2005). In contrast on Anastasia Island, the FLUt3 is a function of the 1986 beach width, the
change in dune height from 1972 to 1999 and orientation. The negative coefficient for change in
dune height indicates that higher numbers of units are planned where the dune height change over


148
Table E-2. Continued
Monument
Number
Date
Set
Northing
Northing
(position 2)
NS
Change Easting
(in m)
1
Easting
(position 2)
EW
change
(in m)
2
159
Jan-79
1990823.78
1990823.78
0.00
416579.44
416579.44
0.00
160
Jun-72
1989749.24
416778.39
161
Jan-79
1988689.50
1988689.50
0.00
413974.55
413974.55
0.00
162
Jun-72
1987775.82
417078.72
163
Jun-72
1986781.99
417265.09
164
Jun-72
1985789.56
417446.41
165
Jun-72
1984793.34
417617.63
166
Jun-72
1983804.61
417804.44
167
Jun-72
1982808.73
417945.86
168
Jun-72
1981851.00
418268.00
169
Jun-72
1980858.53
418453.51
170
Jul-86
Monument replaced > 3m from original
171
Jan-79
Monument replaced > 3m from original
172
Jan-79
1977923.69
1977931.19
-2.29
419315.38
419251.88
19.36
173
Jun-72
1976910.16
419509.44
174
1995
1975927.49
1975931.16
-1.12
419793.17
419803.38
-3.11
175
Jun-72
1974965.70
420102.20
176
1999
1973988.30
1974000.45
-3.70
420376.60
420407.61
-9.45
177
Jun-72
1973078.40
420692.30
178
Jun-72
1972123.39
421018.97
179
Jun-72
1971139.74
421300.45
180
Jun-72
1970226.93
421608.59
181
Jan-79
1969334.30
1969337.86
-1.09
421895.30
421889.19
1.86
182
Jun-72
1968374.37
422230.74
183
Jan-79
1967420.91
1967420.91
0.00
422535.53
422535.53
0.00
184
Nov-83
1966439.00
1966439.00
0.00
422844.00
422844.00
0.00
185
Jan-79
1965547.24
1965544.46
0.85
423198.28
423204.53
-1.90
186
Jun-72
1964574.38
423544.90
187
1974
1963637.48
1963636.85
0.19
423888.11
423885.89
0.68
188
Jul-86
1962632.15
1962632.15
0.00
424227.44
424227.44
0.00
189
Jun-72
1961665.78
424608.67
190
Jun-72
1960710.72
424958.42
191
Jun-72
1959786.44
425371.24
192
Jun-72
1958858.98
425784.40
193
Jun-72
1957935.42
426216.81
194
Jan-79
1956981.54
1956975.04
1.98
426662.17
426670.39
-2.51
195
Jun-72
1956065.25
427111.16
196
Jan-79
Monument replaced > 3m from original
197
1995
Monument replaced > 3m from original
197A
Jan-79
1951647.69
1951647.69
0.00
428227.75
428227.75


To Evelyn and Margaret, for adventure and intellect; and to Kurt, Jeremy, and Emma, for their
patience and understanding


78
1
decrease of 4 units (UN), from 1972 to 1997 with a corresponding increase in impervious area
(PIM) increase of over 90 percent. This was due to the small area available for development and
the sensitivity of using the percentage of available area. Similarly the methodology is sensitive to
data misclassification. When redevelopment occurs and residential areas are converted to other
uses, the decrease in units (UN, UH) will be replaced by increased impervious area (IMP, PIM)
and hectares of commercial (C). In St. Johns County monument (187) was revised in 1986 after
GIS investigation of the percent impervious (PIM), which was over 100, and further GIS
investigations showed miscoding of impervious area. This served as a methodological check. In
Brevard County at monuments 21 and 35 the PIM was over 100, by less than 1 percent. Further
review indicated that in this area small lots with two story single-family structures and the
standard residential hectare estimate had overestimated residential impervious area. These areas
were adjusted to reflect a limit at 100 percent.


APPENDIX D: USE OF AERIAL PHOTOGRAPHY AND EXCLUSION OF AREAS
UNAVAILABLE FOR DEVELOPMENT
Beach
Atlantic Ocean
Figure D-I: Use of aerial photography and exclusion of areas unavailable for development
138


151
Table F-l. Continued
End
Rate Averaging
Difference
Average of
(LT) Adjacent
Point
(Olsen 1989)
Olsen and End
Point
Average
Monument
(m)
(m)
(m)
(m)
(m)
36