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

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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
























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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









































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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