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Case Study of Development in the County Road 241 Jonesville-Alachua, Florida Corridor

Permanent Link: http://ufdc.ufl.edu/UFE0021300/00001

Material Information

Title: Case Study of Development in the County Road 241 Jonesville-Alachua, Florida Corridor
Physical Description: 1 online resource (129 p.)
Language: english
Creator: Glenn, Sophia Janene
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: agglomeration, alachua, central, development, economics, graphical, jonesville, land, location, newberry, pattern, place, theory
Food and Resource Economics -- Dissertations, Academic -- UF
Genre: Food and Resource Economics thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Local and state governments throughout the United States (U.S.) have increasing concerns about population growth pressures in the urban/urbanizing areas. Due to growth pressures many different spatial patterns and distributions of land use are observed. These growth pressures necessitate management decisions concerning land use and land distribution. Understanding spatial distribution patterns of new development/land use are important because different patterns over space result in different social, economical, environmental and political impacts. Alachua County has had a steady increase in the number of development projects over the last decade. As its population growth continues to increase the county is forced to accommodate this growth through residential and commercial development. Much of the growth has been residential and commercial developments in the Jonesville-Newberry area. Another area of growth has been in the City of Alachua where investments are being made in commercial and high-end residential real estate developments. The population and development growth have impacted the areas land allocation decisions as well as its infrastructure and services. Although the land conversions and settlement patterns differ between the two areas, County Road (CR) 241 connects these two areas which creates interdependencies, as well as centripetal and centrifugal forces of development. A single case study design was used to study the patterns of development (residential, commercial and agricultural) of the Alachua-Jonesville Florida CR 241 corridor for the years 2000 through 2007. The goal is to determine if economic theory can explain the development pattern of this corridor. Three different subsets of land use theories (location, central place and agglomeration) will be used to determine how well each of these individual theories explain, the development pattern. Individual theories alone cannot completely determine if economic theory explains the development pattern, but many aspects of each theory are confirmed. The strategy for this case study is to use geographical information analysis (GIS) to analyze land values and land use patterns; determine if central place theory can be used to analyze the development patterns of the surrounding cities/municipalities and the Jonesville community; and to analyze the effects of agglomeration on the development pattern. No theory alone can explain the development pattern, but combining the analysis of these theories can help explain the development pattern of the study area.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Sophia Janene Glenn.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Clouser, Rodney L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021300:00001

Permanent Link: http://ufdc.ufl.edu/UFE0021300/00001

Material Information

Title: Case Study of Development in the County Road 241 Jonesville-Alachua, Florida Corridor
Physical Description: 1 online resource (129 p.)
Language: english
Creator: Glenn, Sophia Janene
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2007

Subjects

Subjects / Keywords: agglomeration, alachua, central, development, economics, graphical, jonesville, land, location, newberry, pattern, place, theory
Food and Resource Economics -- Dissertations, Academic -- UF
Genre: Food and Resource Economics thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Local and state governments throughout the United States (U.S.) have increasing concerns about population growth pressures in the urban/urbanizing areas. Due to growth pressures many different spatial patterns and distributions of land use are observed. These growth pressures necessitate management decisions concerning land use and land distribution. Understanding spatial distribution patterns of new development/land use are important because different patterns over space result in different social, economical, environmental and political impacts. Alachua County has had a steady increase in the number of development projects over the last decade. As its population growth continues to increase the county is forced to accommodate this growth through residential and commercial development. Much of the growth has been residential and commercial developments in the Jonesville-Newberry area. Another area of growth has been in the City of Alachua where investments are being made in commercial and high-end residential real estate developments. The population and development growth have impacted the areas land allocation decisions as well as its infrastructure and services. Although the land conversions and settlement patterns differ between the two areas, County Road (CR) 241 connects these two areas which creates interdependencies, as well as centripetal and centrifugal forces of development. A single case study design was used to study the patterns of development (residential, commercial and agricultural) of the Alachua-Jonesville Florida CR 241 corridor for the years 2000 through 2007. The goal is to determine if economic theory can explain the development pattern of this corridor. Three different subsets of land use theories (location, central place and agglomeration) will be used to determine how well each of these individual theories explain, the development pattern. Individual theories alone cannot completely determine if economic theory explains the development pattern, but many aspects of each theory are confirmed. The strategy for this case study is to use geographical information analysis (GIS) to analyze land values and land use patterns; determine if central place theory can be used to analyze the development patterns of the surrounding cities/municipalities and the Jonesville community; and to analyze the effects of agglomeration on the development pattern. No theory alone can explain the development pattern, but combining the analysis of these theories can help explain the development pattern of the study area.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Sophia Janene Glenn.
Thesis: Thesis (Ph.D.)--University of Florida, 2007.
Local: Adviser: Clouser, Rodney L.

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2007
System ID: UFE0021300:00001


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CASE STUDY OF DEVELOPMENT INT THE COUNTY ROAD 241 JONESVELLE-
ALACHUA, FLORIDA CORRIDOR

















By

SOPHIA JANENE GLENN


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

2007

































O 2007 Sophia Janene Glenn


































To my Mother who taught me that I can do all things through Jesus Christ who strengthens me.









ACKNOWLEDGMENTS

I acknowledge and thank Jesus Christ for all that he has done for me. My faith in Him and

His unfailing love have made this journey possible. I thank my mother who taught me that I can

do and be anything and never to give up no matter how hard it may be.

I would like to acknowledge and thank Dr. John Reynolds, who passed away before I

completed the Doctoral Program, for all of his kind support. I also want to thank Dr. Rodney

Clouser for accepting the responsibility and challenge of becoming my committee chair after Dr.

Reynolds's sudden death. I truly appreciate his support and efforts in assisting and supporting

me throughout the completion of this dissertation.

Other special thanks go to Dr. Richard Kilmer for providing me with the opportunity to

publish research in academic j ournals; Dr. Sharon Hutchinson and Lurleen Walters for providing

me with great friendships and moral support; Dr. Thomas Spreen for his support throughout my

doctoral program; Dr James Seal for his academic advice and support and the Food and Resource

Economics Support Staff and Faculty, all have played an important role in my success.












TABLE OF CONTENTS


page

ACKNOWLEDGMENT S .............. ...............4.....


LI ST OF T ABLE S ............ ..... .__ ...............7...


LI ST OF FIGURE S .............. ...............8.....


AB S TRAC T ............._. .......... ..............._ 1 1..


CHAPTER


1 INTRODUCTION AND BACKGROUND .............. ...............13....


Urbanization and Change .............. ...............13....
Alachua County, Florida............... ...............15
Problems Setting ................. ...............17.................
Local Comprehensive Planning ................. ...............20........... ....
Jonesville and Alachua Communities............... ..............2

Population Growth ................. ...............25.................
Problem Statement ................. ...............26.................


2 LOCATION THEORY AND LITERATURE REVIEW ................. ......... ................30


Introducti on ................. ...............30.................
Land Use Change............... ...............32.
Location Theory................ ...............34
Classical Location Theory ................. ...............3.. 5......... ....
Central Place Theory .............. ....... ...............39
Agglomeration and Economic Activity ................. ...............44................
Agglomeration ................. ...............44.................
Agglomeration forces ................. ...............46.................
Location of economic activity ................. ......... ...............46. ....

3 CASE STUDY METHODS AND DATA............... ...............50..


Case Study Design ................. ...............50........... ....
Data and Methods ................. ...............52........... ....
Location Theory................ ...............54
Classical Location Theory ................. ...............54................
Central Place Theory .............. ...............55....
Ag glomeration Theory .............. ...............56....

4 RE SULT S .............. ...............58....


Classical Location Theory .............. ...............58....












General Land Values .............. ......... ...............60
Commercial and Industrial Land Values ................. ...............61........... ...
Residential Land Values ................. ...............61........... ....

Agricultural Land Value ................. ........... ...............62......
Summary of Location Theory Results............... ...............63
Central Place Theory ................ ..... ... .............6
Alachua County Central Place Results ................. ...............64........... ...
Summary of Central Place Theory Analysis .............. ...............65....
Agglomeration Theory.................... .... ............6
Timeline of Development Activity ................. ...............66................
Regulation and Agglomeration............... .............6
Ag glomeration Forces .............. ...............70....

5 CONCLUSIONS ................. ...............112........ ......


Future W ork .......__................. ..........__..........11

Implications ..........._.__........... ...............116.....

LIST OF REFERENCES ....._.. ................. ........_.. .........12


BIOGRAPHICAL SKETCH ..........._.__........... .........._..........12











LIST OF TABLES

Table page


1-1 Study Area Population and Percentage Change from 1990 to 2006 ................. ...............29

4-1 Commercial and Industrial Land Value Data .............. ...............74....

4-2. Commercial Land Value Data .............. ...............75....

4-3 Industrial Land Value Data ................. ...............76........... ...

4-4 Residential Land Value Data .............. ...............77....

4-5 Agricultural Land Value Data............... ...............78..

4-6 Alachua County Straight Lines Distances between Municipalities ................. ................79










LIST OF FIGURES


Figure page

4-1 Alachua County, Florida Study Area Map .............. ...............80....

4-2 2000 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............81

4-3 2001 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............82

4-4 2002 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............83

4-5 2003 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............84

4-6 2004 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............85

4-7 2005 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............86

4-8 2006 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)............... ...............87

4-9 2000 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............8.. 8..............

4-10 2001 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............89.......... ......

4-11 2002 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............90.......... ......

4-12 2003 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............9.. 1..............

4-13 2004 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............92.......... ......

4-14 2005 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............93.......... ......

4-15 2006 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Defl ator) ................. ...............94.......... ......










4-16 2000 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............95.......... ......

4-17 2001 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............96.......... ......

4-18 2002 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............97.......... ......

4-19 2003 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............98.......... ......

4-20 2004 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............99.......... ......

4-21 2005 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............100......... ......

4-22 2006 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Defl ator) ................. ...............10. 1...............

4-23 Alachua County Florida Municipality Central Place Orders and Straight-Line
Distances (miles are rounded up to the nearest whole number) ................... ...............102

4-24 Jonesville Study Area Timeline of Development Activities ................. ........._. .....103

4-25 Land rent theory. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems,
Hofstra University, Department of Economics & Geography, Chapter 6 Concepts,
Slide # 44, http ://people.hofstra.edu/geotrans, Date last accessed June 2007 [used
with permission]................ .............10

4-26 Contemporary modifications of the land rent theory. Rodrigue, J-P, et al. (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 6 Concepts, Slide # 46, http://people.hofstra. edu/geotrans,
Date last accessed June 2007 [used with permission] .............. ...............106....

4-27 Market threshold and range. Rodrigue, J-P, et al. (2006), The Geography of
Transport Systems, Hofstra University, Department of Economics & Geography,
Chapter 7 Methods, Slide # 3, http ://peoplehhofstra.edu/geotrans, Date last accessed
June 2007 [used with permission] ................. ...............107........... ...

4-28 Threshold range and market profitability relationship. Rodrigue, J-P, et al. (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 7 Methods, Slide # 4, http ://people.hofstra.edu/geotrans, Date
last accessed June 2007 [used with permission] .............. ...............108....

4-29 Market size and threshold. Rodrigue, J-P, et al. (2006), The Geoguraphy of Transport
Systems, Hofstra University, Department of Economics & Geography, Chapter 7










Methods, Slide # 5, http://people.hofstra. edu/geotrans, Date last accessed June 2007
[used with permission] ................. ...............109..._.._ .....

4-30 Conventional distance decay curves for retail activities. Rodrigue, J-P, et al. (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 7 Methods, Slide # 12, http://people.hofstra. edu/geotrans,
Date last accessed June 2007 [used with permission] .......... ................ ...............110

4-31 Central places theory (K=3). Rodrigue, J-P, et al. (2006), The Geoguraphy of
Transport Systems, Hofstra University, Department of Economics & Geography,
Chapter 7 Concepts, Slide # 42, http://people.hofstra. edu/geotrans, Date last accessed
June 2007 [used with permission] ..........._...__........_......._ ....... .....1

5-1 Central place theory's implied next possible central place in Alachua County ..............119









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

CASE STUDY OF THE COUNTY ROAD 241 JONESVILLE-ALACHUA, FLORIDA
CORRIDOR

By

Sophia Janene Glenn

December 2007

Chair: Rodney L. Clouser
Maj or: Food and Resource Economics

Local and state governments throughout the United States (U. S.) have increasing concerns

about population growth pressures in the urban/urbanizing areas. Due to growth pressures many

different spatial patterns and distributions of land use are observed. These growth pressures

necessitate management decisions concerning land use and land distribution. Understanding

spatial distribution patterns of new development/land use are important because different

patterns over space result in different social, economical, environmental and political impacts.

Alachua County has had a steady increase in the number of development proj ects over the

last decade. As its population growth continues to increase the county is forced to accommodate

this growth through residential and commercial development. Much of the growth has been

residential and commercial developments in the Jonesville-Newberry area. Another area of

growth has been in the City of Alachua where investments are being made in commercial and

high-end residential real estate developments.

The population and development growth have impacted the area's land allocation decisions

as well as its infrastructure and services. Although the land conversions and settlement patterns

differ between the two areas, County Road (CR) 241 connects these two areas which creates

interdependencies, as well as centripetal and centrifugal forces of development









A single case study design was used to study the patterns of development (residential,

commercial and agricultural) of the Alachua-Jonesville Florida CR 241 corridor for the years

2000 through 2006. The goal is to determine if economic theory can explain the development

pattern of this corridor. Three different subsets of land use theories (location, central place and

agglomeration) will be used to determine how well each of these individual theories explain, the

development pattern. Individual theories alone cannot completely determine if economic theory

explains the development pattern, but many aspects of each theory are confirmed. The strategy

for this case study is to use geographical information analysis (GIS) to analyze land values and

land use patterns; determine if central place theory can be used to analyze the development

patterns of the surrounding cities/municipalities and the Jonesville community; and to analyze

the effects of agglomeration on the development pattern. No theory alone can explain the

development pattern, but combining the analysis of these theories can help explain the

development pattern of the study area.









CHAPTER 1
INTRODUCTION AND BACKGROUND

Urbanization and Change

The 1997 National Resource Inventory (NRI) reports on the dynamics of land use change

from 1992 to 1997; just over 1 1.2 million acres of U.S. land were converted to urban uses. More

than 50% of the land converted to urban uses during this time period can be found in ten states,

of which six are in the South. The state of Florida converted 825.2 thousand acres between 1992

and 1997 and it is estimated 1.2 million acres to 5 million acres between the years of 1964 and

1997. Conversion of land from rural to urban use is more pronounced in Florida than in many

other states. About 3% of the total land area in the United States is classified as urban. While

Florida's urban land area is small (15%), it is still expanding more rapidly than most other states

(Reynolds, 2001).

The rural land-base changes as urban growth expands into rural areas. One important

impact on the natural resource base is the conversion of land formerly used extensively for

agriculture, forestry and open-space (rural land) to urban uses. Given the United States

marketing economy, with its emphasis on private property rights and flexible, sometimes

nonexistent, land use controls, the amount of land converted from rural uses to urban uses

increases directly with the growth of population in an area. If patterns of land consumption

could be established and future urban land conversion could be better predicted, then better

judgments could be made in developing land use policies (Reynolds and Dillman, 1981).

Florida and other areas of the South have experienced rapid population growth. Since the

1960s, population has increased faster in the South than the rest of the U. S. population. The U. S.

population grew at a compound rate of 1.1% from 1962 to 1997 while the population change in

Florida was 2.95% per year. Between 2000 and 2030, the U.S. population is expected to grow by










approximately 82.2 million people, of which about 47% (3 8.7 million) of this growth will occur

in the seven southern states (Florida, Georgia, North Carolina, South Carolina, Tennessee, Texas,

and Virginia). Florida alone will account for 15.5% of the US population growth during this

period. In addition, Florida has the distinction of having the most counties (14) of the nation's

100 fastest-growing counties; with Flagler County being the fastest growing county in the

country between 2000 and 2004 (Clouser, 2006). During the 1990s, Florida's population almost

doubled every 20 years and is estimated to reach 20.3 million in 2020 (Bureau of Economic

Business Research, 1997). Florida's growth rate between 2000 and 2030 is expected to rank as

the third fastest-growing population growth (79.5%) in the United States. Since the 1920s,

Florida has experienced a housing boom unlike any other state. As Florida's population

increases along with growth rates, existing and new residents will place demands on the states

fiscal, human and natural resources. Population increases will impact many aspects of the

region. One of the most obvious and immediate impacts is in the areas of land allocations,

decisions, infrastructure and services.

Throughout the United States, changes in the composition of rural populations reflect a

simultaneous increase in ex-urban/transitional land populations and decreases in traditional rural

populations (Hart 1995). As population increases, population centers grow and mature as urban

areas and the demand for high-value uses of land also increases. As a result the value of land

increases, land is then bid away from more extensive uses such as pasture, forestland and other

undeveloped uses (rural lands) to urban uses. As these population centers grow urban

development becomes more compact, and the price of building sites increases. Those who want

to develop land for urban uses are usually able to bid land away from extensive uses because of

the higher capitalized net returns in the more extensive uses. Consequently, urban land









conversion rates and settlement patterns very substantially between Metropolitan Statistical

Areas (MSA) (Reynolds, 1993).

During 2004 Florida's agricultural land continued to increase in value and the state

continued its population boom and strong nonagricultural demand for land by developers,

investors and speculators. These factors contributed to the increase in value of transitional land

being converted or likely to be converted to urban uses by 7% to 13% in the northern regions of

the state (2005 Florida Land Values Survey, "Nonagricultural Demand Costs Causes Land

Values to Increase," UF/IFAS Electronic Data Information Source (EDIS) FE545,

http://edis.ifas.ufl .edu).

The population boom in Florida has contributed to the state's housing boom. From 1980

through 1996, Florida's house prices, adjusted for inflation, fell by 7% according to the cost and

quality repeat sales index of the Office of Federal Housing Enterprise Oversight (June 1, 2006).

Between 1996 and 2004 Florida's housing prices rose by 70%, compared to 50% nationally. For

the period ending March 31, 2006, Florida's house price appreciation percentage change ranked

number two in the country, second to Arizona, having a one-year percentage increase of 26.6, a

five-year increase of 101.5% and a 363.7% increase since 1980 (Office of Federal Housing

Enterprise Oversight, June 1, 2006). This rapid increase is widespread throughout Florida's

Metropolitan Statistical Areas (MSA), with Florida having 10 of the top 20 highest MAS

increases in the United States.

Alachua County, Florida

Alachua County, Florida lies in the north-central portion of the Florida peninsula and is

part of the Central Highlands, or Central Florida range of the Atlantic Coastal Plain (Spangler,

1985). The county is comprised of approximately 892 square miles, with total county land

acreage of 620,876 acres and 593,585 acres (parcel acreage). The unincorporated area is









comprised of 501,492 parcel acres (84.5% of County) of which 456,055 parcel acres are rural

unincorporated (90.9% of the unincorporated area). The rural/agricultural totals 372,766 acres.

The urban cluster has 45,437 parcel acres and the municipalities are comprised of 92,01 1 acres

(Alachua County Comprehensive Plan: 2001-2020).

In 1997, Alachua County had 1086 farms, averaging 182 acres, with a total acreage of

198, 193 acres (3 1.92% of total county land acreage) and an average value of $19,083.2 per acre.

Cattle, dairy products, vegetables, tobacco, corn and timber generate the greatest sources of

agricultural revenue. Timber produces the greatest revenue, comprising of approximately

296,535 acres in 1997 (47.76% of total County), 245, 012 acres in 2000 (39.46% of total County

acreage) and 240,947 acres in 2001 (38.81% of total County).

Alachua County has used a variety of techniques and strategies as a guide for

development within unincorporated Alachua County. Some of these techniques include urban

growth boundaries (i.e., urban cluster line), urban services line, traditional neighborhood

developments, mixed-use village centers, activity centered design standards, cluster subdivisions,

transfer of development rights and community and neighborhood planning programs. The urban

growth boundary (urban cluster line) defines the area where urban growth should be contained

for a period of time specified by the growth management program and is used to mark the

separation between urbanized and rural land. The urban services line defines an area within the

urban cluster to promote efficient use of land and infrastructure and to minimize sprawl by

phasing development of land within the urban cluster. Also within the urban cluster are activity

centers, which are designated and designed to provide for the concentration of mixtures of higher

intensity and density land uses in the urban area. Activity centers were classified by different

levels and based on their primary and secondary functions, market size, area and intensity.









Problems Setting

Local and state governments throughout the United States have increasing concerns about

population growth pressures in the urban/urbanizing areas. Due to the growth pressures many

different spatial patterns and distributions of land use are observed. These growth pressures

necessitate management decisions concerning land use and land distribution. Understanding

spatial distribution patterns of new development/land use are important because different

patterns over space result in different social, economical, environmental and political impacts.

Therefore, growth management has come to the forefront for many local and state governments.

Hanushek and Quigley (1990, p. 176) describe land-use rules as "the most significant

market intervention taken by state and local government" (Feiock, 2004, p. 363). To address

the multiple issues posed by the state's continued growth and development, Florida has

developed an integrated planning system intended to address and ensure the coordinated

administration of policies. The integrated comprehensive planning framework calls for planning

at all levels of government. There are three key Florida Statutes that guide this planning:

Chapter 380, Part I, the Environmental Land and Water Management Act; Chapter 187, State

Comprehensive Planning; and Chapter 163, Part II, the Local Govemnment Planning and Land

Development Regulation Act.

The Florida Legislature first visited the subj ect of growth management in 1972 with the

adoption of two land use programs within Chapter 3 80, Florida Statutes, Environmental Land

and Water Management Act. This chapter directs the integration and coordination of land and

water management activities and specifically authorizes Developments of Regional Impact (DRI)

and Areas of Critical Concern. The DRI is defined as a proj ect that impacts multiple

jurisdictions and provides for coordinated review of the proj ects through the regional planning

councils. The lead authority for DRIs rests with the department's regional planning councils.









Areas of Critical Concern are areas having significant impact upon environmental or natural

resources of regional or statewide importance, including but not limited to state or federal parks,

maj or rivers and estuaries, state environmental endangered lands, outstanding Florida waters and

aquifer recharge areas and uncontrolled private or public development, that would cause

substantial deterioration of such resources. Historical or archaeological resources, sites or

statutorily defined historical or archaeological districts are also considered areas having

significant impact upon private or public development that would cause substantial deterioration

or complete loss of such resources sites or districts.

Florida's 1985 legislature adopted the Florida's Growth Management Act (Chapter 163,

Part II, Florida Statutes, the Florida Local Government Comprehensive Planning and Land

Development Regulation Act), which directs local government planning and includes

requirements for Evaluation and Appraisal Reports (EAR). This required Florida's 67 counties

and 410 municipalities to adopt local government comprehensive plans to guide future growth

and development. These comprehensive plans contain elements that address future housing,

transportation, infrastructure, coastal management, conservation, recreation and open space,

intergovernmental coordination and capital improvements.

"Concurrency", is a key component of Chapter 163. Concurrency requires that public

facilities and services be provided concurrent with the impacts of development to achieve and

maintain the adequate adopted level of service standard established by the local government

within their jurisdiction. Public facilities subject to concurrency include transportation, water,

sewers, drainage, parks and recreation, solid waste, public schools or other facilities and services.

In order to achieve and maintain level-of-service standards, "concurrency" also requires









intergovernmental coordination for future, public facilities, five-year capital improvements

schedule, and concurrency management systems to address development permits.

The Growth Management Act authorizes the Department of Community Affairs (DCA),

Division of Community Planning to review comprehensive plans and plan amendments for

compliance, but it does not have regulatory authority to "enforce" local government

development. The Division of Community Planning reviews all local development projects

within the designated areas and may appeal to the Administration Commission, Governor, and

any local development orders that are inconsistent with state guidelines. They are also

responsible for reviewing and approving amendments to comprehensive plans and land

development regulations proposed by local governments within the designated areas. Additional

reviewing agencies include the regional planning councils and water management districts,

Departments of State, Transportation, Environmental Protection, Agriculture, and the Florida

Fish and Wildlife Conservation Commission.

Intergovernmental coordination and capital improvements are of particular importance in

comprehensive plans. Comprehensive plans are to include standards to ensure the adequacy of

public facilities. Chapter 186, Florida Statutes provides direction for the integration of state,

regional and local planning efforts. It specifically requires the development of agency strategic

plans and Strategic Regional Policy Plans (SRPP). The North Florida Regional Planning

Council consists of 11 north-central counties, including Alachua County. Their mission is to

improve the quality of life of the region' s citizens by coordinating growth management,

protecting regional resources, promoting economic development and providing technical services

to local governments. Within these 11 counties, the number of residents has increased

dramatically during the last 10 years. The council believes that much of this increase is because










people from other parts of the world and nation are discovering the amenities of North Florida

living. The City of Gainesville, together with Alachua County, accounts for 50% of the total

population of the region. Regional cooperation and planning are becoming increasingly

necessary due to the opportunities and problems that population growth can create for local

governments. Being an association of local governments with strong ties to state and federal

agencies, the council is in a unique position to coordinate the development and implementation

of strategies designed to address the problems and opportunities created by growth. The council

also assists municipalities and counties in preparing concurrency assessments to evaluate the

impact of development on the level of service for roads, water, sanitary sewers, solid waste,

storm water drainage and recreational facilities.

The council maintains a Strategic Regional Policy Plan, which addresses five issue areas:

affordable housing, economic development, emergency preparedness, natural resources of

regional significance, and regional transportation. This plan was used as the basis for reviewing

local government comprehensive plans and amendments during the year. The plan is a long-

range one for the physical, economic and social development of the region, which identifies

regional goals and policies designed to promote a coordinated program of regional actions.

Within this plan, the Metropolitan Transportation Planning Organization was formed through an

interlocal agreement signed by the Florida Department of Transportation, Alachua County and

the City of Gainesville. This organization was formed to conduct long-range transportation

planning activities in the Gainesville Metropolitan area.

Local Comprehensive Planning

The cities of Alachua and Newberry, including the Jonesville community, have their own

individual comprehensive plans for development. All the comprehensive plan strategies address

the long-and near-term needs and desires of each community and are consistent with the Florida









comprehensive plan as well as the North-Central Florida Strategic Regional Policy Plan. Each

city recognizes the critical importance of its planning efforts as part of the north-central Florida

region. Each acknowledges interdependence through the connectivity of County Road 241, and

the City of Gainesville as the maj or metropolitan statistical area in common.

As Alachua County's residential growth continues to increase, the county is forced to

accommodate this growth through development. Therefore, Alachua County has had a steady

increase in the number of development proj ects over the last decade. Although the City of

Gainesville had the greatest number and largest size developments, other areas of the county

have had similar development. During 2005, Alachua County issued a record 443 housing unit

building permits (180 in 2004) (SOCDS building permit database) despite the new building

codes and impact fees charged to developers to offset the costs for roads and county services

(Alachua County Growth Management). Many of these building permits were for homes and

business developments in the Jonesville-Newberry area as well as the City of Alachua.

Investments are being made in commercial and high-end residential real estate developments in

these areas. Within the Jonesville Community and the City of Alachua, developers have made

extensive use of the concepts of traditional neighborhood developments, mixed-use planned

developments, village centers and activity centers within the urban service line. These types of

development are strongly encouraged in the county comprehensive plan and have been identified

as some of the techniques and strategies used for developmental controls.

Traditional Neighborhood Developments integrate housing with other uses to create a

walkable interconnected community. This development is in contrast with conventional

developments, characterized by separation of land uses and housing types within developments

and only accessible by automobile (Danny et. al., 2000). Walkability is the principal focus of









this type of development as well as village centers which encourage the use of non-automobile

forms of transportation by integrating retail services within residential areas. Village centers are

provided with incentives to encourage their development and are allowed in the urban residential

areas as part of the new traditional neighborhood development.

Activity centers are located within urban clusters and provide for the concentration of

mixtures of higher intensity and density land use. Different levels of activity centers are

identified based on their primary and secondary functions, market size and area, and intensity.

They are identified as retail-or employment-oriented and have high, medium or low intensity. A

center's design includes a balance of mixed-uses integrated with a pedestrian-friendly

environment through an overall design framework of size, scale, portion and material. The

Jonesville community center is designated as a low-activity employment center, and is designed

to promote the area around the intersection of Newberry Road (State Road 26) and County Road

241 as a low-intensity employment-oriented local point and a mixed-use center.

Jonesville and Alachua Communities

Jonesville area development has exploded within the last 10 years. It is positioned both

geographically and economically to take advantage of Alachua County's westward growth and

the City of Newberry's infrastructure and equipment (water, sewer, waste disposal and utilities).

Many believe that the community's designation as an Activity center has spurred the

development of proj ects that are well suited to the surrounding area, taking into account market

demands and environmental sensitivity. Hawley Realty and Investments, Inc. has played a large

role in the real estate sales and development in the area and has been instrumental in attracting

the Publix at Steeplechase, Kazbor's, Tuffy Muffler, Tractor Supply and other retail outlets. In

the early 1980s, the company developed residential subdivisions, along County Road 241

between Jonesville and Alachua such as Canterbury Farms, North Central Florida's first gated









community. The Jonesville community has been nationally recognized for its award-winning

Traditional Neighborhood Development, Town of Tioga, which exemplifies the modern-day

mixed-use center. The concentration of development in this area has placed a great toll on

Newberry Road, State Road 26, between Newberry and Gainesville, which has caused the City

of Newberry to turn away developers due to capacity limits. The Newberry City Commission

has committed $58,000 to a study that will lead to a transportation master plan for the city. The

Florida Department of Transportation is also studying solutions to State Road 26 congestion and

has discussed creating a bypass around the city that would take a decade or longer to finish.

The City of Alachua has experienced growth as well, though a large portion of its growth

has been in business development. The city is home to corporations, technology incubators,

local businesses and startup companies. The Alachua US 441 corridor is being developed into a

"corporate corridor (e.g. Sabine, J. A. Weber, Progress Corporate Park and Alachua Professional

Center). Hawley Realty and investments, Inc. has worked on several properties in the City of

Alachua, including Alachua Town Centre and the Progress Corporate Park on US 441. The City

of Alachua has attracted national corporations to its area, including Sysco, North America's

largest food distributor.

Alachua County property values have increased at unprecedented rates in 2006. The total

value of all property in Alachua County jumped 15.5%, to more than $20.6 billion according to

the Alachua County Property Appraiser's assessment. The increased property values have

positive and negative effects on the community. The positive effects are increased tax revenue.

New construction proj ects in the county during 2006 assessed values were at more than $3 81

million and account for 25.5% of the increase in property values. Increased tax revenue, from

the $381 million increase in assessed value, could be spent in areas such as infrastructure and









social and educational programs. One of the negative aspects of increased property values is the

potential for increased tax burdens placed on residents and businesses. The value of single-

family homes in the county increased about 18.4%. If tax burdens did increase it may be more

difficult for young families, retired persons and low-income individuals/families to find housing.

Although regulations are in place to control/manage land use, population growth and

increased development can still create and maintain a path of its own. Therefore the predicted

outcomes of growth and development are still questionable in the case of Jonesville. The

settlement and development patterns for the City of Alachua and Jonesville are different,

reiterating Reynolds' (1993) observation that urban land conversion rates and settlement patterns

vary substantially between areas.

The population growth in these areas has increased ex-urban/transitional area populations

in more rural population centers and has increased land values. The increases in population and

development in both areas has impacted land allocation decisions, infrastructure, and services.

Although concurrency measures are in place to remedy these issues, there are still issues with

transportation and infrastructure. The City of Newberry and the Jonesville community

experienced more growth than anticipated. The unintended consequence of the unanticipated

growth and development is an inadequate supply of affordable housing in these areas due to the

higher land values and more high-end housing developments. Although higher land values have

increased tax revenues, there is still a lag in infrastructure services. It is no surprise that

developers are taking advantage of the new growth management regulation in these areas and are

capitalizing on the high net returns from higher density land values. The Traditional

Neighborhoods, mixed-use developments and cluster subdivisions incentives provided more

flexibility to developers.










Population Growth

The population growth in the study area has been increasing at a significant rate from 1990

to 2000. The City of Newberry has had the most significant increase in population 50.4 percent

between 1990 and 2000 followed by Alachua at 25.7 percent and Gainesville at 11.2 percent

(U.S. Census Bureau) (Table 1-1). The significant growth in the Jonesville community can be

attributed to the growth of the City of Newberry. The Jonesville community is east of the City of

Newberry, which may explain the significant residential growth in that area. In addition,

Jonesville's growth may also be attributed to the growth of the City of Gainesville. As

Gainesville' s population increases, one would expect a subsequent expansion of the city

boundaries westward.

The proj ected population changes from 2000 to 2006 (Table 4-6) shows that the cities of

Newberry and Gainesville will experience a 12.8 and 12.2 percent population increase

respectively, while the City of Alachua will experience an estimated population increase of 28.2

percent. During this time frame, the city with the largest percentage population growth will shift

from Newberry to Alachua while Gainesville and Newberry's have similar population increases.

The If one assumes that population growth causes congestion and places more demands on land

use, then Gainesville's population increase may exert pressure on the urban/rural boundary. As

the population on the outer skirts of Gainesville experience increasing congestion, people will

attempt to avoid congestion by moving further into the rural less congested areas. The Cities of

Newberry and Alachua are closest to Gainesville and the population spillovers will have a

tendency to flow in these directions.

Development in the Jonesville community suggests that Gainesville's growth pressures

have induced pressure on the city's boundaries westward towards Newberry in the Jonesville

neighborhood. One can also extrapolate that Newberry's population will increase at the rate of









the spillover from Gainesville. Therefore the population growth rates of the two cities are

interdependent and the increase in Newberry's population has been concentrated in the Jonesville

community which was also designated as an activity/employment center in the 2001-2020

Alachua County Comprehensive Plan.

The population growth of Alachua has continued to grow since 1990, increasing to 28.2

percent between 2000 and 2006. This increase may also be attributed to Gainesville's population

spillover and/or the city's commercial/industrial enterprises growth. The commercial/industrial

growth may have been facilitated by the city's proximity to Interstate 75. The City of Alachua

also has a designated rural employment activity center. The employment center is designed to

attract and accommodate varies commercial/industrial firms to boost employment, income, and

quality of live for rural residents. The relatively low land values and interstate access makes the

area more attractive and thus possibly contributed to the increase in population growth. In 2007

the median home costs for, Newberry, Alachua and, Gainesville are $294,500, $279,900 and

$259,900 and the median household income is $37,366, $44,541 and, $31,283 respectively. The

median age was 34.6, 35.6, and 28.4 for Newberry Alachua, and Gainesville (Sperling's Best

Places, www.bestplaces.net)

Problem Statement

The City of Gainesville and Alachua County account for approximately 50% of the

regional population and population growth is expected to continue in the future. This case study

concentrates on the developmental growth in the County Road 241 Alachua-Jonesville, Florida

corridor where the population growth is expected to increase over time and exert developmental

pressures on the surrounding communities of Newberry, Alachua, Gainesville and the adj oining

urban-rural fringe. The record number of housing/building permits issued in the county during

2005 is an indication of the rate of development growth in the county.









Although current growth management policies have been used to direct/manage county

development, it has not slowed development but seems to have induced it. County

developmental growth has been moving in a west/northwest direction towards the cities of

Newberry and Alachua and the Jonesville community. Besides Jonesville's designation as a

low-employment mixed-use activity center the community has the infrastructure and is

geographically located in an area to take advantage of the county growth and development.

This study uses the case study method to study and analyze the development pattern in the

Alachua-Jonesville corridor during the 2000-2006 time periods. Three land use theories will be

used to analyze the study area's development pattern; classical location theory using von

Thuinen's bid rent method of concentric rings, central place theory and agglomeration theory.

Geographical Information Analysis (GIS) will be used to apply von Thtmnen's theory to the

study area. The study area roads were identified and a one mile buffer on both sides of the road

will encompass the study area. The Arc Info software spatial analysis tool, inverse distance

weighted interpolation, will be used with GIS parcel and county property appraiser's data to

generate the land value per acre surface. These surfaces will be classified by land use;

commercial/industrial, residential and agricultural. The land values per acre will also be

classified into group values and color codes. Each land use and land value per acre will be

analyzed to determine if the land values are consistent with the bid-rent theory.

Central place theory analysis will be conducted using a map of Alachua County cities and

municipalities using the straight line distances from each city/municipality. This theory suggests

that cities of the same order offering similar goods and services will be located equidistance from

each other and form an equilateral triangle/hexagonal pattern. This study will concentrate on the









cities of Newberry, Alachua, Gainesville and the Jonesville community. The results of this

analysis will then be used to analyze the possible development of the county's central places.

A timeline of developmental activity will be used in the agglomeration theory analysis.

Developmental data was obtained from the Department of Growth Management Developmental

Division using the section, township, and range of the study area sorted by year and plotted on a

timeline of developmental activity. The timeline will then used to analyze the spatial distribution

and pattern of new development; when, where and what type of development took place and the

results of the development pattern over the 2000-2006 time period.

Finally, based on the information collected and the analysis conducted, speculation on

central place development in Alachua County will be addressed. This combines both the

empirical and theoretical aspect of future land use and development in the county.














Table 1-1. Study Area Population and Percentage Change from 1990 to 2006


Study Area USCansusitseauPopshkmlksta
year.................~ 199* proof 2non(10oost 2no(Est.) 20102 (Es) 2003 (Et) 204(Est. 05s. 2006 (Est.}%h)%Or
oty use 2nos11 2non ~2nos
Gaknesvle sITIo Wit47 HO,243 189,409 108,263 108,251 108,143 1M8,6i5 1L1%9 12.1696
Altadium 4529 6098 6,582 56,59 6,922 7,243 7,556 8,453 25.73%L 28.20%
CC$inghrkg 3144 3853 4,0461 4,088 4,119 4,129 4,15i 4,213 18.61%6 R31%
Newberry 1664 3316 3,342 3,356 3,443 3,619 3,8001 3,804 50.42%L 12.33%
Hawthorne 180s6 1415 1,430 1,438 1,443 1,444 1,448 1466 -27.4%L 135%L
Ardie 137 1289 1,266 1,8 1282 1,283 1,287 31132 -6.44%L L00%
waldo lov7 an 8os 795 7as 7as 716 773 -23.8% -6.21%L
Micanopy 612 553 6566 650 651 550 652 658 6.28% 0.76%
La Onse 122 143 146 150 152 153 15i 155 14.699 9.4%L









CHAPTER 2
LOCATION THEORY AND LITERATURE REVIEW

Introduction

Land and land usage have been a universal concern throughout history. The development

of agricultural land is for all practical purposes irreversible and results in a loss of option value,

which may not be taken into account by land markets (Hailu and Brown 2005; NERCRD 2002).

This multifunctionality of land in agriculture keeps it in the public eye and on many research

agendas (Hailu and Brown, 2005; Batie, 2003; Abler, 2003). Walker and Solecki (2004) stated

that land cover and land use change result from economic and demographic interactions between

cities and hinterland, as well as from specifically agricultural and urban processes. The need to

know why and to understand how these changes are maj or concerns of economic geographers,

urban economists, developmental economists, spatial economists, regional scientists, planners

and policymakers today. A better understanding of the way cities and regions work and function

can contribute to better policymaking, thus improving the quality of life and standard of living of

the urban and rural inhabitants (McCann and Scheffer, 2004, p. 177)

The search for answers to these questions has been the study of scholars from many

different disciplines, each having its own particular foci in the different uses of land and space.

McCann and Scheffer (2004), regional scientists, stated that the aim of regional science is to

better understand the structure and function of cities and regions while taking into account the

multifaceted dimensions of the phenomena whether economic, social, political or environmental.

In the field of regional science, an interdisciplinary social science enterprise is concerned with

analytical approaches to problems that are specifically urban, rural or regional. Each discipline,









having its own specific foci and aim, has resulted in a multitude of land use/location, spatial and

regional growth theories that often only deal with a particular portion of the spatial structure.

Many of the theories within disciplines overlap and become blurred, particularly due to the

tendencies toward interdisciplinary research.

The lack of spatial analysis in mainstream economics has been addressed by Krugman

(1995): "It's almost 40 years since Walter Isard attacked economic analysis for taking place in a

'wonderland of no spatial dimensions', yet his plea for spatial economics has gone virtually

unanswered." In 1956, Isard's Location in Space Economy made a powerful effort to get

economists to take space seriously. It was the first big effort to get space into economics,

although Ohlin (1933) previously proposed development of general location by interacting trade

and location theory. Isard made the previously inaccessible German tradition of Germanic

geometry, the geometry of location on a two-dimensional landscape, available to monolingual

economists, creating an important practical interdisciplinary enterprise of regional science

founded in 1954. He and a core group of scholars and practitioners promoted the obj ective and

scientific analysis of settlement, industrial location and urban development.

Given the broad spectrum of disciplines dealing in spatial, locational/geographical land

use and land use change theory, this section will provide a historical background of theory,

usage, application and the evolution of what we observe today. The following sections will begin

by identifying some of the more prominent figures in historical location theory; they, along their

contributions, usage and applications.






SIn this study, location and land use theory will be used somewhat interchangeably, defining land use theory under
the umbrella of the broad heading of location theory.









Land Use Change

Economists are interested in change because of the connections between economic

choices regarding land use and the aggregate impact of land use change to include various

applications for policy (Bell and Irwin, 2002). Therefore, studying land use change allows

application of economic theory to analyze local and regional land use patterns, assists in

improving the understanding of land use impacts and bring about the assessment of various

factors influencing change. The results can offer understanding and improvements in the

management of land resources.

Land use planning has developed and continues to evolve in order to manage and direct

the development of land. Land use change is the result of complex interactions between

physical, socioeconomic and legal issues within the geographical/regional context. The

geographical/regional context in itself is complex, filled with uncertainty and error. In other

words, any examination of land use is by definition imprecise and incomplete (Johnson, 2004)

and therefore the resulting impacts from land use change are uncertain (Mojica and Bukenya

2006)

Many studies have been conducted to model land use change determine factors

influencing change and measure impacts of land use change. These studies have covered many

issues concerning land use change, such as land conversion to urban uses and urban sprawl

(Carrion-Flores and Irwin, 2004; Irwin and Bockstael, 2002; Bell and Irwin, 2002; Reynolds,

2000; Lin et al., 2005). Studies have also been conducted addressing issues related to

agricultural/forest and open-space (Kline and Alig, 1999; Nzaku and Bukenya, 2005; Johnson,

2004; Sokolow and Kuminoff, 2000). The Economic Research Service (ERS) and the Natural

Resource Conservation Service (NRCS) of the U. S. Department of Agriculture have conducted

several studies of land use changes and the dynamics of urbanizing areas over the last three









decades (Heimlich and Anderson 1987; Heimlich and Reining, 1989; Vesterby and Brooks,

1989; Vesterby and Krupa, 1997).

Many agree that the urban "push factors" and rural and suburban "pull factors" determine

spatial patterns of development, and hence agricultural land use change. Other factors that affect

regional growth and land use change include public investment in transportation technologies

and improved access to outlying areas (Hailu and Brown, 2005). Irwin and Bockstael (2002)

suggest that urban spatial structure (land use change) is determined by interdependencies among

spatially distributed agents. They adopt the common theme that urban spatial structure evolves

from a 'tug-of-war' between attracting and repelling forces that result from economic

interactions among agents. The individual agents location decisions and hence, the land use

patterns, is determined by the relative magnitude of these interactions. Many other studies

suggest that demographics play an important role in land use change. Studies on population

demographics in urban areas are thought to be a significant factor influencing rural land

conversion (Ahn, 2002, Reynolds, 2001, Ramsey and Corty, 1992, Mojica and Bukenya, 2006,

Nzaku and Bukenya, 2005). There is a significant amount of literature studying the many factors

influencing land use change.

Thus far we have concentrated on microeconomic approaches of the urban land rent

theory; the behavior of the individual consumer or producer aggregates the behavior of others to

derive the resulting land use patterns. In general, the central theoretical conclusion of

economists on land use and land use change is determined by relative rents, economic factors,

social factors, political factors and land characteristics such as location and soil fertility. Some

of the basic assumptions are profit maximization of rents, maximization of utility and the effects

of supply and demand on land use patterns based on a perfectly competitive market, rational










agent behavior and a single equilibrium pattern. The macro-level economic theory approaches

deal with aggregate level data and utilize aggregate concepts that are broadly described in the

fields of regional science, regional economics and development. In spite of the improvements

and expansion of land use theory, Walker (2004) suggested that land cover and land use change

still remain under theorized. He stated that applications making use of structural elements that

specifically attempt to examine and explain these issues are few and far between.

Location Theory

Location theory is concerned with the geographical location of economic activity and is an

integral part of economic geography, regional science and spatial economics.

Theory, as defined by Chapin and Kaiser (1979, p. 27), "is a system of thought which,

through logical constructs, supplies an explanation of a process, behavior or phenomenon of

interest as it exists in reality." Because theory denotes knowledge, the nature and status of

theories differ among different epistemologies (Briassoulis, 2000)-discourse on how knowledge

is acquired, transmitted, altered and integrated into conceptual systems (Johnston et al., 1994, p.

168). Given the definition of theory, Briassoulis (2000) defines theory of land use change as a

set of propositions used to understand the "what" of land use change and the "why" of this

change. In other words, a theory of land use change describes the structure of the changes in the

uses of land from one type to another-and explains why these changes occur, what causes these

changes and what the mechanisms of change are. Briassoulis reiterates Sack (1990), "knowing

the 'why' is essential if we expect to change 'what' we do"; in other words, the theory is a guide

to policy on land use change, a strong and critical demand of the contemporary times.

Now, having a better understanding and definition of theory, this section will discuss the

origins of location theory and its development of what is practiced in economic location theory

today. This section on location theory will be divided into four parts. Part one concentrates on









what is referred to as "Classical Location Theory". The second portion deals with the "Central

Place Theory" which is a spin-off, or evolution of the Classical Location Theory. The third part

is defined in the broad term of agglomeration and economic activity. The last theoretical portion

deals with growth and economic development.

Classical Location Theory

Classical location theory concentrates on the least cost theory of location. The object of

location theory is to answer the question: Why do particular production/economic activities (such

as plants, offices, public facilities, etc.) choose to establish themselves in particular place of a

given space (Ottaviano and Thisse, 2002)? Walker and Solecki (2004) stated that anthropogenic

changes in land-cover, land use and the environmental problems that arise as a result are mainly

driven by the desire to use land as a factor in the production of agricultural goods and residential

amenities. In addition, they also state that land-cover and land use change result from economic

and demographic interactions between city and hinterland as well as from specifically

agricultural and urban processes. The site selection process in this approach is viewed in terms

of cost minimization and emphasizes such variables as labor cost, transportation costs and

agglomeration economies (discussed further in agglomeration and economic activity).

The foundation of location theory can be attributed to Thomas Robert Malthus' theory of

population growth which emphasized the rigid dependence of population growth on the food

supply, and thus focused on the limited supply of land. His ideas led to the concept of

diminishing return, and the theory and nature of land-rent (Blaug, 1985). Land use theory,

therefore, was founded and further expanded in the field of agriculture with the contributions of

Ricardo's (1821) theory of differential fertility of land and land rent. He focused on local

productivity difference, and developed the theory of land use based on relative fertility.

Ricardo's trade-based theory viewed rent as a function of land productivity/fertility and was later










generalized to consider exogenous technological differences for all types of goods, not just

agricultural goods. Ohlin (1933), building on Ricardo's trade-based land rent theory proposed

the development of "general location theory" integrating trade and location theory. General

location theory builds on differences in factor endowments, such as land, labor, capital,

technology etc., over space, thereby developing the so-called Heckscher-Ohlin theory of trade.

The Ricardian and Heckscher-Ohlin approaches have led to sophisticated theories of location and

trade that rely on the existence of (exogenous) 'comparative advantages' across locations.

Although these approaches are central to international trade, they play a much less important role

in the development of spatial economic theory (Duranton, 2005).

The theory of land rent was continued by von Thiinen, known as the "father of location

theorists." In von Thiinen's (1826; 1966) bid-rent model, the maximum amount a renter is

willing to pay for the use of land, explained the effects of location and transportation costs on

Ricardo's land rent. The bid-rent model, the most productive lands with the lowest per unit cost

generate the greatest economic rents. Von Thiinen's theory set the optimum distribution of rural

land uses around a town market where land values differ only with the distance from s town's

center. Using von Thiinen's method, land use patterns generate a set of concentric rings around

the town center. He saw land rent as a function of access to the region's core where population

and the bulk of economic activity took place. Land at the central core is used most intensively

and land use intensity decreases with each outward concentric ring. This theory of bid-rent is

highly conditional on the transportation cost of product and labor markets. Bid-rent theory is

known as the least cost location theory, where agricultural and industry locate as close to markets

as possible, thereby minimizing their cost of transportation for the goods produced. This basic

model has been expanded and used in many studies to address land use changes in the fields of










agriculture (Thiinen, 1966; Dunn, 1954; Isard, 1956), urbanization (Alonso, 1964; Muth, 1969;

Casetti, 1971; Mills, 1972a, 1972b; Solow, 1973), transportation (Muth, 1969 and Beckman,

1974), social issues (Beckman, 1973 and Wheaton, 1978) and multiple central business districts

(Fujita and Krugman, 1995)

Extending von Thiinen's theory, the concept of potential rent was developed by Chomitz

and Gray (1996) and Walker and Solecki (1999). They recognize the importance of bid-rent and

its link to transportation costs as a factor affecting change. Potential rent becomes true rent

when transportation costs are reduced due to new infrastructure or new infrastructure providing

access to the development of undeveloped land. The speculation of potential rent is the incentive

driving land acquisitions in an area' s anticipated development. Both of these models directly

relate shares to land rent determinants. This concept has been used by many (Nelson and

Hellerstein, 1997; Wear and Bolstad, 1998; Chomitz and Gray, 1996) to statistically estimate the

accessibility of land.

Given the broad application of von Thiinen's bid-rent theory, its application and focus were

modeling the microeconomic land use aspects of a monocentric economy. Von Thiinen's model

has primarily been used in the analysis of urban economic growth and, although macroeconomic

applications have been used to describe frontier evolution in large regions (Katzman, 1977;

Cronon, 1991), microeconomic applications are used most frequently. The basis of von

Thiinen's bid rent theory has also been used in multi-centric city application as well (Fujita,

1989). The bulk of microeconomic applications have been on specific places where local

products and labor markets play the main role in bid-rent theory. Von Thiinen's bid-rent theory

has evolved from explaining agricultural land uses to urban and regional land uses.









Taking into account the urban aspect of land use theory, the Ricardian and von Thiinen

models have been combined into an integrated land share model that explicitly includes both

rural and urban land use (Hardy, et al., 2000). Walker (2001) integrated urban and agricultural

spaces by linking land cover change and economic development in the Florida Everglades by

merging von Thiinen 's model with Alonso's (1964). Alonso, one of the University of

Pennsylvania's first Regional Science Department graduates, published "Location and Land

Use" in 1964. In his dissertation he defined a modeled approach on the formation of land rent in

urban environments. Cronon (1991) also used this method to describe the linkages between the

growth of Chicago and frontier expansion in the "Great West". Among the economically

oriented land use theorists, Burgess (1925) asserted that land use patterns of cities consist of

geometric patterns of concentric circles of different land values surrounding a business district

(i.e., von Thiinen's bid-rent theory). Barlow's theory expands the definition of land rent for

given uses as decreasing functions of fertility and the location index or "use capacity" (Miller

and Plantinga, 1999; Barlowe, 1958).

Alfred Weber (1909; 1929), among others, analyzed the location decisions of a firm in

his plant location model. In his publication of "The Theory of the Location of Industries", he

identified the optimal location of a firm by deriving the "minisum" location problem that aimed

to minimize the weighted sum of the Euclidean distances from the plant to a finite number of

sites corresponding to the markets where the plant purchases its inputs and sells its outputs,

therefore minimizing cost. The optimal solution is to find a site that is a dominant place/central

location where its weighted sum is greater or equal to the sum of the weights of all the other sites

(Weiszfeld, 1936). This result may explain the locational decision made by seemingly different

firms to build in a large metropolitan area (e.g. steel mills next to iron mines and other









minimarkets). It also suggested some form of inertia in a firm's locational behavior (Ottaviano

and Thisse, 2002). The focus of Weber' s theories has been moved from minimization of

transportation costs to more standard microeconomic approaches of profit maximization.

Additional variables have been added to this framework to better understand the influences of

geographical and economic factors on location. Sakashita (1967), used production and demand

functions along with firm theory to determine the location of firms. Ziegler (1986) used these as

well as elasticity with respect to distance and quantity and the price elasticity of demand for

inputs in determining firm location. Although Ziegler is best known for firm location theory, his

main concern was to explain the formation of industrial clusters (Isard 1956, chap. 2) thus

introducing agglomeration and deglomerative forces to location theory. The topic of

agglomeration and location theory will be visited in more detail in the agglomeration and

economic activity section. Sakashita also addressed grouping production units-anticipating

Losch' s ([1940]1954) market areas.

Central Place Theory

Christaller (1933; 1966) and Loisch (1940; 1954) are credited as the founders of central

place theory. Their goal was to explain the spatial distribution of economic activities within a

hierarchical system of urban centers. Giving credit to von Thuinen as the origin of geographical

economics, they used his work as the basis of their theories. Alonso also applied von Thtmnen' s

theory to create the urban land market theory.

Christaller' s central place theory was developed in his 1933 dissertation, "The Central

Places in Southern Germany", where he suggested there are laws determining the number, size

and distributions of towns. Transportation costs, population and consumer preferences

determined the location and size of markets/centers supplying a particular type of good, thereby

forming levels of hierarchy. He found that people were more willing to travel greater distances










to obtain higher order goods and services-ones with a larger range and considered more durable,

valuable variables such as jewelry, cars, shopping malls, etc. He determined an urban hierarchy

of settlements having seven principal orders providing different groups of goods and services.

Christaller found that settlements were regularly spaced apart with larger centers spaced further

apart than smaller centers. These settlements had a tendency to form into a triangular/hexagonal

lattice that was found to be the most efficient pattern for travel between settlements. Loisch has

been given credit in proposing these hexagons as an optimum rather than a market outcome.

Losch's theory has been used in market area studies, retail location planning and the planning of

"new towns".

Central place theory provides the principal conceptual lens economist use to understand

the geographic implications of private-sector activity (Castle, 2003, p. 26). It is a geographical

theory used to explain the size and spacing of economic activity or hierarchies of economic

activity based on population and transportation. In this theory, centralization is considered a

natural principle of human settlement and economic activity. Von Thtmnen first used this concept

of centralized economic activity in his location theory. This theory is primarily concerned with

where and why cities are established. It is a powerful organizing principle for looking at and

thinking about urban systems and provides insight about the organization of economic geography

(Mulligan, 1984). Central place theory tells a story about how agents' interactions lead firms to

cluster together into a hierarchy of cities-a city is considered to be a clustering of firms and

workers (Krugman, 1995). This clustering effect will be discussed later in the agglomeration and

economic activity section. Central place theory does not deal with agent interactions or market

structure. They are not necessarily theories of change due to their emphasis on individual

activities (micro aspects) located in space (Briassoulis, 2000). Aspects of agent interactions and









market structure are one of the links in central place theory to agglomeration economies. This

theory is important to understand due to its direct impact in the public policy sector. Because

state and local governments are tasked with the primary responsibility of public policy it is

important that policies and policy implications are considered and addressed properly.

Basic questions in the theory of central places are: Under what conditions can production

be decentralized and when is it profitable to relocate a certain production activity outside the

metropolis in cities of lower order? This theory relies on two basic concepts: (1) the population

or market determines the production of goods and services and (2), the distance or transportation

costs that consumers are willing to travel or pay for that good. To understand this theory,

consideration must be given to the combined production and transportation costs for a product

distributed over a market of a given radius (Beckmann, 1995). Von Thuinen's model of an

economy has a single central city, the central business district (CBD). All economic activities

with increasing returns to scale are concentrated in central location. The agriculture and local

services are continuously extended in a two-dimensional region (outside of the central city) and

endowed uniformly with land suitable for cultivation. Von Thtinen's economic growth process

was driven by simple population growth. In his model, as production in the agricultural sector

increases, transportation demand rises due to increased distance and the city grows in response to

increasing demand for both transportation and industrial goods.

The central city or central business district (CBD) is the beginning point from which all

other economic activity stems and has become the principal orientation of the field of urban

economics (Briassoulis, 2000). Many different aspects of urban and regional studies have been

conducted concerning housing (Romanos, 1976). Bockstael and Irwin (1999) analyzed urban

spatial structure and urban policy impact analysis. Fujita and Thisse (2002) focused on how










population growth fosters the development of incumbent cities and provides incentives to

establish new cities. They suggested that as population grows, new cities emerge when some

critical population threshold is reached (Fujita and Mori, 1997). Walter Isard was one of the first

pioneers in this Hield with his firm location theory and formation of industrial clusters.

By the turn of the 19th century employment shifted from rural agricultural-based

employment to consumer and producer services and manufacturing. This was due in part to

technological improvements in the agricultural sector reducing the demand for labor in rural

areas. The technological advances in the industrial sector provided j obs for workers who

migrated to urban areas for alternative employment. As workers migrated to the urban areas, the

high order, high value added services and manufacturing became concentrated in the maj or

metropolitan areas. Given this shift in employment from agriculture to industry, land use theory

had to incorporate urban and industrial aspects.

W. Alonso (1964) applied von Thtmnen' s theory and refined it to create the urban land

market theory. This theory uses the concept of the bid-rent function for households and/or firms

to explain location behavior and spatial structures of urban land use. Hoover and Giarratani

(1984, p. 153) defined household bid rent as the "maximum rent" that can be paid for a unit of

land some distance from the city center if the household is to maintain a given level of utility.

There is only one bid rent associated with a given level of utility. The city center is considered

the central business district (CBD) and household utility is assumed to be a function of housing

distance from the city center and other goods (Chapin and Kaiser, 1979; Romanos, 1976). As

the distance from the CBD increases, land rent decreases, and households and/or firms choose

locations that maximize their utility subj ect to their budget constraints. Briassoulis (2000)

concludes that the bidding process is a realistic account of the way land is allocated to various









competing uses and it has been used in the theoretical and modeling exercises that followed

Alonso's original contribution. The theory has been used broadly in the analysis of urban spatial

structure as well as impact analysis of urban policies (see Irwin and Barksdale, 1999). In 2001,

Walker combined von Thtmnen' s theory with the urban model of Alonso (1964) to specifically

address changing regimes of natural areas encroachment in South Florida. This model was

developed to take into account the linkages between urban and rural sectors (Walker and Solecki,

2004).

Concepts of central place theory have been modified and expanded to cover many

different concepts. Wu (2002) used environmental amenity values to explain urban sprawl and

the economic landscape. Wu (2002) and Wu and Plantinga (2002) studied the influence of open

space on urban landscapes. In this study they found that residents prefer to live close to open

space and that open space amenities attract migrants to the city. Others, such as Krugman (1991,

1995) and Kilkenny (1998a, b, 1999), have modified central place theory and developed

concepts of new gian th1 l theory (this concept will be discussed further in the growth and

economic development section).

Over time, agricultural and urban theories have expanded, been modified and developed

taking into account other social, political, environmental and ecological factors aimed at

providing improved operational versions of land use theories. James Beshers (1962) concluded

that social as well as economic conditions influenced land use patterns and Walter Fry (1947)

concluded that cultural factors/social values exert a direct and positive influence on land use.

Political as well as social and economic factors were taken into account by F. Stuart Chapman Jr.

He saw the political, social and economic spheres as consisting of three different groups of










values labeled as economic, political and social, all of which lead to different types of land use

patterns.

Agglomeration and Economic Activity

Agglomeration

Agglomeration economies have been thought to be the driving force behind explanations

of geographical concentrations of economic activity in population within cities. Agglomeration

can be described as the spatial concentration of economic activity. Fujita and Krugman (2004)

stated that agglomeration (or the clustering) of economic activity occurs at many geographical

levels, having a variety of compositions. Agglomeration can occur when small shops and

restaurants are clustered in a neighborhood or when cities having different sizes cluster or when

industries from industrial districts. These concentrations are a result of some set of cumulative

processes whereby geographic concentration can be self-reinforcing (Fujita, et al, 1999). The

field of new economic geography was developed to assist in the explanation of formations of a

large variety of cumulative processes of economic agglomerations (or concentration) and the

geographical space of a region focusing on the role of linkages. Understanding the formation of

agglomeration economies is critical for the design of effective urban policies

Fujita and Thisse, in "Agglomeration and Economic Theory, 2002." addresses the three

main causes for the formation of various types of economic agglomeration: increasing returns to

scale, externalities, and imperfectly competitive markets with general and strategic

interdependencies.

A. Marshall (189; 1920, Chap. X) stated that externalities are crucial in the formation of

economic agglomerations. His concept of externalities captured the idea that an agglomeration is

the outcome of a "snowball effect" in which a growing number of agents want to congregate to

benefit from a larger diversity of activities and higher specialization (Fujita and Thisse, 2002).









Matsuyama (1995) found that these cumulative processes are now associated with the interplay

of pecuniary externalities in models combining increasing returns and monopolistic competition.

There are two categories of extemalities: technological and pecuniary. Technological

externalities, sometimes referred to as spillovers, deal with nonmarket integration whereas

pecuniary externalities are products of market interactions and are prevalent in imperfectly

competitive markets

Fujita and Thisse (2002) stated that increasing returns in production activities are needed to

explain economic agglomerations without appealing to attributes of physical geography.

Economists, geographers and historians consider "increasing return" due to economies of scale,

the most crucial factor in the emergence of cities. Spatial patterns of economic growth will be

quite different, depending on the extent to which varying levels of economies of scale are

operative in different locations (Kurgman, 1999). The trade-off between increasing returns in

production and transportation costs is central to the understanding of the geography of economic

activities (Fujita and Thisse, 2002). Increasing returns allow local firms to exploit economies of

scale and local consumers are able to achieve higher levels of satisfaction than is the case with

other less diversified areas. Hotelling (1929) stated that imperfectly competitive, strategic

behavior results in the co-location of competing agents. This spatial competition leads to the

agglomeration of firms (Fujita and Thisse 2002). Krugman (1991) argues that an uneven

distribution of industrial activities across space is a natural result of market processes under

conditions of agglomeration economies (McCann and Scheffer, 2004).

Harris (1954) and others believed that the unequal distribution of industrial activities were

due to a firm's tendency to choose locations of maximum market potential. Market potential is

defined as an index of access to markets involving both the purchasing power of all the markets









to which it might sell and the distance to those markets (Krugman, 1995, p.44). Harris (1954)

also found a clear correlation between high market potential and concentration in the industry

marketing belt. He also pointed out that regions with high market potential, such as the U.S.

manufacturing belt, would find their advantage reinforced as more firms move there.

Agglomeration forces

Two opposing forces are thought responsible for explaining the observed spatial

relationship of economic activities. These two opposing forces are described as

cohesive/centripetal forces that are responsible for clustering/agglomeration and

dispersion/centrifugal forces that are responsible for the diffusion of economic activity. Fujita

and Thisse (2002) describe the observed spatial configuration of economic activity as a result of

a complicated balance of forces that push and pull consumers and firms."

Agglomeration forces are of three maj or types. The first type is related to the size of an

economic region (economies of scale). The second type is related to proximity of business

enterprises to specialized resources. The third type is based on flows of communication.

Agglomeration economies can also be described as internal or localization economies. Internal

economies are achieved when a firm's average costs decrease as the firm size increases.

Localization economies are external to the firm when it locates near its suppliers or in proximity

to other firms producing the same product. These economies are internal to the industry but

external to the firm.

Location of economic activity

Location and costs of economic activity are also affected by the density and differentiation

of economic activity. When units are located close to one another, the cost of doing business

decreases and this creates economies of scale internally and externally. These cost savings are

referred to as agglomeration cost savings that come from the clustering of economic activity.










Each firm finds a location good because of the presence of others (Maki and Lichty, 2000). This

is a positive mutual attraction (centripetal force) rather than repulsion (centrifugal force). The

explanation of such mutual attraction clusters lies in specific characteristics of the activity itself,

its market or its suppliers. Anas, et al. (1998) suggested that economic concentration is limited

by dispersion forces, ranging from land limitations to the cost of communication or

transportation, to local congestion or pollution, to the un-priced positive externalities of

proximity.

Large cities and industrial clusters have been a longstanding feature of our economic

system (McCann and Sheffer, 2004). Businesses of competing enterprises cluster to gain access

sharing part of a total customer base. This total customer base is larger than the aggregate of

customers when the same business are dispersed and isolated from one another. An example of

this type of activity center is a local shopping center that includes businesses such as

supermarkets, banks, gas stations, movie rental shops, restaurants, florists, etc. Other dissimilar

businesses cluster together due to their interdependencies for proximity-sensitive production

input or output markets such as printing and publishing businesses or a lime rock and concrete

business. Anas et al. (1998) suggested that competitive small agents locate in close proximity to

each other to exploit pecuniary or non-pecuniary external economies to reduce the average cost

of a local public good; exchange inputs, products or information; or increase the opportunity for

good matches.

As land use theory developed, incorporating urban and rural land use aspects, the theory of

industry location became increasingly important. While industrial location decisions are supply

and demand driven, labor costs, availability and site and transfer costs have become important

determinants in industry locations. Businesses that form clusters of interdependent industries










depend on large, diverse and active local labor markets and efficient transportation to and from

these activity clusters to function efficiently

McCann and Shefer (2004) stated that the work of Krugman (1991) and Poter (1990),

promoting the importance of industrial clusters in generating competitive advantage for firms

and regions provide lessons that geography really does matter in determining economic growth

and performance. Yet the actual ways in which geography determines economic growth and

development are highly complex. Marshall (1920) had three explanations for the existence of

positive agglomeration externalities, which focus on the roles played by information spillovers,

non-traded local inputs, and skilled local labor pools.

Labor costs are important for both existing and new businesses. Rural areas generally

have lower labor costs than urban areas. In addition to lower labor costs, rural areas generally

have lower site costs as well (land and environmental). These lower labor and site costs provide

incentives for industry expansion in rural areas. These incentives are more attractive in the ex-

urban/transitional areas than those between maj or metropolitan areas in the distant rural areas,

where growth may be greater than in the metropolitan areas. The low labor and site costs in

these ex-urban/transitional areas have become an important location attraction for startup

businesses entering a new market with a new product. This is contrary to the experience of long-

established metropolitan areas currently losing much of the formal industrial base to these ex-

urban rural areas. Some of the other site costs of importance in determining industry location

include government imposed land regulations such as impact fees, infrastructure and facilities;

pollution abatement; industry regulation; environmental protection and energy costs.

The role of infrastructure in regional development must also be examined in the context of

governmental decision-making. Marshall (1929) stated that the provision of regional









infrastructure can act as a catalyst for the generation of local agglomeration economies, because

infrastructure can be regarded as a local non-traded input (McCann and Scheffer, 2004). Glaeser

(1998) argues that the transportation costs involved in ensuring that people have both widespread

and frequent face-to-face contact across a range of individuals is necessary to facilitate the

transfer of tacit information. This transfer of information is the crucial driving force behind the

generation of modem cities and industrial clusters.

Transportation costs and transfer costs are also of great importance in industry location.

These transfer costs include input and output costs. They include shipping costs for inputs and

outputs from trucking, warehousing, air transportation and satellite communications. In areas

where population and traffic congestion are issues, transportation costs can be lower and more

attractive in rural areas. Transportation costs could be prohibitively high in rural areas due to the

need of locating in proximity to other industries due to interdependencies. Agglomeration of

economic activity happens, given transportation costs are minimized below a critical threshold

(Fujita and Thisse, 2002). Technological changes are largely responsible for reducing many

aspects of spatial transactions cost, thereby potentially benefiting peripheral economies (McCann

and Shefer, 1994). Road congestion bears many hidden costs to both the employee in

communing costs and to the employer in ground transportation costs. The overcoming of

increased modem spatial information transaction costs is now regarded in many circles as being

the primary rationale underlying the existence of modem cities (McCann and Shefer, 1994)









CHAPTER 3
CASE STUDY METHODS AND DATA

This chapter will describe the data and methods used to explain the manner in which the

study area developed, why these patterns of development might have occurred, how these

patterns of development relate land use and development to economic theory and how

development decisions were made for the area. This will be accomplished by using a case study

research method to analyze, explain and describe contemporary, complex, social phenomenon

and characteristics of the real life events in land use and development of the Jonesville-Alachua

County Road (CR) 241 corridor in Alachua County, Florida between 2000 and 2006.

Due to the contemporary nature of the development patterns of the study area, the data

cannot be manipulated and the boundaries between what we observe and what actually happened

are not clearly evident. Because there are so many factors that contributed to the development

pattern, the study must rely on multiple data sources. These data sources are from direct

observations, primary/secondary documents and physical artifacts. The history of the actual

development in the study area is the source of direct observation and from Alachua County

Department of Growth Management policies, its Office of Planning and Development and other

legislative documents. These data are used to expand and generalize three land use theories:

location, central place and agglomeration. These theories are then used to describe the

theoretical patterns to compare and contrast these with the actual observed patterns to

theorize/generalize the reasons for contradictory patterns of development.

Case Study Design

A single case study design is used for this research to study the patterns of development

(residential, agricultural and commercial) of the Alachua-Jonesville Florida CR 241 corridor

between 2000 and 2006. Three subsets of land use theories will be used to compare and contrast









how well each of these individual theories can explain the development pattern. Each subset has

a specific set of ideas, as well as circumstances, within which the implications are believed to be

true. In this case, economic theory will be used to confirm, challenge or imply further studies

and/or additional explanations of the development patterns. It is suspected that no subset alone

will totally confirm or challenge theory but some aspects of each theory will be relevant. The

strategy for the case is to combine the theories and use them as a whole to explain the

development pattern of the study area.

Within the 2000-2006 time periods, the study area has had a sharp increase in growth both

residential and commercial. In 1989, the Jonesville community consisted of a small handful of

service-oriented firms and a community churches. This population growth is thought to be a

spillover from the growing City of Gainesville. Growth in Gainesville has moved in a western

fashion towards the Jonesville-Alachua area. This growth has been facilitated through

connecting infrastructures and access to services such as employment, shopping, medical,

airport, etc. from the City of Gainesville. The designation of the Jonesville area as an activity

center has also contributed to this growth. This designation has impelled developers to pursue

the advantage and perks provided through this designation.

On the other end of the study area is the City of Alachua. Alachua has been growing in

population as well as industry. It has a county designated rural employment center and has

become the home of many corporations (some national), technology incubators, local businesses

and start-up companies. Much of this growth has been attributed to its location close to

Interstate 75 and U. S. Highway 441, both of which connect it to the City of Gainesville as well

as many other major cities. County Road 241 connects Alachua to Jonesville, creating a

triangular pattern between the three areas.










Population growth pressure has increased in the area as well as the use of ex-

urban/transitional land for residential and commercial purposes. This increase in land-usage has

also increased the demand for land extending the rural boundary which consequentially increases

land values, housing prices and tax bills/revenue. Although the land conversions and settlement

patterns differ between these three areas, CR 241 and Newberry Road connect these two areas,

and thus creating interdependencies as well as centripetal and centrifugal forces of development.

The resulting development patterns that transpire through the dynamics of each area and the

county growth management plan are neither directly predictable nor easily rationalized. This

lack of information has become an increasing governmental concern and the need for effective

policy and predictable outcomes has emerged. Therefore there is an increasing need for effective

policy recommendations to manage land use at the local level and to mitigate potential negative

social, economical, political and environmental impacts. This economic study of land use

development patterns can help in understanding the choices and impacts of development and the

effects of current and proposed development policies. Therefore there is a need to determine the

effectiveness of economic theory to explain development patterns and to provide effective policy

recommendations

Data and Methods

Data used for the case study were obtained from three main sources: the Alachua County

Property Appraiser' s office, the Alachua County Department of Growth Management and the

U.S. Census Bureau. The following will describe what data was used for each analysis, how the

data was obtained and how it was used for the analysis.

In order to conduct the analysis on location theory geographical data was needed. This

data was obtained from two sources: the Alachua County Department of Growth Management

Geographical Information Systems (GIS) and Mapping Division and the Alachua County










Property Appraisers Office. The county's property parcel data was obtained from the GIS and

Mapping Division. The study roads were determined using the detailed roads file (see Chapter 4

Classical Location Theory for details) and ArcGIS software was used to form a one mile buffer

from each side of the road study area. A selection was made using only those parcels whose

centroid fell within the buffered area. This selection created the study area parcels that were

used for the analysis. The acreage of each parcel was then calculated using ArcGIS. The

Alachua County Property Appraisers market value tax data was obtained and joined with the

attribute data tables for the selected study area parcels. The parcel market value data was used

with the parcel acreage data to calculate the land values per acre. The 2000 GDP deflator was

then used to deflate the land values per acre into constant 2000 dollars.

Once this data was obtained, the study area parcels were converted into point files. The

data was categorized by land use types: agricultural, residential and commercial/industrial. Only

parcel points for these three land uses were used in the analysis. These points were inputted into

the ArcGIS spatial analysis tool interpolation using the inverted distance weight (IDW)

technique. The per acre land values were used in the z-value field in a raster analysis setting

using a cell size of 100 and the one mile buffer as a mask to create the land value surfaces.

These values were then separated into classifications by value and color (see Figures 4-2 to 4-

22).

Central place analysis data were obtained from an Alachua county map created using the

GIS and Mapping Division data (obtained from their GIS server (www.nikos.alachua.fl.us). The

County boundary, maj or road, detailed roads and municipality shape file were used to construct

the map. The municipality shape file was converted to points to obtain the central location of the

city/municipality. Straight line distances were calculated using a straight-line distance calculator









(http ://www.findlocalweather. com/how~far~isrit/dc/washington.html) to determine the distances

between cities/municipalities (see Figure 4-23).

The agglomeration analysis data was obtained from the Alachua County Department of

Growth Management Development Services Division. The section, township, and range for the

study area was determined and used to obtain the study area's developmental and planning data.

This data was obtained in spreadsheet form and was sorted according to year and then plotted on

the timeline of developmental activity (see Figure 4-24).

Location Theory

Location theory studies the effects of geography on economic activities. Space/geography

affects economic relationships through market activities in adj acent locations (neighborhood

effects) and in the movement of people and goods (Beckmann, 1968). Within this broad

category described as location theory, there are three generalized subcategories that will be

discussed with reference to the land-use development patterns of the case study area. These

three subcategories will be referred to as classical location theory, central place theory and

agglomeration economics. Although each of these subcategories have somewhat different ideas

and perspectives, they are all relevant in explaining the development patterns of this case study.

Classical Location Theory

To apply the classical location theories in this case study, the initial focus will be on the

relationship between land use change and land rent over the study period using von Thtmnen's

theory. The focus here is on the distance between the CBD (Gainesville) and the sub-centers

(Newberry and Alachua) on CR 241 and Newberry Road (State Road 26) with the Jonesville

community as a central point. The study will observe the changes in land use (agricultural,

residential and commercial/industrial) and land rent (land value will be substituted for rent) as

the distance increases from the CBD and sub-centers. GIS data from the Alachua County









Growth Management GIS Department will be used to calculate changes in land values at the sub-

centers and the CBD. Land values were divided into value per acre classifications using GIS

data from the Alachua County Property Appraiser. According to this theory, land rent/value will

decrease as the distance from the CBD increases. Land use will change in intensity from high

intensive uses (firms and other larger developments) to low intensive uses (rural housing and

subdivisions) with distance from CBD. Due to the interdependencies and the influences of

adj acent CBD and sub-centers (i.e., neighborhoods have an affect) one can expect a blurring of

the land values and a distorted non-theoretical ring pattern.

The second classical location theory to be applied is Alonso's "bid-rent" function. This

theory assumes that firms are indifferent to their location to the CBD along a bid-rent function

and subj ect to fixed transportation budgets and costs. This theory will be used to analyze

location behavior by determining how and if land values affect location and the average land

values in the study area were determined over time. Historical land development data were used

to determine the location and type of development and to determine the pattern of development

and land uses associated with land values. Historical GIS parcel data were collected from the

Alachua County Department of Growth Management to conduct this study. The Alachua County

Department of Growth Management Office of Planning & Development provided historical

development data from 1997 to 2007 and tax data were obtained from the Alachua County

Property Appraisers Office for land values.

Central Place Theory

The study area was evaluated to determine if hierarchies exist within the study area and if

so, are the hierarchies consistent with the hierarchies of central places in theory? Are the

distances between central places equidistance forming equilateral triangles? The state of

Florida' s requirements for incorporated places does not distinguish between cities, villages and









towns. The requirements for a town or village are the same as for a city. The city designation

requires at least 1,500 residents in counties with greater than 50,000 residents and 5,000

residents for other counties. The 2000 U.S. Census Bureau population estimate for Alachua

County was 217,995. Since there is no official distinguishing characteristics between

cities/central places, a central place population hierarchy in three ordered increments will be

designated: population less than 1000, 1000 to 10,000 and population greater than 10,000. This

can be generalized because the market area/size determines the central place, not the city size.

Central place theory is used in this study to help identify the factors that most influence the

development pattern. This is done by analyzing the hierarchy of central places and spatial

structures.

Agglomeration Theory

The focus of agglomeration economics is to attempt to explain the main causes of

agglomeration in the study area. The analysis will focus on the agglomeration effects of

increasing returns to scale/cost savings, externalities and imperfectly competitive markets. The

use of agglomeration of central places in this case study is used to determine the factors that

most influence the development patterns. The policy and the private sector impacts on

development patterns will also be analyzed. The results of this study can assist in developing

and modifying policies to obtain desired growth and development.

Assuming that firms behave in a competitive manner, central places will optimize market

area through clustering of activities. To test or illustrate this in the study area, a timeline of

development activity will be used to observe area growth, clustering activities and the interaction

of firms over time. An analysis of policy impacts (growth management) and private sector

activities (developers' activities) on the development patterns will also conducted. The data used

for this portion of the analysis were obtained from the Alachua County (Florida) Department of









Growth Management Office of Planning and Development. This data included development

plans reviewed or approved by the Alachua County Development Review Committee within the

study area from 1997 to 2007.

In this study area, the cities of Alachua, Gainesville and Newberry have already been

established. An interesting aspect of Jonesville is that it is not a city or municipality; it is a

neighborhood of the city of Newberry. It has no local government but functions somewhat as if

it is one or may become one. Economists, geographers and historians consider "increasing

return" due to economies of scale the most crucial factor in explaining economic agglomerations

and the emergence of cities. The question is: Will Jonesville turn into an independent

city/municipality due to the agglomeration forces or will be annexed into the City of Gainesville

or Newberry?









CHAPTER 4
RESULTS

This chapter presents the results of the location theory analyses applied to the study area.

Three location theory methods were used: classical location theory, central place theory and

agglomeration economics. Each will be discussed in detail in the following sections.

Classical Location Theory

GIS analysis was applied to demonstrate von Thtmnen's classical location theory of

concentric rings. GIS parcel data from the years 2000-2006 were obtained from the Alachua

County Growth Management Office and 2000-2006 GIS tax data from the Alachua County

Property Appraisers office. These data were combined to form one data set. The data set was

divided into three land use categories: agricultural, commercial and industrial and residential.

Parcel market value and acreage for each parcel were used to calculate the land value per acre.

All values were normalized using the 2000 Gross Domestic Product deflator.

The study area for this analysis is a one-mile buffer from the north and south sides of

Newberry Road (State Road 26) and east and west of County Road 241. These roads cover the

area on Newberry Road from the City of Newberry to SW 34th Street in Gainesville and on CR

241 from the City of Alachua to the Jonesville Community on Newberry Road (Figure 4-1).

The study area buffer was used to select the parcel shape Hiles that have their centroids

within the study area. The study area parcel shape Hiles were then converted to point files to be

used in the spatial analysis. Shape files are defined by Environmental Systems Research

Institute, Inc. (ESRI) as a vector data storage format for storing the location, shape and attributes

of geographic features. A shapefile is stored in a set of related files and contains one feature

class. Interpolation spatial analysis of the land values per acre were used to estimate the surface

values at unsampled points based on known surface values of surrounding points. In this case an









inverse distance weighted (IDW) interpolation was used to estimate cell values in a raster form

of a set of sample points that have been weighted so that the farther a sample point is from the

cell being evaluated, the less weight it has in the calculation of the cell's value. The term raster

is defined by ESRI as a spatial data model that defines space as an array of equally sized cells

arranged in rows and columns, and composed of single or multiple bands. Each cell contains an

attribute value and location coordinates. Unlike a vector structure, which stores coordinates

explicitly, raster coordinates are contained in the ordering of the matrix. Groups of cells that

share the same value represent the same type of geographic feature. The statistics for each land

use and year are provided in Tables 4-1 to 4-5.

Reviewing tables 4-1 to 4-5 from 2000 to 2006 shows that there was an increase in the

number of commercial/industrial and residential land parcels in the study area and a decrease in

the number agricultural parcels. In 2000 there were 569 commercial/industrial firms and 769 in

2006. Two hundred commercial/industrial firms (176 commercial) were established in the study

are during this seven year period. During that time the number of residential parcels increased

by 1631 and the agricultural land parcels decreased by fourteen.

The standard deviations for the three land value classifications (value per acre) had values

larger than their mean. The large commercial/industrial standard deviations may possibly be due

to relative high market land values for professional/office buildings located on relatively small

parcels. Similarly residential standard deviations my be due in part to high market value

residents such as single family homes or condos on relatively small parcels of land. The

agricultural land value deviations may be due to homes with relatively high market value located

on relatively small parcels designated for agricultural uses. The Alachua County Property

Appraiser designates acreage devoted to a home site as cartilage acreage. This acreage cannot









receive the agricultural classification for tax purposes and is assessed at market value therefore;

the home and the cartilage are assessed separately (Florida State Statute 193.461).

General Land Values

The study area land value maps for the three types (commercial/industrial, residential and

agricultural) demonstrate the land values per acre. These values per acre were divided into 11 or

12 classifications (see map legends). IDW analysis was conducted on the parcel land values for

each year from 2000 to 2006. Each classification is a different color and represents a

range/classification of land values per acre.

Von Thuinen's theory states that land values will decrease as the distance from the CBD

increases. In this case, one CBD, Gainesville, and two sub-centers, Alachua and Newberry, were

identified. Viewing the land values per acre over the study period for each classification

(Figures 4-2 to 4-22); there is a general trend of decreasing land value from the CBD, to each

sub-center. This trend is described as general because each sub-center had decreasing land value

trends as the distance increases from their respective sub-centers. Agricultural land values do

not consistently display the decreasing trend from each sub-center or CBD. Neither land value

classification trend displayed perfect concentric rings, but they do show that land values decrease

with distance from the CBD and sub-centers. Although imperfect, these trends are consistent

with von Thtmnen's (1862) theory of concentric rings and also conform to the contemporary

modifications of Alonso' s (1964) land rent theory. Agricultural trends as well as land use are

further discussed in the following sections.

Within the study time frame, one is able to see a trend in the intensity of land uses. The

City of Gainesville is the county seat and the CBD of Alachua County. It is also the location of

The University of Florida, the state' s largest university, and is classified as a metropolitan

statistical area (MSA) by the U.S. Bureau of Statistics. The City of Newberry and Alachua are









small rural municipalities with populations of 3,316 and 6,098 respectively (2000 Census). The

city of Alachua has recently experienced a tremendous growth in industry.

Commercial and Industrial Land Values

Viewing the commercial/industrial land value maps from 2000 to 2006 (Figures 4-2 to 4-

8), the highest land values are in the Gainesville area, followed by Alachua and Newberry. The

trend over the study period shows increasing land values. Each year shows progressive increases

in the land values as the map colors for the lower land values progressively change from the

dominant pink and purple ($40,000-60,000) in Alachua and Newberry to blue and turquoise

($60,000-350,000). The Gainesville area (CBD) land values, initially the highest in value, have

progressively increased in value from yellow ($1-5 million) and green ($3 50,000-1,000,000) to

predominantly yellow. The maps also show a drastic increase in land values in the Jonesville

area increasing from turquoise (100,000-3 50,000) to yellow ($1,000,000 to $5,000,000).

The commercial and industrial land values along Interstate 75 are high as expected due to

the access that the interstate provides. The values within the core of the cities of Alachua and

Newberry are high, due to the local goods and services they provide.

Residential Land Values

Looking at the overall change in residential land values over the study period (Figures 4-9

to 4-15); one finds distinctive changes in land values in 2004 and 2006. In 2004, there is a

general increase in land values at each city and in the Jonesville area over time. In 2006, there

was a significant increase in the land values in each city and most significantly in Jonesville.

Note that the changes in land values in the Jonesville area have the greatest change in values.

The map indicates color changes from predominately red ($2,800-50,000) with some orange

($50,000-100,000) to a substantial increase in the yellow to blue ranges ($200,000-1 3,000,000).










Agricultural Land Value

The change in the agricultural land values displayed moderately increasing land value

trends and also some volatility of these land values (Figures 4-16 to 4-22). One area in particular

surrounds the City of Alachua. Over the study period, an undulation of the agricultural land

values was observed. This undulation may be attributed to a lag in the change in land

classification between land sales from agricultural uses to residential, commercial or industrial

uses. The City of Alachua has a designated rural employment center and has had a significant

influx in industrial settlements.

The high peaks in the agricultural land values are probably due to high value agricultural

land such as timberland and Class I grazing lands. As expected agricultural land values decrease

significantly in the Gainesville area. The cities of Newberry and Alachua display a weak

concentration of high land values within their central places which were greatly weakened by the

volatility of the land value based on changes in land use. Land values within in the Jonesville-

Alachua CR 241 corridor and the Gainesville and Newberry corridor, with the exception of the

Jonesville community, were generally higher due to the more rural location and the distance

from the main roads/highways. Note the increasing agricultural land values that surround the

Jonesville activity center, located at the intersection of Newberry Road and CR 241, on all sides.

As discussed previously, there has been a substantial increase in commercial/industrial and

residential land values in the Jonesville area. The concentration of high land values surrounding

the Jonesville intersection may be due in part to inflated agricultural land values in anticipation

of urban land uses associated with the Jonesville activity center. These differences in land use

and land values have fashioned a boundary that separates urban and rural land uses. The

interplay between the urban/rural spatial boundaries may be thought necessary for the










agglomeration of economic activity (Walker and Solecki, 2004). The urban-rural push and pull

factors at this boundary contribute to and shape the development of agglomeration

Summary of Location Theory Results

Overall, the results obtained from the classical location theory analysis demonstrate that

the land values for the commercial/industrial and residential land uses decreased with distance

from the CBD and the sub-centers as demonstrated in Figures 4-25 and 4-26. However, this is

not the case for agricultural land values. There appears to be a general trend of higher land

values in the Alachua sub-centers than in the Newberry sub-center and the Gainesville CBD.

The Jonesville's inconsistency with von Thtmnen's theory may be due in part to its designation as

an activity center. This designation may have biased the agricultural land values in anticipation

of potential profits from urban uses. These results can be attributed to the urbanization of the

sub-centers, thus higher land values occur between the urban areas as demonstrated by the maps.

Gainesville, being the CBD, does not have any relevant agricultural land because it is an urban

area unlike the urbanizing areas of Newberry, Alachua and Jonesville.

The population growth in these areas contributes to the results of the three land uses. As

the population within the CBD and sub-centers increases, the residential and

commercial/industrial land values will also increase at these centers to accommodate population

growth and to take advantage of surplus economic rents. These increased land values will affect

the agricultural land values because agricultural land is bid away from extensive uses, such as

agriculture, to intensive urban uses.

Central Place Theory

Central place theory can be used to analyze urban spatial structures and policy impacts as

well as dispersion of economic activity. Here the aim is to understand where and why cities are

established and look at the interactions of central places. Central place theory attempts to










explain how these interactions lead to clustering and hierarchies of cities. The objective of this

theory is for firms to obtain an optimal market area. This market is determined by its threshold

and range (see Figures 4-27 and 4-28). The market area and distance form the central place

determines its threshold and thus the hierarchy and order of the city/central place (see Figures 4-

29 and 4-30). Theory suggests that neighboring central places offering the same order of goods

and services will be located equidistance from each other forming an equilateral triangle or

hexagonal pattern where the centers are at the corners (see Figure 4-31).

In this case study the cities and municipalities of Alachua County are divided into three

orders by population: "A", "B" and "C". Central places with populations over 10,000 are of the

highest order, order "A"; followed by order 'B" (population 1,000-9,999) and order "C"

(population less than 1,000). Higher order markets are fewer in number and more widely

distributed and cover a larger market area such as shopping malls, superstores, universities,

central markets/commerce, etc (see Figure 4-30).

Alachua County Central Place Results

The straight line distances between cities/municipalities (rounded to the nearest whole

number) were plotted on an Alachua County map and the order of each central place was labeled

(Figure 4-23; Table 4-7). The City of Gainesville is order,"A". The order "B"

cities/municipalities are Alachua, High Springs, Newberry, Hawthorne and Archer. The order

"C" cities/municipalities are Waldo, Micanopy and La Crosse.

At first glance, the order "B" city distances are all very similar, with the exception of the

distance from Archer to Alachua. Hawthorne is the only order "B" city on the eastside of the

county. Therefore it doesn't have any direct linkages to other "B" order cities in Alachua but

may connect to others cities/towns in the adj acent counties.









The class "C" cities do not have any real direct linkages between them. Two are located in

the northern portion of the county and one is located in the southern portion. If you look at the

class "B" and "C" points on the eastern portion of the county, you will find that Micanopy,

Hawthorne and Waldo are approximately equidistance form one another. This may or may not

be a coincidence. Hawthorne as well as Micanopy and Waldo may be a part of an adj oining

county system of central places or may offer the same order of goods regardless of population

size. In addition, the growth and development in the county during this study period has been

concentrated in the west and northwest portion of the county.

Note the distances between the cities joining Gainesville, Newberry and Alachua. When

the straight line distances between each city is calculated the lengths of the formed triangle have

similar distances (9, 10, and 11 miles: see Figure 4-23). What does it mean? Given the theory

that central places offering the same order of goods and services will be located equidistance

from each other in a triangular fashion suggests that Jonesville is in a perfect location to be

converted into another central place of order "B".

Summary of Central Place Theory Analysis

Overall, looking at the plotted distances between the cities by order does not give the neat

hexagonal structure suggested by Loisch (1940) (see Figure 4-31). Although Figure 4-23 does

not truly demonstrate the hexagonal structure of central places in Alachua County, it does

illustrate the equilateral triangles for the order "B" central places. In order to obtain a true view

of the central place structure, one would have to plot the structures of the surrounding counties to

obtain a truer view of the central place structure.

Agglomeration Theory

This section will discuss the theoretical explanations of the development activity as it

relates to agglomeration economics and activity. The focus will be on the interplay between










spatial boundaries; increasing returns to scale/cost savings and the existence of positive profits,

externalities and imperfectly competitive markets associated with agglomeration economics and

activities. A timeline of development activity was created and employed to analyze and discuss

the development pattern of the study area as it relates to agglomeration theory (Figure 4-24). In

conclusion, there is a discussion of these development activities as they relate to the Jonesville

community during this study period and in the future.

Timeline of Development Activity

Although the time period of this study begins in the year 2000, the timeline of

development activity begins in the year 1997 (Figure 4-24). The year 1997 is relevant because

these activities were catalysts for the following activities. In the 1991-2011 Alachua County

Comprehensive Plan, Jonesville (located within the urban services area) was designated as a low

activity/employment center.

The initial phase of constructing the Jonesville Crossing shopping center began in 1997.

The shopping center was developed to accommodate 21,000 square feet of commercial space.

The shopping center's commercial space was designed to accommodate retail stores, office space

and restaurants. Storage and warehouse facilities were also built during the same year. These

facilities may have been pre-planned to accommodate construction and development activity in

the area. After the initial infrastructure was established, a bank, gas station/convenience store

and a small business center were built to attract consumers. These types of firms form the basis

of a neighborhood center that can capture and concentrate the surrounding population needs,

customer base and market area (see Figure 4-26). The market areas of the individual firms have

been combined to create a larger market area and customer base that is shared equally by each

firm. This shared customer base is the area created by the range of the market area and its

customer base. The range is dependent on the maximum distance that consumers are willing to










travel to get to the neighborhood center. Thus the development of firms sharing a customer base

creates the market area of the neighborhood center. Realizing the competitive advantage of

concentrating spatial economic activity, firms cluster together to create a larger market area and

customer base. This clustering positive externality by increasing firms market area. Firms

benefit from the increased market area which enables firms to realize positive profits.

Jonesville is located approximately half way between Gainesville and Newberry and is

approximately 10 miles from Alachua (see Figure 4-23). The area surrounding the Jonesville

neighborhood center has captured the market areas between these central places, creating an

extended built-up area of surrounding central places. This description of the Jonesville area and

the neighborhood center suggests that it is an agglomeration and can possibly, not necessarily,

become a central place. As development activities continue, the Jonesville neighborhood center

may evolve into a higher order central place.

Between 2002 and 2004, the maj or developments were commercial retail shops and

services. These commercial activities have further developed the neighborhood center from

basic commercial firms to more diversified firms. Some of these additional services include a

drugstore, auto center (Tuffy), hardware store (Tractor Supply), recreational facility

(gymnastics), Dollar General (basic house wares), etc. There was an explosion of offices, retail

shops, restaurants, warehouses and office space that further increased the concentration of

economic activities. This expansion was accommodated through infrastructure improvements

such as existing road improvements and the addition of a communications tower. In the midst of

the increasing commercial activity, residential development also increased to take advantage of

the nearby neighborhood center's commercial activity. During this time period, 722 single









family homes and 60 apartment units were established. This is a significantly large number of

residents in this relatively small area.

During the 2005 to 2007 period residential development continued to grow and 347

additional single family homes were constructed. Commercial development also continued with

the construction of a grocery store (Publix), the addition of two banks (one as the headquarters),

a funeral home and recreational facilities. These additions have created a more self-sustaining

commercial area. Area residents no longer have the need to travel to town/central places for

basic necessities such as food and recreation. To further population sustainment, additions and

improvements were made in the area' s infrastructure such as a sewer expansion and a new fire

station. These services indicate that the area is expecting additional growth. Future plans and

proposals have been made to further increase development in the area by adding a county park

(Jonesville Park), additional gas stations/restaurant/convenience stores, a power station,

communications tower and storm water drainage. Increased commercial growth during this

period helped to accommodate residential growth. Continued commercial and residential growth

functions as centripetal forces that will multiply the agglomeration of Jonesville' s economic

activity.

Regulation and Agglomeration

Reviewing the timeline of development may make one wonder why development occurred

in this area and not in other parts of the county. One reason is that the Department of Growth

Management designated Jonesville as a low density activity/employment center. This activity

center was designed to promote the area around the intersection of Newberry Road and CR 241

as a low-intensity, employment-oriented mixed-use center (i.e., commercial, open space,

office/business parks, institutional and residential). The center is located within the urban cluster

to provide for the concentration of mixtures of higher intensity and density land uses in the urban









area. Residential development may be clustered because of the county's zoning regulations, with

activity centers requiring central water and sewer. This development required a minimum

population of 10,000 people per 80,000 square feet of commercial space for neighborhood

shopping centers and 35,000 people for a single 150,000 square-foot commercial community

shopping center. These required guidelines were developed to prevent premature development.

The urban activity center' s policies address factors influencing the timing of development

such as market penetration within surrounding markets; travel time, population; the number of

households; median annual income; employment rates; economic development needs and job-

housing balances (see 2001-2020 Alachua County Comprehensive Plan, 2.0 Urban Activity

Center Policies). These factors were studied and documented through market and employment

studies to determine the location and/or expansion of activity centers.

Activity center policies require, whenever possible, that centers be confined to

intersections of multi-modal corridors, and appropriate sizing to allow the development of

associated activities while minimizing encroachment on existing and future neighborhoods. The

primary and secondary uses of the centers are determined based on the needs of the community,

character of the surrounding area and market considerations identified in market studies. The

design standards and policies of the activity center are to create compact, multi-purpose, mixed-

use centers that integrate commercial development with residential development that is

pedestrian-friendly development. Commercial facilities shall be phased with the residential

component of the development to allow community green space and surface storm water

management. The county evaluates and updates the Activity center Plans to determine and

maintain compliance.









Considering the growth management policy above, the development pattern of the

Jonesville community appears to coincide with the development policies. Has this development

occurred because of policy or has policy developed to accommodate the Jonesville development?

What, if any, are the push-pull factors/centripetal-centrifugal forces that influenced development

in this area?

Agglomeration Forces

A discussion of the urban push factors and rural/suburban pull factors associated with the

agglomeration of firms in the Jonesville study area will be discussed to determine impacts on the

development pattern. This discussion will address the development of the Jonesville community

and its interdependency with the tri-city area of Gainesville, Newberry and Alachua. The 'tug-

of-war' of attracting and repelling forces resulting in economic interactions among the

surrounding areas and their interdependencies will also be discussed.

Many studies have suggested that demographics play an important role in land use change

and that population demographics in urban areas have a significant impact on rural land

conversion. Walker and Solecki (2004) stated that land cover and land use change results from

economic and demographic interactions between cities and hinterland, as well as from specific

agricultural and urban processes. Agglomeration is said to emerge through the interplay between

spatial boundaries, trip dispersion and the existence of positive profits. Thus, population growth

plays an important role in the agglomeration of economic activities because it modifies the

spatial boundaries between urban and rural areas (review The Population Growth section of

Classical Location Theory).

Constant increases in population growth over this seven-year period have greatly fueled the

agglomeration push and pull factors on the surrounding land uses in the study area. The cities of

Newberry and Alachua, once rural, are seeing an influx in population possibly due to a spillover









of the City of Gainesville. The resulting urban growth has pushed the urban/rural boundary

outwards in a west/northwest direction towards Alachua, Newberry and the Jonesville. Another

maj or push factor is the limitation of available urban land and the relatively lower rural land

values in the rural areas of Newberry and Alachua. Higher land values within the City of

Gainesville have pushed growth outside of the city limits to accommodate further economic

development (see Figure 4-1). Although the outlying land values are relatively low, agricultural

values have been increasing while the profitability of agricultural enterprises has been

decreasing.

Another result of the Gainesville population growth is the increase in population density,

congestion and land values. Population growth in Gainesville has pushed some residents into

rural/suburban areas. Lower land values and labor costs have also pulled some economic

development from Gainesville into the surrounding rural/suburban area. Fujita in his "new

economic geography" believes that this dynamic process in which population gradually

increases, lending to moving agricultural frontiers and the 'occasional' formation of new cities,

can generate an emergent hierarchy of central places (Krugman, 1996). Applying this statement

to this study the Jonesville community could possibly become one of these occasional cities and

part of the hierarchy of central places within the study area/county.

Transportation cost is an important factor in the agglomeration of economic activities. As

population growth increases, the distances between urban and rural also increase. Increased

distance increases the transportation costs of moving goods and services and consumer travel

costs. These costs are impacted by public investment in transportation technologies and

improved access to outlying areas. Because distance has a negative effect on transportation

costs, the increase in transportation costs is thought to lead to the agglomeration of firms.










Agglomeration of economic activity is limited by transportation costs and proximity of other

firms. Firms realize cost savings through clustering of economic activity (agglomeration cost

savings) and the amount of cost savings has an impact on the density and differentiation of

economic activity. Given these factors, infrastructure can act as a catalyst for the formation of

local agglomeration economies where consumers benefit through reduced travel costs and

increased product diversity.

When transportation costs reach a critical point, firms will relocate. Lower rural land

values, density and congestion attract economic activity through cost savings. These cost

savings attract other firms and these firms cluster together to realize agglomeration cost savings.

The agglomeration and differentiation of firms creates a spatial competitive advantage for firms

in the local area. The concept of Marshallian externalities has been used to describe these

cumulative/multiplier effects of agglomeration where firms cluster to ultimately realize positive

profits through increasing returns and monopolistic competition.

Focusing on the study area and knowing the important role of infrastructure, one of the

most important features of the Jonesville community was the expansion of Newberry Road (State

Road 26) from a two-lane to a four-lane road. This improved access to the outlying areas and

literally paved the way to the Jonesville agglomeration of economic development. Prior to the

construction of the Jonesville Activity center, there was no substantial economic activity in

Newb erry and Alachua. The push and pull factors; their interacti ons and cumul ative/multiplying

effects; and the' tug-of-war' between Alachua, Newberry, and the Jonesville neighborhood

center have contributed to their development as central places. Geographically, the Jonesville

neighborhood center is located between the cities of Newberry, Alachua and Gainesville (see

Figure 4-23) and was the first area to experience the effects of 'tug-of-war' and subsequent









development. The natural features of Jonesville and its location have placed it in an opportune

position for the agglomeration of economic activity.

Agglomeration of economic activity is thought to occur through the interactions of spatial

boundaries, trip dispersion and the existence of positive profits. The Jonesville location

encompasses all these concepts of agglomeration. Due to its location, it is in the center of the

spatial boundary interactions of Gainesville, Newberry and Alachua. This central location

minimizes trip dispersion and the relatively low land values and lack of competitive economic

activity create the possibility of economic profits.

One can clearly see the agglomeration of economic activity from reviewing the timeline of

development activity, county policy and regulation of economic activity and the agglomeration

forces in the study area. Given the above observations and the many types and definitions of

agglomeration, Papageorgiou and Thisse (1985) correctly described it as being one of the most

difficult phenomena in spatial analysis. The agglomeration of economic activity is evident but is

in the middle of the 'tug-of-war' and the centripetal/multiplicative forces or factors responsible

for its initial commencement cannot be determined










Table 4-1. Commercial and Industrial Land Value Data


Commercial and Industrial Land Value Data
Min Max Mea n Std. Dev


Year Count
2000 569.00
2001 603.00
2002 566.00
2003 686.00
2004 735.00
2005 751.00
2006 769.00


Sum
652,865,407.30
781,714, 140. 11
670,579,095.50
862,039,520.70
1,041,828,491.56
1,083, 105,840.44
1,181,823,020.49


4,443.28
4,328.91
5,889.08
6,51 5.79
11,334.72
11,114.71
14,832.66


12,720,000.00
12,802,831.52
12,611,689.79
2,349,020.14
41,451,593.35
40,387,294.70
21,266,716.29


1,147,390.87
1,296,375.03
1,184,768.72
1,256,617.38
1,417,453.73
1,442,218.16
1,544,633.32


1,584,723.86
1,792,9 76.17
1,718,962.74
1,723,495.30
2,420,670.13
2,359,087.21
1,996,353.76











Table 4-2. Commercial Land Value Data


Commercial Land Value Data
Max Mean
6,802.56 2,720,000.00 121,254.0
6,668.15 2,802,831.52 1,363,975.6t
6,216.77 12,611b689.79 1,257,607.6
6,515.79 12,349,02.14 1,325,634.9;
1,334.72 41,451593.35 1,494,126.4;
11,114.71 40,387)94.70 1,519,699.43
14,832.66 21,266,716.29 1,629,081.01


Count Min
532.00
566.00
527.00
641.00
688.00
703.00
708.00


Std.Dev Sumn
5 1,616,407.57 644,387,157.26
81,824,785.83 772,010,232.12
91,757,579.68 662,759,25435
2 1,756,852.55 849,731,983.19
7 2,479,400.37 1,027,959,00B.58
1 2,414,864.46 1,068,348,682BS
52,047,130.51 1,153,389,383.55


Year
2000
2001
2002
2003
2004
2005
2005













Industrial Land Value Data
Year Count Min Max Mean Std. Dev Sum
2000 37.00 4,443.28 1,807,806.84 229,141.89 388,867.09 8,478250.04
2001 37.00 4328.91 3,027366.72 262)67.78 561,310.84 9,703,907.99
2002 39.00 5,889.08 1,954287.45 200,508.75 316,591.29 1,954)87.45
2003 45.00 6,972.42 2004,730.49 273,500.83 530,902.96 2004,730.49
2004 47.00 15,987.34 3261,418.13 295,095.38 548,869.94 13,869,482.98
2005 48.00 16,500.50 2,430,687.83 292,411.96 466,082.42 14,035,773.84
2006 61.00 16,169.70 3,388,605.46 654,485.85 747,641.52 34,433,636.94


Table 4-3. Industrial Land Value Data












Table 4-4. Residential Land Value Data


Residential Land Value Data


Year Count
2000
2001
2002
2003
2004
2005
2005


Min Max
9,423.00 578.34 4,758,054.52
9,707.00 564.80 10,644,612.0)2
9,948.00 1,938.53 109,999,393.29
10,095.0 1,936.08 11,508,091.24
10,609.0 1,839.28 12,460,992.50
10,902.0 2,453.54 13,584,007.06
11,054.0 2.560.74 14.703374.07


Mean


Std.Dev Surn
336,026.7 488,674.U 3,166,380,258.29
405,418.50 853,710.93 3,945,104,342.29
447,988.81 942,852.99 4,456,592,633.05
489,315.65 976,549.98 4,939,641,47893
546,381.36 1,063,211.32 5,796,559,858.09
610,307.14 1,166,458.56 6,653,568,482.78
803.782.97 14,415349.52 8.884.375.807.09










Table 4-5. Agricultural Land Value Data

Agricultural Land Value Data
Year Count Min Max Mean Std.Dev Sum
2000 547.00 78.13 3225836.94 4,601.40 18,055.87 2,516966.71
2001 549.00 76.30 329,633.04 5,014.62 18,806.86 2,753,027.65
2002 538.00 76.78 336332.52 5,587.01 20,022.90 3,005513.04
2003 518.00 76.78 196,612.86 5374.23 14,188.01 278,353.43
2004 550.00 91.72 35836962.50 19,764.24 203,593.77 10,870334.32
2005 594.00 100.57 2380,519.80 12,728.13 106,415.86 7,560,12.05
2006 533.00 97.49 204.718.79 6,002.65 15,738.72 3,199,410.79










Table 4-6. Alachua County Straight Lines Distances between Municipalities

AlachuaCounty Dislances Belween Municipalities
Gainesville Alachua HighSprings Newberry Hawthorne Archer Waldo Micacnopy LaCrosse
Gainesville 0 9 20 17 15 14 13 11 14
Alachua 9 0 12 13 23 16 16 19 6
High Springs 20 12 0 13 35 21 26 29 12
Newberry 17 13 13 0 31 10 28 22 18
Hawthorne 15 23 35 31 0 26 14 13 26
Archer 14 16 21 10 26 0 28 15 23
Waldo 13 16 26 28 14 28 0 21 15
Micanopy 11 19 29 22 13 15 21 0 25
LaCrosse 14 6 12 18 26 23 15 25 0











































I-C IMiles
O 1.5 3 B 9 12


---- Study Area Roads
County Roads

O Urban Services Line
SStudy Area
SMunicipalities
SCounty_Boundary


Figure 4-1. Alachua County, Florida Study Area Map


N



a


Legend

















9 i


NW 56 A~V
ryW 50 AV
NW 46 AV
NW 39AV




e. *


Newberry


IN W3 1 A



wr U~NIERSHY Av
IW -PL


sw 'ay s kl
~. r

z NYW4 PL "a ,
sw 1 PL SW 1 PL ,
swsnv~;4 S


m w Miles
0 0,5 1 2 3 4


Total Count:
Minimum:
Maximum:
Sum: 6
Me~an:
Std Dev:

Commercial:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:O

Industrial :
Minimum:
Maximum:
Sum:
Mean:
Std Dev:


589
4,443.28
12,720,000.00
52,865,407.30
1 ,147,390,87
1,584,723.86

532
8,802,58
12,720,000.00
644,387,157.26
1,211,254.08
1,616,407.57

37
4,443.28
1,807,806.84
8,478,250.04
229,141.89t
388,867.00


Legend
2000 Commercial & Indlustrial Land Valuets/Acre
4,884.42 20,4000
20,000.01 40,000
40,000.01 0,000
80,000.01- 80,000
80,000.01 100,000
S100,000.01 350,000
350,000.01 650,000
550,000.01 1,000,000
S1,000,000.01 6,000,000
II 5,000,040001 -15,000,000
15,000,000.01 25,000,000
25,000,000.01- 42,000,000


Figure 4-2. 2000 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)


Alachua


N


Gainesvile


Ng ? A



































NW "iGAV

NW 50 AV













Jon esvil lei


Gainesville


m v



TYY AVL;~


sw 1 NLWSW PL


mm1 Miles
0 05 1 2 3 4


Legend
2001 Commeriail Industrial Land ValueslCAcre
4 ,788.65 20,000
2(0,00001 -40,000
40,000.01 -00,000
00,000.01 -80,000
80,000.01- 100,000
100,00.01 360,000
3I 50,0080.0 5 50,000
550,000.01 1,000,000
S1,000,000.01 6,000,000
S5,000,000.01- 15,000,000
15,000,000.01 -26,000,000
S 25,000,000.01 -142,0,000


Total ObsrvationIs: 603


Minimum:
Maxistantr
Sum:
Mean:
Std Dev:


4,328.91
12,802,831.52
781,714,140.11
1,296375.0
1,792,976.17


d


Comnnercal Obs: 566
Minirnurn: 6,66i8,16
Maximum: 12,802,831.52
Sum: 772,010,232.12
Mean: 1,363,975,68
Std. Dev.: 1,824,785.83


Mn usidal Ob;:
Maximum:
Sunc
Mean:
Std. DevN:


3748
3,027.366.72
9,73,9067.99
262,267.78
561,310.84


Figure 4-3. 2001 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)


i c
M
4i -~-----

WHI~CI~V.~


1~1
3-; -_1 I,
c--
,
-1
-L"t. _LLI1Y



;;'; f
r
''


i


Alachua


Newberry



















awa ,,


Alachua


r;
s~n~crvrs~v
hH ILR~
mtwru
Z I~HlmW
~~1L~I
HHIII*V
a~h YW

6 p
rml~*u
; J~IVYISPL
$ c I~~rPI-
r~v~rargR
::I iJonesville L
P ip sra*v
a
I IP t
3 r


Gainesville


Newbe~rry


16 a crr

uggR AV"


... ~r


I
b wr'~s
5"
8?:
PPL q~
wlPL

1


f B~E
j g~~
~ ara
in ~a~r
wl!n~


)RYI
$ a
5
6


I(MI'L~ a
QHI~~Y
"~-
ir
B


I~~_....... l~......_.......M les
00.5 1 2 3 4


Total Count:
ulinimum:
MaI~kmum:
Sum:

Std Dev:

Commercial:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:

Industrial:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:


966
s,ase.oe
1 2,611,869.79s
8t~70,579095.5
1,184,768.72
1,718,962.74

527
621 6.77
12,811,869.79
662,759,254.35
1,257,807899
1,757,579.68

SA
5,889.08
1,954,287.45
7,819,841.15
2009508.75
316,591.29


Legend
2002 Commrercial and Industrual Values

C 6,200.35 20,000
g 20,000.01 40,000
1140,000,01 60,000
m 80,000.01 80,000
g 80,000,01 100,000
i3100,000.01 350.000
-n 1350,000,01 550.000
.550,000.01 1,000,000
C 1,000,000.01 5,000,000
g 500,000,0001 8,820,944
m 8,820.944.01 25.000.000
m 25,000,000.01 42,O0000,00


Figure 4-4. 2002 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)


;il


P" .L~ ~Lg~
D-'



-:?


i




















































































Figure 4-5. 2003 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)


Newuberry


F

r4 A


Aiachua


Iw oa


I
yr narr r
R


rl


a
~ wrllw
r


;ei nesvil~e
g
i ~ =a r
1 ~E
%J e ~rB~J~

~ rrur~pe~r+u


.,, r s E


~C1 ~ ar


"5


I


C C Mler


3 0j.5 1 2


lll~L
III1I~Y
YW
c
n
It
X


i,


._._r
a
;a


Legend
2003 Commretial & ubulusral Land Vallufcre


8, 84.68I.O 20,0#

20,000.01 -40,000

g 50,000.01-80,000
m 590,0003 1400,00
(MWe.OOOs -ampm DO
350,000.04 -550,000 W

4cin .673.953.65 5,858.549.56
5,959e.14.17 25io0M,0M
24004000.0 -42WI,000000


Count: 6886
Minimum: 8,5'15.78
Maximrum: 12.349,020.1
Sum: 882,039,620.70
Mea n: 1.256,817.88
Std Dev: 1,"f3,495.30

Clommnercilal: 841
Minimum: 6,515.79
Maximum: 12,349.020 14
lum. 648~.751,555.11
Mean: 1,326,634.g2
Std Dev: 1,756,862.5

Indulstil: 45
Minimum; 6.972.423
Maxinurm: 3,204,730.45
Sum: 12,307,637.51
Mean: 273,600.83
Std Dev: 630,02.9




















* I~~


Alachua


Rg
s ,I,,~
HWYlk~
N~~bA~
HWSlhV


Gainesville

~ ~RHwrslv
I8 EB
8~~'
HIYBKY
L YVLIIRSIPI*Y


Newberry





aw I.,
Ja ~


Jonesvilik
ggIF4AM
HR~N U


a WMIPL
SW3AV
9# AV


IYllb~Y

t
,I
"2
a


NWeM ul A

' a
a a. i


sonommem------mae Miles
0 0.51 2 3 41


Count~:
Minimum:
Maximum: 1

Mean:
Std Dev:

Commerd~alt:
MYinimum;
Maximum:
Sum: 1,(
Mean:
Std Dev:

industrial:
Minimum:
Maximum:
Sum:
Mean:
Std Dev*


7865
1'1,384.72
01,41,8 .5
1,417,453.73
2,420,8670.13

6888
11,334.72
41,451,593.35
027,959,008.58
1,494,1 26,47
2479.400.37

47
15,987.34
3,261,418.13
13,869,482.98
295.095.38
548,&89.94


Legend
2004 Commercial/Industrial Valule/Acre

11,334.72 -20,000
S20,000.01 -40,000
S 40,000.01 -60,000
S60,000.01 -80,000
S 8,000.01 100,000
100,000.01 350,000
350,000.01 550,000
550,000.01 1,000,000
S1,000,000.01 5.000,000
i 5,000,000.01 -15,000,000
S15,000,000.01 25,000,000
S25,000,000.01 42,000,000


Figure 4-6. 2004 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)
















ri'

111~l~.a i~!
:rs 6;
:
r..
i r.




Legend
2005 Commericial & Industrial Land Value/Acre
S11,958.87 -20,000
20,000.01 40,000
40,000.01 0,000
6~p0,00.1 -80,9000
80,0040.D -100,B000
100,000.01- 35,000
3_ 50,000.01 550,000
550,000.01 1,000,Q000
/ 1,000,000.01 5,000,000
S5,000,000.01 15,000,000
15,000,000.01 25,000,0400
25,000,000.01 42,000,000


* -


5
E ,,,,
kVrmlv
aO. L


Alachua


b clnv WliqN SA


HW1 P 8v.NVP gv
nes ~vileIa lL

0 4Miles


Gainesvillea


~~~$$imJWAAV
U"8 aE


E

i
..

i
swllrv m


un. ,,,g ~R


count:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:

Count:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:

Industrial:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:


751

40,387,294.70
1,083,105,840.44
1,442,218.16
2.359,087.21

703
11,114.71
40,387,294 .70
1,068,348,682.88
1,519),699.41
2.414,864.46

48
18,500.50
2.430,687.83
14,035,773.84
28)2,411.95
468,082,42


Figure 4-7. 2005 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)















NlW 158 AV
NW 147 AVi .


Alachua


N~W 39j AV


z
NW 19 PL


Newberry


Gi ainreSVIIIO
,, NW 16AV

i'i 1~~58 rVSW 2AV


NW 23 AV 2


NW4rIPL
SW 1i PL
SW 8 AVr


,

'"" RD


NW 8 LN ~
N 3 At a


mcM-mmm-----ammmMiles
0 0.5 1 2 3 4l


Count: 789
Minimum: 14,832.,68
Maximum:, 21,266,716.29
Sum: 1,187,823,020.49
Mean: 1.544.633.32
St Dev: 1,990,353.78


Commerical: 708
Minimum: 14,832.66
Maximum: 21,268,718.29
Sum: 1,153,389.383.55
Mea n: 1,629,081.05
Std Dev: 2,047,130.51

Industrial: 61
Minimum: 16,189.70
Maximum: 3,388,605.46
Sum: 34,433,838.94
Mean: 564,485.85
Std Dev: 747,841.82


Legend
2006 Commercial & Industria Land Value/Acre

S18,199.45 20,000
20,000.01 -40,000
40,000.01 -60,Q000
60,000.01 80,000
80,000.01 -100,000
~1 00,000,01 350,000
S350,000,01 -550,000
S550,000.01 1,000,000
~1,000,000.01 5,000,000
S5,000,000.01- 15,000,000
15,0010,000.01 25,000,000
25;,000,000.01l -42,000,000


.


Figure 4-8. 2006 Alachua County Florida Study Area Commercial and Industrial Land Values
per Acre (2000 GDP Deflator)





























































Count: 9423
Minimum: 578.34
Maximum: 4758064.52
Sum: 3166380258.29
Mean: 336026.77
Std Dev: 488674.03


Legend
2000 Residential Land Values 2
S578,34 50,000

S100,000 01 200,000
20 00 01(lrll 300,000
S300,000 01 400,000
S400 000 01 100(00 r~
500,000 01 600,000
S600,000.01 700,M000
M 700,000.01 1,000,000
M 1,000,000 01 5,000,000
M 5,000,000 01 15 000 000j~


Alachua


Gainesvile


-. *..


Newberry


0 0.5 1 2 3 4
~I Miles


Figure 4-9. 2000 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


















1.* Alachua





~ -1RD



h~0 II


m rm m ---ggg Miles
0 0.51 ,..2 3 4


Legend
2001 Residential L~anl Values/Acre 2"

586.48 50,000
501,000.01 100,000

200,000 01~ooo 300,000

S300,000 01 400,000

S500,000 01 600,000 Count. 9707
6~ 00,0100 01 -700,000 Minimum: 564.80
S700,000 01 -^ 000 000 Maximum* 10,644,61 2.02
Sum: 3,9415,104,342.29
1,000,000.01 5,000,000 Mean: 406.418.50
5,000,000.01 15,000.000 1 Std Dev: 853,71 0.93


Figure 4-10. 2001 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)





Al~chua N




















Gainesville
i- ej
s:
Cb;
m 51 ~ii~snr
"Y~
%;j~ as'. c3r ~"" 3
-;
rJ i PUIIIYC~LNUI:


m-m Miles
0 0.5 1 2 3 4


Legend
2002 R~esidential Land Value/Acre 2
S2,090. 09 0,000
S50,000.01 100,000
S100,000.01 200,000
S230,00r0.01 300,000
300Sli 000 01 40)0,000
S400,000.01 500,000 il
S5005 000 01 600,000
600.000(lO 01 700(,000
M '00O 000I 01 1,000,000
S1,000,000.01 5.000,000
S5,000,000.01 15 000 000


Count: 9,948
Minimum: 1,938.53
Marimum- 10.8999.393.20
Sunt 4,456,59,633.05
Mean: 447,988.81
Std Dev: 924,852.99


~.9 {


Figure 4-11. 2002 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


I I

c
I
.r.Y
-














i:?: r?
rl,
i ,rr 1
r. I s
~;
1
it.r
r rrrr: .
137--
I- '-I-
ICII ~r
~ T~.E- It
(I 1~ ''
Ir~x~ p- I-
i~" v.; i ~:]















Newberry


Alachua


ii
R
vo
~-c_'.


mm I Miles
O) 0.5 1 2 3 4


Legend
2003 Residential Lanid Values/Acre 2


2,118.87 -50,000
6;0,000.01 -100,000
100,000.01 200,000
S200,000.01- 300,000
S300,W00001 400,000
400,000.01 500,000
500,000.01 600,000
800,000.01- 700,000
S700,000.01 1,000,000
1,000,000.01 5,000,000
5,000,000.0-1 15,000,000


Count:
Minimum:
Maximum:
Sum:
Mea n:
Std Dev:


10,095
1,936.08
11,508,091.24
4,939.841,478.93
489,315.65
976,549.98


4~ Et ': g


Figure 4-12. 2003 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


Gal nesville
,,i~i~hjsv u 'il~ AV
-~,~a~F *c~ -~h ~bnv
10d -I ;bT~ %~. ~ HYLDPI\I
V e;er
~C Erav
a i-~F'- c~ ~C~P~H*PL
~ P~~ir















































0 0,51 2 3 4
an-a-uage- --numeMiles


.~


Count: 10,809
Minimum: 1,839,28
Maximum 12,460,992.50
Sum: 5,700,559,8598.0
Mea n. 646,381.36
Std Dev: 1,083,211.32


Legend
2004 Residential Land Value/Acre 2

1,839.28 50,000
50,000.01 -100,000
'i"": 100,000.01 -200,000
~]200,000,01 300,8000
300,000.01 -400,000
400,000.01 500,000
6_ 00,000.01 800,000
600.000.01 -700,000
S700,000,01 1.000.000
1,000,000.01 5.000,000
M 5.000.000.01 -1 5.000.000


Figure 4-13. 2004 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


Gainesville
,4~,,;~f~ a
~shs~v

4
Ja ~c .g h.3N';i~S~ E on rr~l

Ct, r
















Alachua


*i~. 4%


Gainesville
R .k
)Cm n
~?~pm~""
~z~ap~~
3 ~ S ~VLIA,
iSNVE~IY*Y
.sl O


Newberry


I MilES
0 05 1 2 3 4


Legend
2005 Residential Land Value/Acre 2
S2,509,6 50,000
S50) 00) 01 100,000
S100,000.01 200,000
20j 0,000.01 300,000
S300,000.01 400,000
40 0030( 0R1 ) 500,000U
i.......!500,000.01 600,000
6 400,000.01 70,0 000
M 700,00I0.011 1,000,000

S5,000,000.01 1 5,000,000


a .,
,,


Count:
Minimum:
Maximum:
Sum:
Mean'
Std Dev:


10,902
2,463.64
13,584,007.06
6,653,568,482.78
610,307.14
1,166,458.58


Figure 4-14. 2005 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


~ ira~ i















Alachua


Gainesville


mm I -Miles
0 05 1 2 3 1


Legend
2006 Residential Land Values/Acre 2

M 25601.74 66,002.36
S56,002.36 109,198.6
ii 1093,198.61 215,591.1
S215,591 11 321,983.6
S321,983.61 375,1'79.85
S375,179.86 4e 1,572.36
S481i,5"72.37 694,357.36
i~l694,357,37 -1,013 ,534.86
S1,013,534.87 5,003,253.66
S5.003,253.67 10,003,701.21
S10,003,7101.22 13 .567,850


Count:
Mmuimum:
Maximum:

Std Dev:


11,054
2560.74
14,703,974.07

14,416,349.52


Figure 4-15. 2006 Alachua County Florida Study Area Residential Land Values per Acre (2000
GDP Deflator)


I1I ~y~AV ~~P UWclB AV
pg WWJPIV NW 8 AV~
;d a
~r~' PLF ~I Sdi~2AV
















Alachiua


















Gainesvl~e


o~wberry


2F NW B AV

W UNIVERSrlY AMY


%C'


m m m Miles
0 0.5 1 2 3 4


Legend
2000 Agricultural Land Values/Acre
7 8.13 1,000
1,100 -5,000
5,100 -10,000
11,000- 20,000
21i,000 40,000
41 ~,000- 60,000
S61.000 80,000
81,000 100,000
S110,000 -500,000
S510,ooo 1,000,000
S1,100,000 -4,000,000


Observations
Minimum:
Maximum:
Sum;
Mean:
8td Dev:


:547
78.13
322,838.94
2,518,968.71
4,601.40
18,066.871


-


Figure 4-16. 2000 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)






















































I~ I Miles
0 08.5 1 2 3 4c


Leglend
2001 Agriculural Land Values/Acre

S08.71 1,000
1,000.01-5,6000
5,000.01 160,00
10,000,01 -20,000
20,000.01- 40,000
| 40,00.01- 60,000
00o~~,0001- 80,000
1 80,000,01 -100,000


Obsenrations:
Minimum:
Maximum
Sum:
Mean:
Std Dev:


: 49
76.30
329,633,04
2,753.027.65
5,014.62
118,806.86


100,000.01 500,000
6j00,000.01- 1,000,000
1 ,000,000.01- 4,000,010



Figure 4-17. 2001 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)


Newh

















Alachua


Gainesville


Newberry


~l-au
.1


. Miles
0 0.5 1 2 3 4


Leend
2002 Agricultural Land Values/Acres

//86.8 1,000
1,000.01 5,000
5,000.01 10,000
10,000.01 20,000
20,000.01 410,000
4 r0,000.01 60,000
60,000.01 80,000
80,000,01 100.000
~ I100,000,01 00,000
500,000,01 1,000,000
S1oo,000,00001- 4,000.000


n eraions: 538767
Maximum: 336,332.52
Sum: 3,005.813.04
Mean: 5,587.01
Std Dev: 20,022.90


Figure 4-18. 2002 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)





Alachua


Newberry


I~r rMiles
0I 0.5 1 2 3 4


Legend
2003 Agric cultural Land Values/Acre
i 34.31 -1,060
S 1,000.01 -5,000
S5,000.01 10.000
S10,000.01 20,000
S20,000.01 40.000
40,M000.01 60,000
6 0,000.01 80,000
/ 80,000.01 100,000
S100,000.01 -500,000
500,000.01 1,000,000
I ,000,000.1 [1- 4,000,000


Observations:


Minimum:
Maximum:
Sum:
Mean:
Std Dev:


78.78
190,812.86
2,788,853.43
5,374.23
14C,188.01


Figure 4-19. 2003 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)


Gainesville


~w NVns11 A

4 YPL


*















Alach ua


Gainesville


Newberry


E~~~Ei ""
Isr
E NINBg E
~wuNaAenvrar I
a $
r


m-m W illes
0 03.5 1 2 3 4B


Legend
2004 Agricultural Latnd Value/Acre

L_] 81.34 1,000
11 1,000.01 -5,000
S5,000.01 101,000
S10,000 01 20,000
S20,000 01 40,000
-40,000.01 -60,9000
S60,000 01 80,000
S80,000 01 100,000
100,000 01 500,000
S500,000.01 1,000,000
S1!000,000 01 4,000,000


Count
MJinimum:
Maximum:
Sum:
Mean:
Std Dev:


650
91.72
3,836,962.50
10.870,334.32
19,764.24
20r3,593.77


Figure 4-20. 2004 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)















Alach ua


Gainesville


Newb


mI


NWIIAV

AV


m.m Miles
0051 2354


Legend

2005 Agricultural L~and Value/Acre



1,000 01 5.000

10,00001 20,000


.00000so(-COnOO Count: 594
60B.000 0 080.000 Min imum: 100.57
Maximum: 2380519.80
800000.am00000m Sum: 758061 2.05
I ~t~o oooo sooco Mean: 12728.1 3
soo~col 1,000@Std Dev: 106415.88





Figure 4-21. 2005 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)







































v6 !1AV
SW~PA 'A


... -~ .-Miles
0 0.5 1 2 3 4


Legend
2000 Agricultural Land Values/Acre
<~VALUE>
97.49 -1,000
l ,000.01 ,000
S5,000 01 10,000
S10,000.01 20,000
TI20,000.01 40,000
__140,000 01 60 000
6 0,000_01 80,000
8 0,000.01 -100,000
S100,000.01 -500,000
S500,000 01 1,000,000
S1,000,000.01 4,000,000


Count:
Minimum:
Maximum:
Sum:
Mean:
Std Dev:


533
97.49
204,718.79
3,199,410.79
6.002.65
15,738.72


Figure 4-22. 2006 Alachua County Florida Study Area Agricultural Land Values per Acre (2000
GDP Deflator)


Alachua





RD








































A BC

Figure 4-23. Alachua County Florida Municipality Central Place Orders and Straight-Line
Distances (miles are rounded up to the nearest whole number)




































Amnenrille


* Infraslrucine
* Relail
* OfiEn
* storage


Grmnercial

* Bank


.kmenrile
Busiar Park


Shre
* Eainers CeNIE


Figure 4-24. Jonesville Study Area Timeline of Development Activities


























4d51 ~~Fid

*2Offimmueter /Park
*Dolar General
*Turty Aur"
*Warehouse

*2 Lane knprvemenrt
stanrter


*Jonesvle Cnrter

Hoads


*corrnmaicatimn
Tower
*Tinga mv
Center-netail
/curnmercia


am ss~earkv

*Rearrationafaldty
*w~arhouse
*2 Offew BhL
*2Letaillrater


Figure 4-24. Continued


usi~eF~y
9aA~-nReris
r~o~~
ce~e~8~sn
m;reho~e
Ch~e~rpa~im
~Rnad
~e~lificalion


Figure 4-24. Continued


Famiynsens*osFasine
W~aarpie *Rskuq~s ampen


emp~and *sewaressessin
*on-mecrpex n sidenniummuss
*FwanuaHame


*



















Rent


S= Tr&


S = 75.40 -1 km 5 km 10 km
S =235.62





S = Surface area
D= Distance
77= 314



Figure 4-25 Land rent theory. Rodrigue, J-P, et al. (2006), The Geoguraphy of Transport Systems,
Hofstra University, Department of Economics & Geography, Chapter 6 Concepts,
Slide # 44, http:.//people.hofstra. edu/geotrans, Date last accessed June 2007 [used
with permission]




















A -Conventional CBD
B-Commercial I industry
C-High to medium density residential
D-Sub center










Figure 4-26 Contemporary modifications of the land rent theory. Rodrigue, J-P, et al (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 6 Concepts, Slide # 46, http://people.hofstra. edu/geotrans,
Date last accessed June 2007 [used with permission]














Threshold


I


Cux~~r~r

2
r c
r


Figure 4-27 Market threshold and range. Rodrigue, J-P, et al (2006), The Geoguraphy of
Transport Systems, Hofstra University, Department of Economics & Geography,
Chapter 7 Methods, Slide # 3, http://people.hofstra. edu/geotrans, Date last accessed
June 2007 [used with permission]


















A ,w' Range '

/f Threshold \ 1

o R (A)







Situation A:
Demand > Costs


BThreshold

/ Range \\'t

PO



Situto B:
Dean < Cost


Figure 4-28 Threshold range and market profitability relationship. Rodrigue, J-P, et al. (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 7 Methods, Slide # 4, http ://people.hofstra.edu/geotrans, Date
last accessed June 2007 [used with permission]













-E 50 Town



10 -II
Villg




1,I0 I00010,
ThxIl Ipplt~n xrid

5iur -2 Iake Iieadtrsod orge -,e a.(06,TeGorpyo rnp




[s wTh preishold(ouaio evd














Superstre





O Grocesry Store




OflVenlielCoe


Distance

Figure 4-30 Conventional distance decay curves for retail activities. Rodrigue, J-P, et al. (2006),
The Geoguraphy of Transport Systems, Hofstra University, Department of Economics
& Geography, Chapter 7 Methods, Slide # 12, http ://people.hofstra.edu/geotrans,
Date last accessed June 2007 [used with permission]



























Figure 4-31 Central places theory (K=3). Rodrigue, J-P, et al (2006), The Geoguraphy of
Transport Systems, Hofstra University, Department of Economics & Geography,
Chapter 7 Concepts, Slide # 42, http://people.hofstra. edu/geotrans, Date last accessed
June 2007 [used with permission]









CHAPTER 5
CONCLUSIONS

Although the results of the classical location, central place and agglomeration theories

have contributed to the explanation of the study area development pattern, they cannot fully

explain why the development occurred in this particular area and not in other areas of the county.

What motivated this development and what are the end results of this development.

Reviewing the results of classical location theory suggests that population growth; urban

encroachment and increasing land values have led to development of the study area. The results

obtained from the classical location theory analysis demonstrated that the land values for

commercial/industrial and residential land uses decreased with distance from the CBD and sub-

centers as demonstrated in Figure 4-25 and 4-26. This is not the case for agricultural land

values. There appears to be a general trend of higher land values in the Alachua sub-centers than

in Newberry and Gainesville. The Jonesville inconsistency with von Thtmnen's theory may be

due in part to its designation as an activity center. This designation may have biased the

agricultural land values in potential of anticipated profits of urban uses. These results can be

attributed to the urbanization of the sub-centers, thus the higher land values occur between the

urban areas as demonstrated by the maps. Gainesville, being the CBD, does not have any

relevant agricultural land because it is an urban area rather than an urbanizing area such as

Newberry, Alachua, and Jonesville.

The population growth in these areas contributes to the results of the three land uses. As

the population within the CBD and sub-centers increases, the residential and

commercial/industrial land values will also increase at these centers to accommodate the

population growth and to take advantage of the surplus economic rents. These increased land









values also affect agricultural land values in that agricultural land is bid away from extensive

uses, such as agriculture, to intensive urban uses.

Central place theory results suggest that the study area development was due to its

geographical location, the surrounding central places/order and potential market areas. Noting

the distances between the cities joining Gainesville, Newberry and Alachua, one will find that a

triangle is formed between them and that each length has similar distances (9, 10 and, 11).

Given the theory of central places, Jonesville is in a perfect location to become another central

place of order "B"- if it incorporates, which is not guaranteed.

Reasons cited for incorporation include dissatisfaction with service delivery by the county ,

land- use and growth management concerns, more fiscal control, a since of re proportional

representation or as a means to stave off annexation(Legislative Committee on

Intergovernmental Relations, 2001). In order for the Jonesville community to become an

incorporated municipality, the Florida Formation of Municipalities Act (Ch 74-192) requires a

feasibility study to ensure that the municipality has a viable community and a proposed charter

that is prepared in bill form and submitted to the Legislature.

Overall just looking at the plotted distances between the cities by order does not give the

neat hexagonal structure suggested by Loisch (1940) (see Figure 4-31). Although Figure 4-23

doses not truly demonstrate the hexagonal structure of central places in Alachua County, it does

illustrate the equilateral triangles for an order "B" central place. To obtain a true view of the

central place structure, one must plot the structures of the surrounding counties to obtain a truer

view of the central place structure.

The agglomeration of economic activity is evident but in the middle of the 'tug-of-war'

and the centripetal/multiplicative forces or factors responsible for its initial commencement









cannot be determined. Agglomeration of economic activity is thought to occur through the

interactions of spatial boundaries, trip dispersion and the existence of positive profits. The

Jonesville location encompasses all these concepts of agglomeration. Due to its location, it is in

the center of the spatial boundary interactions of Gainesville, Newberry and Alachua. This

central location minimizes trip dispersion and the relatively low land values and lack of

competitive economic activity creates the possibility of economic profits.

One can clearly see agglomeration of economic activity by reviewing the timeline of

development activity, county policy and regulation of economic activity. Given the above

observations and the many types and definitions of agglomeration, Papageorgiou and Thisse

(1985) correctly described it as being one of the most difficult phenomena in spatial analysis.

The ability of economic theory to explain the development activity of the study area is

limited. Each theory contributes to the explanation but does not explain the development. The

dynamics associated with land development is multifaceted and theory in unable to account for

the infinite number of variables that are responsible for development patterns.

Future Work

After completing this case study many of the case study weaknesses and shortcomings

were evident. Initially, during the data collection phase it became evident that the data for this

type of study was not readily available or of sufficient quality. Due to the data quality issues the

case study method was chosen. The case study method leads to the use of qualitative models

instead of quantitative. This study was limited by the availability and capacity of the qualitative

data to explain the development patterns and by the time limitations to carry out the study.

This study presented a number of data issues and concerns. The availability and

consistency of the data were problematic. The data used for this study was obtained from several

sources; The Alachua County Property Appraiser GIS data, Alachua County Tax Collector tax










data, the Department of Growth Management Offices of Planning & Development and GIS

department and the U. S. Bureau of Census. Inconsistencies of the data were very common. The

GIS data that was obtained from the property appraiser's office and the Growth Management

GIS department were inconsistent. The parcel characteristics were consistent but the metadata

tables did not have the same or consistent information although the Growth Management

Department data is obtained from the property appraiser' s office. Data obtained from the

Department of Growth Management Office of Planning was not recorded in a consistent orderly

fashion. The manner in which the data were organized left gaps in time periods and required

inference to fi11 in the missing data, if possible. The U.S. Census data did not provide consistent

data for comparison purposes. Examples include the American Community Survey data was not

provided for both years 2000 and 2006; there was no information available for the zip code or

City of Newberry in 2006. This information would have been helpful in explaining the changes

in the social economic and housing characteristics.

Data issues were more prevalent in the classical location theory analysis. A portion of the

data issues were with the GIS interpolation spatial analysis model used to generate the land value

surfaces. The interpolation method caused some concern because the visual land value surfaces

do not represent the true acreage for each land use category. The land value surfaces are

weighted to create surface values at unsampled points. The unsampled points are those that are

included in the remaining two categories. Using all sample points to create the land value

surface would not provide a suitable representation of land values. The weighted surface values

also contributed to the large standard deviations from the sample means. Reviewing the land

value statistics from this analysis revealed large standard deviations from the sample mean. The

standard deviation values may have been minimized if the median value was used instead of the









mean. Other useful information may have been obtained through analyzing the acreage statistics

for the three different land uses.

Other weaknesses of this case study are due in part to time limitations. Obtaining the best

and most accurate data for this case study would require an in-depth detailed investigation to

accurately obtain the required historical data from the different county agencies. Another

weakness in the study limited by time was the lack of interviews or survey of the community and

agencies to triangulate the results of the case study. In order to provide true triangulation of the

case study, a survey would need to be created to obtain the data for triangulation.

The results of this study indicate that there is much work to be done to explain

development patterns. The field of"new economic geography" is making great attempts to

develop theory that will address the dynamics of spatial economics. More comprehensive and

intensive multidisciplinary studies are necessary to obtain a more thorough understanding of

dynamics of the spatial economics.

Implications

Reviewing the results of the analysis for the three land use theory applications, the central

place theory analysis proved to be the most applicable in explaining the study area development

pattern. The results of this analysis may be useful in implying the geographical location of

possible central places within Alachua County, Florida.

As an exercise, utilizing the results of the study area analysis may be extended to imply the

next possible central place in Alachua County. Alachua County's development growth has been

primarily in the western portion of the county and over the years the eastern half of the county

has received little development. This exercise is not intended to explain why development

occurred in this manner but to point out that the development potential in western half of the









county is nearing its carrying capacity. Given geographical limitation, the county's development

and population growth must locate in the less developed portion of the county, the eastern half.

Using central place analysis and applying it to Alachua County's eastside figure 5-1

suggests that the next possible central place for the county may be located on the east side of the

county and the general location is indicated by the red highlighted area. The approximate

location may be within the area created by the intersection of Lake Shore Drive, Hawthorne

Road and East University Avenue. This location and the cities of Hawthorne and Waldo are

approximately equidistance form each other. Theory suggests that cities offering the same order

goods and services will be equidistance from each other creating an equilateral triangle.

Although these three areas are approximately equidistance (straight-line distances) the cities of

Waldo and Hawthomne have different orders of goods and services. At present, Hawthomne offers

a higher order of goods and services (order "B") than Waldo (order "C"). Given the counties

past and current rates of growth and development the order of these cities may possibly change.

To address the possible changes in order for the cities of Waldo and Hawthorne, one can

look at the infrastructure to determine the developmental carrying capacity for each location.

Hawthorne Road and Waldo Road are both four lane roads and provide ample access for

development. In addition to the four lane roads, the Gainesville Airport is located between

Waldo and the maps highlighted implied central place. Given the location of the airport and the

possible development it may generate, the city of Waldo has the possibility of becoming a higher

order central place (order "B"). If this was to happen and Hawthorne remained a central place of

order "B", the possible implied central place will be consistent with theory.

The location of this implied central place is a speculation suggested by theory. Only time

can determine if this location will develop into the next central place in Alachua County. Central










place theory also suggest that given the current order of western central places, the likelihood of

developing additional order "B" central places in the same portion of the county is small. If

other order "B" central places were to develop they would be located outside Alachua County.

Another possibility would be that one or more of the order "B" central places could become

annexed into the city of Gainesville. In summary, the future development of an order "B" central

in Alachua County is very likely to occur in the eastern area but the exact location of the

development can only be determined over time.



























Major Roads -
Order:
90 0
A BC




Figure 5-1 Central place theory's implied next possible central place in Alachua County










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BIOGRAPHICAL SKETCH

Sophia Janene Glenn was born in Youngstown, Ohio. She was the second child of seven.

She grew up in Youngstown, Ohio, and graduated from Woodrow Wilson High School in June

1996. As a high school senior she was accepted into The Ohio State University undergraduate

program. During her senior year, at age 17, she also enlisted in the U.S. Army Reserve to assist

in paying for her college education expenses. She attended the U.S. Army Basic Training and

Advanced Individual Training at Fort Jackson, South Carolina, one month after her high school

graduation.

She began her undergraduate studies at The Ohio State University in January 1987,

majoring in economics. During the fall quarter 1987, she joined the Army ROTC 2-year

program and graduated in 1989 with a commission in the Ordinance Branch. In the midst of her

undergraduate education, in 1991, she was mobilized to Fort Lee, Virginia, in support of

Operation Desert Storm/Shield. She graduated in 1992 with a degree in economics and was

offered an assistantship to peruse a specialized master's degree in agricultural economics at The

Ohio State University. She began her master' s degree studies in 1992 and again was called for

military duty in 1993 for the mandatory Officers Basic Course at Aberdeen Proving Ground,

Maryland. In June 1995, she completed her master' s degree in agricultural economics with a

concentration in natural resource economics.

After graduation she accepted a position at the Florida A&M University as an assistant

professor in extension. Her duties were concentrated in the USDA Small Farmer and Technical

Assistance Program as a farm financial management specialist. In 1995, she decided to further

her academic career and was accepted into the University of Florida Food and Resource

Economics doctoral program. In 2003, she was once again called to military duty in support of

Operation Iraqi/Enduring Freedom.





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1 CASE STUDY OF DEVELOPMENT IN THE COUNTY ROAD 241 JONESVILLEALACHUA, FLORIDA CORRIDOR By SOPHIA JANENE GLENN A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2007

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2 2007 Sophia Janene Glenn

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3 To my Mother who taught me that I can do all things through Jesus Christ who strengthens me.

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4 ACKNOWLEDGMENTS I acknowledge and thank Jesus Christ for all that he has done for me. My faith in Him and His unfailing love have made this journey possible. I thank my mother w ho taught me that I can do and be anything and never to gi ve up no matter how hard it may be. I would like to acknowledge and thank Dr. John Reynolds, who passed away before I completed the Doctoral Program, for all of his kind support. I also wa nt to thank Dr. Rodney Clouser for accepting the responsibility and challe nge of becoming my committee chair after Dr. Reynoldss sudden death. I truly appreciate his support and efforts in assisting and supporting me throughout the completion of this dissertation. Other special thanks go to Dr. Richard Kilm er for providing me w ith the opportunity to publish research in academic journals; Dr. Sharon Hutchinson and Lurleen Walters for providing me with great friendships and moral support; Dr Thomas Spreen for hi s support throughout my doctoral program; Dr James Seal for his academic advice and support and the Food and Resource Economics Support Staff and Faculty, all have play ed an important role in my success.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS...............................................................................................................4 LIST OF TABLES................................................................................................................. ..........7 LIST OF FIGURES................................................................................................................ .........8 ABSTRACT....................................................................................................................... ............11 CHAPTER 1 INTRODUCTION AND BACKGROUND...........................................................................13 Urbanization and Change.......................................................................................................13 Alachua County, Florida........................................................................................................ .15 Problems Setting............................................................................................................... ......17 Local Comprehensive Planning..............................................................................................20 Jonesville and Alachua Communities.....................................................................................22 Population Growth.............................................................................................................. ....25 Problem Statement.............................................................................................................. ....26 2 LOCATION THEORY AND LITERATURE REVIEW.......................................................30 Introduction................................................................................................................... ..........30 Land Use Change................................................................................................................ ....32 Location Theory................................................................................................................ ......34 Classical Location Theory...............................................................................................35 Central Place Theory.......................................................................................................39 Agglomeration and Economic Activity...........................................................................44 Agglomeration..........................................................................................................44 Agglomeration forces...............................................................................................46 Location of economic activity..................................................................................46 3 CASE STUDY METHODS AND DATA..............................................................................50 Case Study Design.............................................................................................................. ....50 Data and Methods............................................................................................................... ....52 Location Theory................................................................................................................ ......54 Classical Location Theory...............................................................................................54 Central Place Theory.......................................................................................................55 Agglomeration Theory....................................................................................................56 4 RESULTS........................................................................................................................ .......58 Classical Location Theory......................................................................................................58

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6 General Land Values.......................................................................................................60 Commercial and Industrial Land Values.........................................................................61 Residential Land Values..................................................................................................61 Agricultural Land Value..................................................................................................62 Summary of Location Theory Results.............................................................................63 Central Place Theory........................................................................................................... ...63 Alachua County Central Place Results............................................................................64 Summary of Central Place Theory Analysis...................................................................65 Agglomerati on Theory........................................................................................................... .65 Timeline of Deve lopment Activity..................................................................................66 Regulation and Agglomeration........................................................................................68 Agglomerati on Forces.....................................................................................................70 5 CONCLUSIONS..................................................................................................................112 Future Work.................................................................................................................... ......114 Implications................................................................................................................... .......116 LIST OF REFERENCES.............................................................................................................120 BIOGRAPHICAL SKETCH.......................................................................................................128

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7 LIST OF TABLES Table page 1-1 Study Area Population and Percen tage Change from 1990 to 2006..................................29 4-1 Commercial and Indus trial Land Value Data....................................................................74 4-2. Commercial Land Value Data...........................................................................................75 4-3 Industrial Land Value Data................................................................................................76 4-4 Residential Land Value Data.............................................................................................77 4-5 Agricultural Land Value Data............................................................................................78 4-6 Alachua County Straight Lines Distances between Municipalities...................................79

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8 LIST OF FIGURES Figure page 4-1 Alachua County, Florida Study Area Map........................................................................80 4-2 2000 Alachua County Florida Study Area Co mmercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................81 4-3 2001 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................82 4-4 2002 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................83 4-5 2003 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................84 4-6 2004 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................85 4-7 2005 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................86 4-8 2006 Alachua County Florida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)...........................................................................................87 4-9 2000 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..88 4-10 2001 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..89 4-11 2002 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..90 4-12 2003 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..91 4-13 2004 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..92 4-14 2005 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..93 4-15 2006 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..94

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9 4-16 2000 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..95 4-17 2001 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..96 4-18 2002 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..97 4-19 2003 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..98 4-20 2004 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator).................................................................................................................. ..99 4-21 2005 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator)..................................................................................................................100 4-22 2006 Alachua County Florida Study Area Ag ricultural Land Values per Acre (2000 GDP Deflator)..................................................................................................................101 4-23 Alachua County Florida Municipality Central Place Orders and Straight-Line Distances (miles are rounded up to the nearest whole number)......................................102 4-24 Jonesville Study Area Timeline of Development Activities............................................103 4-25 Land rent theory. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 6 Concepts, Slide # 44, http://people.hofst ra.edu/geotrans, Date last accessed June 2007 [used with permission]...............................................................................................................105 4-26 Contemporary modifications of the land rent theory. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 6 Concepts, Slide # 46, http://people.hofstra.edu/geotrans, Date last accessed June 2007 [used with permission].....................................................106 4-27 Market threshold and range. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 3, http://people .hofstra.edu/geotrans, Date last accessed June 2007 [used with permission]....................................................................................107 4-28 Threshold range and market profitability relationship. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 4, ht tp://people.hofstra.edu/geotrans, Date last accessed June 2007 [used with permission]..............................................................108 4-29 Market size and thre shold. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7

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10 Methods, Slide # 5, http://people.hofstra.e du/geotrans, Date last accessed June 2007 [used with permission].....................................................................................................109 4-30 Conventional distance decay curves for retail activities. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 12, http://people.hofstra.edu/geotrans, Date last accessed June 2007 [used with permission].....................................................110 4-31 Central places theory (K=3). Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Concepts, Slide # 42, http://people.hofstra.edu/geotrans, Date last accessed June 2007 [used with permission]....................................................................................111 5-1 Central place theorys implied next po ssible central place in Alachua County..............119

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11 Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy CASE STUDY OF THE COUNTY ROAD 241 JONESVILLE-AL ACHUA, FLORIDA CORRIDOR By Sophia Janene Glenn December 2007 Chair: Rodney L. Clouser Major: Food and Resource Economics Local and state governments throughout the Unite d States (U.S.) have increasing concerns about population growth pressures in the urban/ur banizing areas. Due to growth pressures many different spatial patterns and distributions of land use are obs erved. These growth pressures necessitate management decisions concerni ng land use and land distribution. Understanding spatial distribution patterns of new developm ent/land use are important because different patterns over space result in different social, eco nomical, environmental and political impacts. Alachua County has had a steady increase in th e number of development projects over the last decade. As its population growth continues to increase the county is forced to accommodate this growth through residential and commercial de velopment. Much of the growth has been residential and commercial developments in the Jonesville-Newberry area. Another area of growth has been in the City of Alachua where investments are being made in commercial and high-end residential real estate developments. The population and development growth have im pacted the areas land allocation decisions as well as its infrastructure a nd services. Although th e land conversions and settlement patterns differ between the two areas, County Road (CR) 241 connects these two areas which creates interdependencies, as well as centripetal and centrifugal forces of development

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12 A single case study design was used to study th e patterns of development (residential, commercial and agricultural) of the Alachua-Jonesville Florid a CR 241 corridor for the years 2000 through 2006. The goal is to determine if economic theory can explain the development pattern of this corridor. Thr ee different subsets of land use th eories (location, central place and agglomeration) will be used to determine how well each of these individual theories explain, the development pattern. Individual theories alone cannot completely determine if economic theory explains the development pattern, but many aspect s of each theory are confirmed. The strategy for this case study is to use geographical informa tion analysis (GIS) to analyze land values and land use patterns; determ ine if central place theory can be used to analyze the development patterns of the surrounding citi es/municipalities and the Jonesv ille community; and to analyze the effects of agglomeration on the developmen t pattern. No theory alone can explain the development pattern, but combining the analysis of these theories can help explain the development pattern of the study area.

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13 CHAPTER 1 INTRODUCTION AND BACKGROUND Urbanization and Change The 1997 National Resource Inventory (NRI) repo rts on the dynamics of land use change from 1992 to 1997; just over 11.2 million acres of U.S. land were converted to urban uses. More than 50% of the land converted to urban uses during this time pe riod can be found in ten states, of which six are in the South. The state of Florida converted 825.2 thousand acres between 1992 and 1997 and it is estimated 1.2 million acres to 5 million acres between the years of 1964 and 1997. Conversion of land from rural to urban us e is more pronounced in Florida than in many other states. About 3% of the to tal land area in the United States is classified as urban. While Florida's urban land area is small (15%), it is st ill expanding more rapidly than most other states (Reynolds, 2001). The rural land-base changes as urban growth expands into rural areas. One important impact on the natural resource base is the conve rsion of land formerly used extensively for agriculture, forestry and open-sp ace (rural land) to urban us es. Given the United States marketing economy, with its emphasis on privat e property rights and flexible, sometimes nonexistent, land use controls, the amount of la nd converted from rural uses to urban uses increases directly with the growth of population in an area. If patterns of land consumption could be established and future urban land conve rsion could be better predicted, then better judgments could be made in developing la nd use policies (Reynol ds and Dillman, 1981). Florida and other areas of the South have e xperienced rapid population growth. Since the 1960s, population has increased faster in the South th an the rest of the U. S. population. The U.S. population grew at a compound rate of 1.1% fr om 1962 to 1997 while the population change in Florida was 2.95% per year. Between 2000 and 2030, th e U.S. population is expected to grow by

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14 approximately 82.2 million people, of which about 47% (38.7 million) of this growth will occur in the seven southern states (F lorida, Georgia, North Carolina, South Carolina, Tennessee, Texas, and Virginia). Florida alone will account fo r 15.5% of the US population growth during this period. In addition, Florida has th e distinction of having the most counties (14) of the nation's 100 fastest-growing counties; with Flagler C ounty being the fastest growing county in the country between 2000 and 2004 (Clouser, 2006). During the 1990s, Floridas population almost doubled every 20 years and is estimated to reach 20.3 million in 2020 (Bureau of Economic Business Research, 1997). Florida's growth rate between 2000 and 2030 is expected to rank as the third fastest-growing populat ion growth (79.5%) in the Unite d States. Since the 1920s, Florida has experienced a housing boom unlike any other state. As Florida's population increases along with growth rates, existing a nd new residents will place demands on the states fiscal, human and natural resources. Populati on increases will impact many aspects of the region. One of the most obvious and immediate impacts is in the areas of land allocations, decisions, infrastructure and services. Throughout the United States, changes in the composition of rural populations reflect a simultaneous increase in ex-urban /transitional land populat ions and decreases in traditional rural populations (Hart 1995). As populat ion increases, population centers grow and mature as urban areas and the demand for high-value uses of land also increases. As a result the value of land increases, land is then bid away from more exte nsive uses such as past ure, forestland and other undeveloped uses (rural lands) to urban uses As these population centers grow urban development becomes more compact, and the price of building sites increases. Those who want to develop land for urban uses are usually able to bid land away from extensive uses because of the higher capitalized net returns in the more extensive uses. Consequently, urban land

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15 conversion rates and settlement patterns very su bstantially between Metr opolitan Statistical Areas (MSA) (Reynolds, 1993). During 2004 Florida's agricultural land conti nued to increase in value and the state continued its population boom and strong nonagricultural demand for land by developers, investors and speculators. These factors contribu ted to the increase in value of transitional land being converted or likely to be converted to urban uses by 7% to 13% in the northern regions of the state (2005 Florida Land Values Surve y, "Nonagricultural Demand Costs Causes Land Values to Increase," UF/IFAS Electroni c Data Information Source (EDIS) FE545, http://edis.ifas.ufl.edu ). The population boom in Florida has contributed to the stat es housing boom. From 1980 through 1996, Florida's house prices, adjusted for in flation, fell by 7% according to the cost and quality repeat sales index of th e Office of Federal Housing Ente rprise Oversight (June 1, 2006). Between 1996 and 2004 Florida's housing prices rose by 70%, compared to 50% nationally. For the period ending March 31, 2006, Florida's house pr ice appreciation percen tage change ranked number two in the country, second to Arizona, having a one-year percenta ge increase of 26.6, a five-year increase of 101.5% and a 363.7% incr ease since 1980 (Office of Federal Housing Enterprise Oversight, June 1, 2006). This ra pid increase is widespr ead throughout Floridas Metropolitan Statistical Areas (MSA), with Florida having 10 of the top 20 highest MAS increases in the United States. Alachua County, Florida Alachua County, Florida lies in the north-central portion of th e Florida peninsula and is part of the Central Highlands, or Central Florid a range of the Atlantic Coastal Plain (Spangler, 1985). The county is comprised of approximate ly 892 square miles, with total county land acreage of 620,876 acres and 593,585 acr es (parcel acreage). Th e unincorporated area is

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16 comprised of 501,492 parcel acres (84.5% of Co unty) of which 456,055 parcel acres are rural unincorporated (90.9% of the uninc orporated area). The rural/agri cultural totals 372,766 acres. The urban cluster has 45,437 parcel acres and the municipalities are comprised of 92,011 acres (Alachua County Comprehensive Plan: 2001-2020). In 1997, Alachua County had 1086 farms, averaging 182 acres, with a total acreage of 198,193 acres (31.92% of total county land acreage) and an average value of $19,083.2 per acre. Cattle, dairy products, vegetables, tobacco, corn and timber generate the greatest sources of agricultural revenue. Timber produces the greatest revenue, comprising of approximately 296,535 acres in 1997 (47.76% of total County), 245, 012 acres in 2000 (39.46% of total County acreage) and 240,947 acres in 2001 (38.81% of total County). Alachua County has used a variety of t echniques and strategies as a guide for development within unincorporated Alachua C ounty. Some of these techniques include urban growth boundaries (i.e., urban cl uster line), urban se rvices line, trad itional neighborhood developments, mixed-use village centers, activity centered design standards, cluster subdivisions, transfer of development rights and community and neighborhood planning programs. The urban growth boundary (urban cluster line) defines th e area where urban growth should be contained for a period of time specified by the growth ma nagement program and is used to mark the separation between urbanized and rural land. The urban services line defines an area within the urban cluster to promote efficient use of land and infrastructure and to minimize sprawl by phasing development of land within the urban cluster. Also within the urban cluster are activity centers, which are designated and designed to provi de for the concentration of mixtures of higher intensity and density land uses in the urban area. Activity cent ers were classified by different levels and based on their primary and secondary functions, market size, area and intensity.

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17 Problems Setting Local and state governments throughout the Unite d States have increasing concerns about population growth pressures in th e urban/urbanizing areas. Due to the growth pressures many different spatial patterns and distributions of land use are obs erved. These growth pressures necessitate management decisions concerni ng land use and land distribution. Understanding spatial distribution patterns of new developm ent/land use are important because different patterns over space result in different social, eco nomical, environmental and political impacts. Therefore, growth management has come to the forefront for many local and state governments. Hanushek and Quigley (1990, p. 176) describe landuse rules as the most significant market intervention taken by state and local governmentd (Feiock, 2004, p. 363). To address the multiple issues posed by the state's con tinued growth and development, Florida has developed an integrated planning system inte nded to address and ensure the coordinated administration of policies. The integrated co mprehensive planning framework calls for planning at all levels of government. There are three ke y Florida Statutes that guide this planning: Chapter 380, Part I, the Environmental Land and Water Management Act; Chapter 187, State Comprehensive Planning; and Chapter 163, Part II, the Local Government Planning and Land Development Regulation Act. The Florida Legislature first visited the subj ect of growth management in 1972 with the adoption of two land use programs within Chap ter 380, Florida Statutes, Environmental Land and Water Management Act. This chapter dire cts the integration and coordination of land and water management activities and specifically aut horizes Developments of Regional Impact (DRI) and Areas of Critical Concern. The DRI is defined as a project that impacts multiple jurisdictions and provides for coordinated review of the projects thr ough the regional planning councils. The lead authority for DRIs rests w ith the department's regional planning councils.

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18 Areas of Critical Concern are areas having sign ificant impact upon envi ronmental or natural resources of regional or statewid e importance, including but not limited to state or federal parks, major rivers and estuaries, state environmenta l endangered lands, outstan ding Florida waters and aquifer recharge areas and unc ontrolled private or public development, that would cause substantial deterioration of such resources. Historical or ar chaeological resources, sites or statutorily defined historical or archaeological districts are also considered areas having significant impact upon private or public developmen t that would cause substantial deterioration or complete loss of such res ources sites or districts. Florida's 1985 legislature adopted the Florid a's Growth Management Act (Chapter 163, Part II, Florida Statutes, the Florida Local Government Comprehe nsive Planning and Land Development Regulation Act) which directs local government planning and includes requirements for Evaluation and Appraisal Reports (EAR). This required Florida's 67 counties and 410 municipalities to adopt local government comprehensive plans to guide future growth and development. These comprehensive plans contain elements that address future housing, transportation, infrastructure, coastal manage ment, conservation, recreation and open space, intergovernmental coordination and capital improvements. "Concurrency, is a key component of Chap ter 163. Concurrency requires that public facilities and services be provide d concurrent with the impacts of development to achieve and maintain the adequate adopted level of servi ce standard established by the local government within their jurisdic tion. Public facilities subj ect to concurrency include transportation, water, sewers, drainage, parks and recreation, solid waste, public schools or other facilities and services. In order to achieve and maintain level-of-s ervice standards, "concur rency" also requires

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19 intergovernmental coordination for future, publ ic facilities, five-year capital improvements schedule, and concurrency management syst ems to address development permits. The Growth Management Act authorizes the Department of Community Affairs (DCA), Division of Community Planning to review comprehensive plans and plan amendments for compliance, but it does not have regulatory authority to "enforce" local government development. The Division of Community Plan ning reviews all local development projects within the designated areas and may appeal to the Administration Commission, Governor, and any local development orders th at are inconsistent with stat e guidelines. They are also responsible for reviewing and approving am endments to comprehensive plans and land development regulations proposed by local governmen ts within the designat ed areas. Additional reviewing agencies include the regional planni ng councils and water management districts, Departments of State, Transportation, Envir onmental Protection, Agriculture, and the Florida Fish and Wildlife Conservation Commission. Intergovernmental coordination and capital im provements are of particular importance in comprehensive plans. Comprehensive plans are to include standards to ensure the adequacy of public facilities. Chapter 186, Florida Statutes pr ovides direction for the integration of state, regional and local planning efforts. It specifica lly requires the developmen t of agency strategic plans and Strategic Regional Policy Plans (S RPP). The North Florida Regional Planning Council consists of 11 north-central counties, including Alachua County. Their mission is to improve the quality of life of the regions citizens by coordinating growth management, protecting regional resources, promoting economic development and providing technical services to local governments. Within these 11 coun ties, the number of re sidents has increased dramatically during the last 10 years. The council believes that much of this increase is because

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20 people from other parts of the world and nation are discovering the amenities of North Florida living. The City of Gainesville, together w ith Alachua County, accounts for 50% of the total population of the region. Regional cooperati on and planning are becoming increasingly necessary due to the opportuni ties and problems that population growth can create for local governments. Being an associati on of local governments with st rong ties to state and federal agencies, the council is in a unique position to coordinate the development and implementation of strategies designed to addre ss the problems and opportunities cr eated by growth. The council also assists municipalities and counties in preparing concurrenc y assessments to evaluate the impact of development on the level of service fo r roads, water, sanitary sewers, solid waste, storm water drainage and recreational facilities. The council maintains a Strategic Regional Policy Plan, which addresses five issue areas: affordable housing, economic development, emer gency preparedness, natural resources of regional significance, and regional transportation. This plan was used as the basis for reviewing local government comprehensive plans and amendm ents during the year. The plan is a longrange one for the physical, economic and social development of the region, which identifies regional goals and policies designed to promot e a coordinated program of regional actions. Within this plan, the Metropol itan Transportation Planning Orga nization was formed through an interlocal agreement signed by the Florida De partment of Transporta tion, Alachua County and the City of Gainesville. This organization wa s formed to conduct long-range transportation planning activities in the Ga inesville Metropolitan area. Local Comprehensive Planning The cities of Alachua and Newberry, includi ng the Jonesville community, have their own individual comprehensive plans fo r development. All the comprehe nsive plan strategies address the long-and near-term needs and desires of each community and are consistent with the Florida

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21 comprehensive plan as well as the North-Central Florida Strategic Regional Policy Plan. Each city recognizes the critical importa nce of its planning efforts as pa rt of the north-central Florida region. Each acknowledges interdependence th rough the connectivity of County Road 241, and the City of Gainesville as the major metropolitan statistical area in common. As Alachua County's residential growth contin ues to increase, the county is forced to accommodate this growth through development. Therefore, Alachua County has had a steady increase in the number of development projects over the last decade. Although the City of Gainesville had the greatest num ber and largest size developments, other areas of the county have had similar development. During 2005, Al achua County issued a record 443 housing unit building permits (180 in 2004) (SOCDS buildi ng permit database) despite the new building codes and impact fees charged to developers to offset the costs for roads and county services (Alachua County Growth Management). Many of these building permits were for homes and business developments in the Jonesville-Newber ry area as well as the City of Alachua. Investments are being made in commercial and highend residential real estate developments in these areas. Within the Jonesville Community a nd the City of Alachua, developers have made extensive use of the concepts of traditional neighborhood developments, mixed-use planned developments, village centers and activity centers within the urban service line. These types of development are strongly encouraged in the county comprehensive plan and have been identified as some of the techniques and strategi es used for developmental controls. Traditional Neighborhood Developments integr ate housing with other uses to create a walkable interconnected community. This deve lopment is in contrast with conventional developments, characterized by separation of land uses and housing types within developments and only accessible by automobile (Danny et. al., 2000). Walkability is the principal focus of

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22 this type of development as well as village centers which encourage th e use of non-automobile forms of transportation by integrating retail services within residential area s. Village centers are provided with incentives to encour age their development and are a llowed in the urban residential areas as part of the new trad itional neighborhood development. Activity centers are located within urban clus ters and provide for the concentration of mixtures of higher intensity and density land us e. Different levels of activity centers are identified based on their primary and secondary f unctions, market size an d area, and intensity. They are identified as retail-or employment-oriented and have hi gh, medium or low intensity. A center's design includes a balanc e of mixed-uses integrated with a pedestrian-friendly environment through an overall design framework of size, scale, portion and material. The Jonesville community center is designated as a lo w-activity employment cen ter, and is designed to promote the area around the in tersection of Newberry Road (State Road 26) and County Road 241 as a low-intensity employment-oriente d local point and a mixed-use center. Jonesville and Alachua Communities Jonesville area development has exploded within the last 10 years. It is positioned both geographically and economically to take advant age of Alachua County's westward growth and the City of Newberrys infrastructure and equipmen t (water, sewer, waste di sposal and utilities). Many believe that the commun ity's designation as an Activ ity center has spurred the development of projects that ar e well suited to the surrounding area, taking into account market demands and environmental sensitivity. Hawley R ealty and Investments, In c. has played a large role in the real estate sales and development in the area and has been instrumental in attracting the Publix at Steeplechase, Kazbor's, Tuffy Muffl er, Tractor Supply and other retail outlets. In the early 1980s, the company developed resi dential subdivisions, along County Road 241 between Jonesville and Alachua such as Canterbu ry Farms, North Central Florida's first gated

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23 community. The Jonesville community has b een nationally recognized for its award-winning Traditional Neighborhood Development, Town of Tioga, which exemplifies the modern-day mixed-use center. The concentration of devel opment in this area has placed a great toll on Newberry Road, State Road 26, between Newberry and Gainesville, which has caused the City of Newberry to turn away developers due to capacity limits. The Newberry City Commission has committed $58,000 to a study that will lead to a tr ansportation master plan for the city. The Florida Department of Transportation is also studying solutions to Stat e Road 26 congestion and has discussed creating a bypass arou nd the city that would take a decade or longer to finish. The City of Alachua has experienced growth as well, though a large portion of its growth has been in business development. The city is home to corporations, technology incubators, local businesses and startup companies. The Al achua US 441 corridor is being developed into a "corporate corridor (e.g. Sabine, J. A. Weber, Pr ogress Corporate Park and Alachua Professional Center). Hawley Realty and investments, Inc. has worked on several prop erties in the City of Alachua, including Alachua Town Centre and the Progress Corporate Park on US 441. The City of Alachua has attracted national corporations to its area, including Sysco, North America's largest food distributor. Alachua County property values have increas ed at unprecedented ra tes in 2006. The total value of all property in Alachua County jumped 15.5%, to more than $ 20.6 billion according to the Alachua County Property Appraiser's assessm ent. The increased property values have positive and negative effects on the community. The positive effects are increased tax revenue. New construction projects in the county duri ng 2006 assessed values were at more than $381 million and account for 25.5% of the increase in pr operty values. Increased tax revenue, from the $381 million increase in assessed value, could be spent in areas such as infrastructure and

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24 social and educational programs. One of the nega tive aspects of increased property values is the potential for increased tax burdens placed on re sidents and businesses. The value of singlefamily homes in the county increased about 18.4%. If tax burdens did increase it may be more difficult for young families, retired persons and lo w-income individuals/families to find housing. Although regulations are in pl ace to control/manage land use, population growth and increased development can still create and mainta in a path of its own. Therefore the predicted outcomes of growth and development are still questionable in the case of Jonesville. The settlement and development patterns for the Ci ty of Alachua and Jonesville are different, reiterating Reynolds (1993) obser vation that urban land conversion rates and settlement patterns vary substantially between areas. The population growth in these areas has incr eased ex-urban/transi tional area populations in more rural population centers and has increased land values. The increases in population and development in both areas has impacted land allo cation decisions, infrastructure, and services. Although concurrency measures are in place to remedy these issues, there are still issues with transportation and infrastructure. The City of Newberry and the Jonesville community experienced more growth than anticipated. Th e unintended consequence of the unanticipated growth and development is an in adequate supply of affordable housing in these areas due to the higher land values and more high-end housing deve lopments. Although higher land values have increased tax revenues, there is still a lag in infr astructure services. It is no surprise that developers are taking advantage of the new growth management regulation in these areas and are capitalizing on the high net returns from hi gher density land values. The Traditional Neighborhoods, mixed-use developments and clus ter subdivisions incen tives provided more flexibility to developers.

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25 Population Growth The population growth in the study area has been increasing at a signifi cant rate from 1990 to 2000. The City of Newberry has had the most significant increase in population 50.4 percent between 1990 and 2000 followed by Alachua at 2 5.7 percent and Gaines ville at 11.2 percent (U.S. Census Bureau) (Table 1-1). The significan t growth in the Jonesville community can be attributed to the growth of the City of Newberr y. The Jonesville community is east of the City of Newberry, which may explain the significant resi dential growth in that area. In addition, Jonesvilles growth may also be attributed to the growth of the City of Gainesville. As Gainesvilles population increases, one would e xpect a subsequent expansion of the city boundaries westward. The projected population changes from 2000 to 2006 (Table 4-6) shows that the cities of Newberry and Gainesville will experi ence a 12.8 and 12.2 percent population increase respectively, while the City of Alachua will ex perience an estimated population increase of 28.2 percent. During this time frame, the city with the largest percentage population growth will shift from Newberry to Alachua while Gainesville and Newberrys have similar population increases. The If one assumes that population growth cau ses congestion and places more demands on land use, then Gainesvilles populat ion increase may exert pressure on the urban/rural boundary. As the population on the outer skirts of Gainesville experience in creasing congestion, people will attempt to avoid congestion by moving further into the rural less congested areas. The Cities of Newberry and Alachua are closest to Gainesvi lle and the population spillovers will have a tendency to flow in these directions. Development in the Jonesville community s uggests that Gainesvill es growth pressures have induced pressure on the citys boundaries westward towards Newberry in the Jonesville neighborhood. One can also extrapolate that Newbe rrys population will increase at the rate of

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26 the spillover from Gainesville. Therefore th e population growth rate s of the two cities are interdependent and the increase in Newberrys population has been concentrated in the Jonesville community which was also designated as an activity/employment center in the 2001-2020 Alachua County Comprehensive Plan. The population growth of Alachua has contin ued to grow since 1990, increasing to 28.2 percent between 2000 and 2006. This increase may al so be attributed to Gainesvilles population spillover and/or the citys commercial/industria l enterprises growth. The commercial/industrial growth may have been facilitate d by the citys proximity to Inte rstate 75. The City of Alachua also has a designated rural employment activity center. The employment center is designed to attract and accommodate varies commercial/industrial firms to boost employment, income, and quality of live for rural residents. The relativ ely low land values and interstate access makes the area more attractive and thus po ssibly contributed to the increas e in population growth. In 2007 the median home costs for, Newberry, Alachua and, Gainesville are $294,500, $279,900 and $259,900 and the median household income is $37,366, $44,541 and, $31,283 respectively. The median age was 34.6, 35.6, and 28.4 for Newberry Alachua, and Gainesville (Sperlings Best Places, www.bestplaces.net ) Problem Statement The City of Gainesville and Alachua C ounty account for approximately 50% of the regional population and population grow th is expected to continue in the future. This case study concentrates on the developmental growth in the County Road 241 Alachua-Jonesville, Florida corridor where the population growth is expected to increase over time and exert developmental pressures on the surrounding communities of Ne wberry, Alachua, Gainesville and the adjoining urban-rural fringe. The record number of housing/building permits issued in the county during 2005 is an indication of the rate of development growth in the county.

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27 Although current growth management policies have been used to direct/manage county development, it has not slowed developmen t but seems to have induced it. County developmental growth has been moving in a we st/northwest direction towards the cities of Newberry and Alachua and the Jonesville commun ity. Besides Jonesvilles designation as a low-employment mixed-use activity center the community has the infrastructure and is geographically located in an area to take advantage of the count y growth and development. This study uses the case study method to study and analyze the development pattern in the Alachua-Jonesville corridor during the 2000-2006 time periods. Three land use theories will be used to analyze the study areas developmen t pattern; classical location theory using von Thnens bid rent method of concentric rings, centr al place theory and agglomeration theory. Geographical Information Analysis (GIS) will be used to apply von Thnens theory to the study area. The study area roads were identified and a one mile buffer on both sides of the road will encompass the study area. The Arc Info software spatial analysis tool, inverse distance weighted interpolation, will be used with GIS pa rcel and county property appraisers data to generate the land value per acre surface. These surfaces will be classified by land use; commercial/industrial, residential and agricultural. The land values per acre will also be classified into group values and color codes. Each land use an d land value per acre will be analyzed to determine if the land values are consistent with the bid-rent theory. Central place theory analysis will be conduc ted using a map of Alachua County cities and municipalities using the straight line distances from each city/municipality. This theory suggests that cities of the same order offering similar good s and services will be located equidistance from each other and form an equilateral triangle/hexag onal pattern. This study will concentrate on the

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28 cities of Newberry, Alachua, Gainesville and th e Jonesville community. The results of this analysis will then be used to analyze the possi ble development of the c ountys central places. A timeline of developmental activity will be us ed in the agglomeration theory analysis. Developmental data was obtained from the Department of Growth Management Developmental Division using the section, township, and range of the study area sorted by year and plotted on a timeline of developmental activity. The timeline w ill then used to analyze the spatial distribution and pattern of new development; when, where and what type of development took place and the results of the development patt ern over the 2000-2006 time period. Finally, based on the information collected and the analysis co nducted, speculation on central place development in Alachua County will be addressed. This combines both the empirical and theoretical asp ect of future land use and development in the county.

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29 Table 1-1. Study Area Population and Percentage Change from 1990 to 2006

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30 CHAPTER 2 LOCATION THEORY AND LITERATURE REVIEW Introduction Land and land usage have been a universal c oncern throughout history. The development of agricultural land is for all pr actical purposes irreversible and re sults in a loss of option value, which may not be taken into account by land markets (Hailu and Brown 2005; NERCRD 2002). This multifunctionality of land in agriculture keeps it in the public eye and on many research agendas (Hailu and Brown, 2005; Batie, 2003; Able r, 2003). Walker and Solecki (2004) stated that land cover and land use cha nge result from economic and de mographic interactions between cities and hinterland, as well as from specifically agricu ltural and urban proce sses. The need to know why and to understand how th ese changes are major concer ns of economic geographers, urban economists, developmental economists, spa tial economists, regional scientists, planners and policymakers today. A better understanding of the way cities and regions work and function can contribute to better policymaking, thus improvi ng the quality of life and standard of living of the urban and rural inhabitants (McCann and Scheffer, 2004, p. 177) The search for answers to these questions has been the study of scholars from many different disciplines, each having its own particular foci in the different uses of land and space. McCann and Scheffer (2004), regional scientists, st ated that the aim of regional science is to better understand the structure and function of cities and regions while taking into account the multifaceted dimensions of the phenomena whether ec onomic, social, political or environmental. In the field of regional science, an interdisciplin ary social science enterp rise is concerned with analytical approaches to problems that are specifically urban, rural or regional. Each discipline,

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31 having its own specific foci and aim, has resulted in a multitude of land use/location,1 spatial and regional growth theories that often only deal with a particular portion of the spatial structure. Many of the theories within disciplines overlap and become blurred, particularly due to the tendencies toward interdisciplinary research. The lack of spatial analysis in mainstr eam economics has been addressed by Krugman (1995): "It's almost 40 years since Walter Isard at tacked economic analysis for taking place in a wonderland of no spatial dimensions, yet his plea for spatial economics has gone virtually unanswered. In 1956, Isard's Location in Space Economy made a powerful effort to get economists to take space seriously. It was th e first big effort to get space into economics, although Ohlin (1933) previously proposed develo pment of general locati on by interacting trade and location theory. Isard made the previous ly inaccessible German tradition of Germanic geometry, the geometry of location on a two-di mensional landscape, available to monolingual economists, creating an important practical interdisciplinary en terprise of regional science founded in 1954. He and a core group of scholars and practitioners promoted the objective and scientific analysis of se ttlement, industrial location and urban development. Given the broad spectrum of di sciplines dealing in spatial, locational/geographical land use and land use change theory, this section will provide a historical background of theory, usage, application and the evolution of what we observe today. The following sections will begin by identifying some of the more prominent figures in historical location theory; they, along their contributions, usage and applications. 1 In this study, location and land use theory will be used somewhat interchangeably, defining land use theory under the umbrella of the broad heading of location theory.

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32 Land Use Change Economists are interested in change becau se of the connections between economic choices regarding land use and the aggregate im pact of land use change to include various applications for policy (Bell and Irwin, 2002). Therefore, studying land use change allows application of economic theory to analyze local and regional land use patterns, assists in improving the understanding of land use impacts and bring about the assessment of various factors influencing change. The results ca n offer understanding and improvements in the management of land resources. Land use planning has developed and continues to evolve in order to manage and direct the development of land. Land use change is the result of complex interactions between physical, socioeconomic and legal issues with in the geographical/reg ional context. The geographical/regional context in itself is complex, filled with uncertainty and error. In other words, any examination of land use is by de finition imprecise and incomplete (Johnson, 2004) and therefore the resulting impacts from land us e change are uncertain (Mojica and Bukenya 2006) Many studies have been conducted to mode l land use change determine factors influencing change and measure impacts of land use change. These studies have covered many issues concerning land use change, such as la nd conversion to urban us es and urban sprawl (Carrion-Flores and Irwin, 2004; Irwin and Bo ckstael, 2002; Bell a nd Irwin, 2002; Reynolds, 2000; Lin et al., 2005). Studies have also been conducted ad dressing issues related to agricultural/forest and open-space (Kline a nd Alig, 1999; Nzaku and Bukenya, 2005; Johnson, 2004; Sokolow and Kuminoff, 2000). The Econom ic Research Service (ERS) and the Natural Resource Conservation Service (NRCS) of the U.S. Department of Agriculture have conducted several studies of land use cha nges and the dynamics of urbanizi ng areas over the last three

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33 decades (Heimlich and Anderson 1987; Heim lich and Reining, 1989; Vesterby and Brooks, 1989; Vesterby and Krupa, 1997). Many agree that the urban "pus h factors" and rural and subur ban "pull factors determine spatial patterns of development, and hence agricu ltural land use change. Othe r factors that affect regional growth and land use change include pu blic investment in tr ansportation technologies and improved access to outlying areas (Hailu and Brown, 2005). Irwin and Bockstael (2002) suggest that urban spatial stru cture (land use change) is determined by interdependencies among spatially distributed agents. They adopt the co mmon theme that urban spatial structure evolves from a tug-of-war between attracting and repelling forces that result from economic interactions among agents. The individual agents location deci sions and hence, the land use patterns, is determined by the relative magnit ude of these interactions. Many other studies suggest that demographics play an important role in land us e change. Studies on population demographics in urban areas are thought to be a significant factor in fluencing rural land conversion (Ahn, 2002, Reynolds, 2001, Ramsey and Corty, 1992, Mojica and Bukenya, 2006, Nzaku and Bukenya, 2005). There is a significant amount of literature studying the many factors influencing land use change. Thus far we have concentrated on microec onomic approaches of the urban land rent theory; the behavior of the individual consumer or producer aggregates the behavior of others to derive the resulting land use patt erns. In general, the centr al theoretical conclusion of economists on land use and land use change is de termined by relative rent s, economic factors, social factors, political factors and land characteristics such as location and soil fertility. Some of the basic assumptions are profit maximization of rents, maximization of utility and the effects of supply and demand on land use patterns base d on a perfectly competitive market, rational

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34 agent behavior and a single equilibrium patter n. The macro-level economic theory approaches deal with aggregate level data and utilize aggregate concepts that are broadly described in the fields of regional science, regional economics an d development. In spite of the improvements and expansion of land use theory, Walker (2004) suggested that land cover and land use change still remain under theorized. He stated that appl ications making use of structural elements that specifically attempt to examine and explai n these issues are few and far between. Location Theory Location theory is concerned with the geograp hical location of economic activity and is an integral part of economi c geography, regional science and spatial economics. Theory, as defined by Chapin and Kaiser (1979, p. 27), "is a system of thought which, through logical constructs, supplies an explana tion of a process, behavior or phenomenon of interest as it exists in real ity." Because theory denotes knowledge, the nature and status of theories differ among different epistemologies (Briassoulis, 2000)di scourse on how knowledge is acquired, transmitted, altered and integrated in to conceptual systems (Johnston et al., 1994, p. 168). Given the definition of theory, Briassoulis (2000) defines theory of land use change as a set of propositions used to understand the "wha t" of land use change and the "why" of this change. In other words, a theory of land use cha nge describes the structure of the changes in the uses of land from one type to another-and explai ns why these changes occur, what causes these changes and what the mechanisms of change are. Briassoulis reiterates Sack (1990), "knowing the why is essential if we expect to change what we do"; in ot her words, the theory is a guide to policy on land use change, a strong and cri tical demand of the contemporary times. Now, having a better understanding and definiti on of theory, this section will discuss the origins of location theory and its development of what is practiced in economic location theory today. This section on location theory will be divi ded into four parts. Part one concentrates on

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35 what is referred to as Classical Location Theory". The se cond portion deals wi th the "Central Place Theory" which is a spin-off, or evolution of the Classical Location Theory. The third part is defined in the broad term of agglomeration a nd economic activity. The la st theoretical portion deals with growth and economic development. Classical Location Theory Classical location theory concentrates on the le ast cost theory of lo cation. The object of location theory is to answer the question: W hy do particular production/ economic activities (such as plants, offices, public facilities, etc.) choose to estab lish themselves in pa rticular place of a given space (Ottaviano and Thisse 2002)? Walker and Solecki ( 2004) stated that anthropogenic changes in land-cover, land use and the environmen tal problems that arise as a result are mainly driven by the desire to use land as a factor in the production of agricultural goods and residential amenities. In addition, they also state that landcover and land use change result from economic and demographic interactions between city and hinterland as well as from specifically agricultural and urban processes. The site selection process in this approach is viewed in terms of cost minimization and emphasizes such vari ables as labor cost, transportation costs and agglomeration economies (discussed further in agglomeration and economic activity). The foundation of location theory can be attrib uted to Thomas Robert Malthus' theory of population growth which emphasized the rigid dependence of population growth on the food supply, and thus focused on the limited supply of land. His ideas led to the concept of diminishing return, and the theory and nature of land-rent (Blaug, 1985). Land use theory, therefore, was founded and further expanded in the field of agriculture with the contributions of Ricardos (1821) theory of differe ntial fertility of land and land rent. He focused on local productivity difference, and developed the theo ry of land use based on relative fertility. Ricardos trade-based theory viewed rent as a function of land pr oductivity/fertility and was later

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36 generalized to consider exoge nous technological differences fo r all types of goods, not just agricultural goods. Ohlin (1933), building on Ricardo's trade-base d land rent theory proposed the development of "general lo cation theory integrating trad e and location theory. General location theory builds on differences in factor endowments, such as land, labor, capital, technology etc., over space, thereby developing the so-called Hecksche r-Ohlin theory of trade. The Ricardian and Heckscher-Ohlin approaches have led to sophisti cated theories of location and trade that rely on the existe nce of (exogenous) comparative advantages across locations. Although these approaches are central to international trade, they play a much less important role in the development of spatial economic theory (Duranton, 2005). The theory of land rent was continued by von Thnen, known as the father of location theorists. In von Thnens (1826; 1966) bid-rent model, the maximum amount a renter is willing to pay for the use of land, explained the effects of location and transportation costs on Ricardos land rent. The bid-rent model, the most productive lands with th e lowest per unit cost generate the greatest economic re nts. Von Thnens theory set th e optimum distri bution of rural land uses around a town market where land values differ only with the distance from s towns center. Using von Thnens method, land use patter ns generate a set of concentric rings around the town center. He saw land rent as a functi on of access to the region's core where population and the bulk of economic activity took place. Land at the central core is used most intensively and land use intensity decreases with each out ward concentric ring. This theory of bid-rent is highly conditional on the transporta tion cost of product and labor markets. Bid-rent theory is known as the least cost location th eory, where agricultura l and industry locate as close to markets as possible, thereby minimizing their cost of transportation for the goods produced. This basic model has been expanded and used in many studies to address land use cha nges in the fields of

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37 agriculture (Thnen, 1966; Dunn, 1954; Isard, 19 56), urbanization (Al onso, 1964; Muth, 1969; Casetti, 1971; Mills, 1972a, 1972b; Solow, 1973), transportation (Muth, 1969 and Beckman, 1974), social issues (Beckman, 1973 and Wheaton, 1978) and multiple central business districts (Fujita and Krugman, 1995) Extending von Thnen's theory, the concept of potential rent was developed by Chomitz and Gray (1996) and Walker and Solecki ( 1999). They recognize the importance of bid-rent and its link to transportation costs as a factor affecting change. Potential rent becomes true rent when transportation costs are reduced due to new infrastructure or new infrastructure providing access to the development of undeve loped land. The speculation of potential rent is the incentive driving land acquisitions in an areas anticipated development. Both of these models directly relate shares to land rent determinants. Th is concept has been used by many (Nelson and Hellerstein, 1997; Wear and Bolsta d, 1998; Chomitz and Gray, 1996) to statistically estimate the accessibility of land. Given the broad application of von Thnen's bid-rent theory, its applicat ion and focus were modeling the microeconomic land use aspects of a monocentric economy. Von Thnen's model has primarily been used in th e analysis of urban economic gr owth and, although macroeconomic applications have been used to describe fr ontier evolution in larg e regions (Katzman, 1977; Cronon, 1991), microeconomic applications are us ed most frequently. The basis of von Thnens bid rent theory has also been used in multi-centric city application as well (Fujita, 1989). The bulk of microeconomic applications have been on specific places where local products and labor markets play the main role in bid-rent theory. Von T hnens bid-rent theory has evolved from explaining agricultural la nd uses to urban and regional land uses.

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38 Taking into account the urban aspect of la nd use theory, the Ricardian and von Thnen models have been combined into an integrated land share model that e xplicitly includes both rural and urban land use (Hardy, et al., 2000). Walker ( 2001) integrated urban and agricultural spaces by linking land cover change and economic development in the Florida Everglades by merging von Thnen 's model with Alonso's ( 1964). Alonso, one of the University of Pennsylvanias first Regional Science Departme nt graduates, published Location and Land Use in 1964. In his dissertation he defined a m odeled approach on the formation of land rent in urban environments. Cronon (1991) also used this method to describe the linkages between the growth of Chicago and frontier expansion in the "Great West". Among the economically oriented land use theorists, Burgess (1925) assert ed that land use patterns of cities consist of geometric patterns of concentric circles of different land values surrounding a business district (i.e., von Thnens bid-rent theory ). Barlow's theory expands the definition of land rent for given uses as decreasing functions of fertility and the location index or use capacity (Miller and Plantinga, 1999; Barlowe, 1958). Alfred Weber (1909; 1929), among others, analyzed the locati on decisions of a firm in his plant location model. In his publication of T he Theory of the Location of Industries, he identified the optimal location of a firm by de riving the minisum location problem that aimed to minimize the weighted sum of the Euclidean di stances from the plant to a finite number of sites corresponding to the market s where the plant purchases its inputs and sells its outputs, therefore minimizing cost. The optimal solution is to find a site that is a dominant place/central location where its weighted sum is greater or equal to the sum of the weight s of all the other sites (Weiszfeld, 1936). This result may explain the locational decisi on made by seemingly different firms to build in a large metropolitan area (e .g. steel mills next to iron mines and other

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39 minimarkets). It also suggested some form of inertia in a firms locational behavior (Ottaviano and Thisse, 2002). The focus of Webers theo ries has been moved from minimization of transportation costs to more standard microeconomic appro aches of profit maximization. Additional variables have been added to this framework to better understand the influences of geographical and economic factors on location. Sakashita (1967), used production and demand functions along with firm theory to determine the location of firm s. Ziegler (1986) used these as well as elasticity with respect to distance and quantity and the price el asticity of demand for inputs in determining firm loca tion. Although Ziegler is best know n for firm location theory, his main concern was to explain the formation of industrial clusters (Isar d 1956, chap. 2) thus introducing agglomeration and deglomerative forces to location theory. The topic of agglomeration and location theory will be vis ited in more detail in the agglomeration and economic activity section. Sakashita also addressed grouping production unitsanticipating Lschs ([1940]1954) ma rket areas. Central Place Theory Christaller (1933; 1966) and Lsch (1940; 1954) are credited as the founders of central place theory. Their goal was to explain the spa tial distribution of economic activities within a hierarchical system of urban cen ters. Giving credit to von Thnen as the origin of geographical economics, they used his work as the basis of their theories. Alonso also applied von Thnens theory to create the urba n land market theory. Christallers central place theory was developed in his 1933 dissertation, "The Central Places in Southern Germany", where he suggested there are laws determining the number, size and distributions of towns. Transportati on costs, population and consumer preferences determined the location and size of markets/cente rs supplying a particular type of good, thereby forming levels of hierarchy. He found that people were more willing to travel greater distances

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40 to obtain higher order goods and servicesones with a larger range and considered more durable, valuable variables such as jewelry, cars, shopping malls, etc. He determined an urban hierarchy of settlements having seven principal orders prov iding different groups of goods and services. Christaller found that settlements were regularly spaced apart with larger centers spaced further apart than smaller centers. These settlements ha d a tendency to form into a triangular/hexagonal lattice that was found to be the most efficient pa ttern for travel between settlements. Lsch has been given credit in proposing these hexagons as an optimum rather than a market outcome. Loschs theory has been used in market area st udies, retail location plan ning and the planning of new towns. Central place theory provides the principal conceptual lens economist use to understand the geographic implications of private-sector activity (Castle, 2003, p. 26). It is a geographical theory used to explain the size and spacing of economic activity or hierarchies of economic activity based on population and tran sportation. In this theory, centralization is considered a natural principle of human settlement and economic activity. Von Thnen fi rst used this concept of centralized economic activity in his location theory. This theory is primarily concerned with where and why cities are established. It is a power ful organizing principl e for looking at and thinking about urban systems and provides insi ght about the organization of economic geography (Mulligan, 1984). Central place th eory tells a story about how agen ts interactions lead firms to cluster together into a hierarchy of citiesa city is considered to be a clustering of firms and workers (Krugman, 1995). This clustering effect w ill be discussed later in the agglomeration and economic activity section. Central place theory does not deal with agent interactions or market structure. They are not necessarily theories of change due to their emphasis on individual activities (micro aspects) located in space (Brias soulis, 2000). Aspects of agent interactions and

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41 market structure are one of the links in central place theory to agglomeration economies. This theory is important to understand due to its dir ect impact in the public policy sector. Because state and local governments are tasked with the primary responsibility of public policy it is important that policies and policy implicati ons are considered a nd addressed properly. Basic questions in the theory of central places are: Unde r what conditions can production be decentralized and when is it profitable to relocate a certain production activity outside the metropolis in cities of lower order? This theo ry relies on two basic co ncepts: (1) the population or market determines the production of goods and se rvices and (2), the di stance or transportation costs that consumers are willing to travel or pay for that good. To understand this theory, consideration must be given to the combined production and tr ansportation costs for a product distributed over a market of a given radius (Beckmann, 1995). Von Thnens model of an economy has a single central city, the central business district ( CBD). All economic activities with increasing returns to scale are concentrated in central loca tion. The agricu lture and local services are continuously extended in a twodimens ional region (outside of the central city) and endowed uniformly with land suitable for cult ivation. Von Thnen's economic growth process was driven by simple population growth. In his model, as production in the agricultural sector increases, transportation demand rises due to incr eased distance and the city grows in response to increasing demand for both transpor tation and industrial goods. The central city or central business district (CBD) is the beginning point from which all other economic activity stems and has become the principal orientation of the field of urban economics (Briassoulis, 2000). Many different asp ects of urban and regional studies have been conducted concerning housing (Romanos, 1976). Bockstael and Irwin (1999) analyzed urban spatial structure and urban policy impact analys is. Fujita and Thisse (2002) focused on how

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42 population growth fosters the de velopment of incumbent cities and provides incentives to establish new cities. They suggested that as population grows, new cities emerge when some critical population threshold is reached (Fujita and Mori, 1997). Walter Isard was one of the first pioneers in this field with his firm location theory and formation of industrial clusters. By the turn of the 19th century employment shifted from rural agricultural-based employment to consumer and producer services and manufacturing. This was due in part to technological improvements in th e agricultural sector reducing the demand for labor in rural areas. The technological advances in the industrial sector pr ovided jobs for workers who migrated to urban areas for altern ative employment. As workers mi grated to the urban areas, the high order, high value added services and manu facturing became concentrated in the major metropolitan areas. Given this shift in employment from agriculture to industry, land use theory had to incorporate urban and industrial aspects. W. Alonso (1964) applied von Thnens theory and refined it to crea te the urban land market theory. This theory uses the concept of the bi d-rent function for households and/or firms to explain location behavior and spatial structures of urban land use. Hoover and Giarratani (1984, p. 153) defined household bid rent as the "maximum rent" th at can be paid for a unit of land some distance from the city center if the house hold is to maintain a given level of utility. There is only one bid rent associated with a given level of utility. The city center is considered the central business district ( CBD) and household utility is assu med to be a function of housing distance from the city center and other goods (Chapin and Kaiser, 1979; Romanos, 1976). As the distance from the CBD increases, land rent decreases, and households and/or firms choose locations that maximize their u tility subject to thei r budget constraints. Briassoulis (2000) concludes that the bidding proce ss is a realistic account of the wa y land is allocated to various

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43 competing uses and it has been used in the th eoretical and modeling ex ercises that followed Alonso's original contribution. The theory has been used broadly in the anal ysis of urban spatial structure as well as impact an alysis of urban policies (see Irwin and Barksdale, 1999). In 2001, Walker combined von Thnens theory with the urban model of Alonso (1964) to specifically address changing regimes of natu ral areas encroachment in South Florida. This model was developed to take into account the linkages between urban and rura l sectors (Walker and Solecki, 2004). Concepts of central place theory have been modified and expanded to cover many different concepts. Wu (2002) used environmenta l amenity values to explain urban sprawl and the economic landscape. Wu (2002) and Wu and Plantinga (2002) studied the influence of open space on urban landscapes. In this study they found that residents prefer to live close to open space and that open space amenities attract migrants to the city. Others, such as Krugman (1991, 1995) and Kilkenny (1998a, b, 1999), have modi fied central place theory and developed concepts of new growth theory (this concept will be discus sed further in the growth and economic development section). Over time, agricultural and urban theories have expanded, been modified and developed taking into account other soci al, political, environmental and ecological factors aimed at providing improved operational versi ons of land use theories. James Beshers (1962) concluded that social as well as economic conditions in fluenced land use patterns and Walter Fry (1947) concluded that cultural factors/social values exert a direct and positive influence on land use. Political as well as social and economic factors we re taken into account by F. Stuart Chapman Jr. He saw the political, social and economic sphere s as consisting of three different groups of

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44 values labeled as economic, political and social, a ll of which lead to different types of land use patterns. Agglomeration and Economic Activity Agglomeration Agglomeration economies have been thought to be the driving force behind explanations of geographical concentrations of economic activity in population within cities. Agglomeration can be described as the spatial concentration of economic activity. Fujita and Krugman (2004) stated that agglomeration (or the clustering) of economic activity occurs at many geographical levels, having a variety of compositions. A gglomeration can occur when small shops and restaurants are clustered in a ne ighborhood or when cities having di fferent sizes cluster or when industries from industrial districts. These concentrations are a resu lt of some set of cumulative processes whereby geographic conc entration can be self-reinforci ng (Fujita, et al, 1999). The field of new economic geography was developed to assist in the e xplanation of formations of a large variety of cumulative processes of econo mic agglomerations (or concentration) and the geographical space of a region focusing on the role of linkages. Understanding the formation of agglomeration economies is critical for th e design of effective urban policies Fujita and Thisse, in Agglomeration and Economic Theory, 2002. addresses the three main causes for the formation of various types of economic agglomeration: increasing returns to scale, externalities, and imperfectly comp etitive markets with general and strategic interdependencies. A. Marshall (189; 1920, Chap. X) stated that externalities are crucial in the formation of economic agglomerations. His concept of externalit ies captured the idea that an agglomeration is the outcome of a snowball effect in which a grow ing number of agents want to congregate to benefit from a larger diversity of activities and higher specialization (Fujita and Thisse, 2002).

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45 Matsuyama (1995) found that these cumulative pro cesses are now associated with the interplay of pecuniary externalities in models combini ng increasing returns and monopolistic competition. There are two categories of externalities: technological and pec uniary. Technological externalities, sometimes referred to as spillove rs, deal with nonmarke t integrations whereas pecuniary externalities are produ cts of market interactions and are prevalent in imperfectly competitive markets Fujita and Thisse (2002) stated that increasing returns in production activities are needed to explain economic agglomerations without appealing to attrib utes of physical geography. Economists, geographers and historians consider increasing return due to economies of scale, the most crucial factor in the emergence of cities. Spatial patterns of economic growth will be quite different, depending on the extent to whic h varying levels of economies of scale are operative in different locations (Kurgman, 1999). The trade-off between increasing returns in production and transportation costs is central to the understanding of the geography of economic activities (Fujita and Thisse, 2002) Increasing returns allow local firms to exploit economies of scale and local consumers are able to achieve highe r levels of satisfaction than is the case with other less diversified areas. Ho telling (1929) stated that impe rfectly competitive, strategic behavior results in the co-loca tion of competing agents. This sp atial competition leads to the agglomeration of firms (Fujita and Thisse 2002). Krugman (1991) ar gues that an uneven distribution of industrial activities across space is a natural result of market processes under conditions of agglomeration economie s (McCann and Scheffer, 2004). Harris (1954) and others believed that the unequal distribution of industrial activities were due to a firms tendency to choose locations of ma ximum market potential. Market potential is defined as an index of access to markets involv ing both the purchasing pow er of all the markets

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46 to which it might sell and the distance to those markets (Krugman, 1995, p.44). Harris (1954) also found a clear correlation be tween high market pot ential and concentrat ion in the industry marketing belt. He also pointed out that regions with high market potential, such as the U.S. manufacturing belt, would find their advantage reinforced as more firms move there. Agglomeration forces Two opposing forces are thought responsible for explaining the observed spatial relationship of economic activ ities. These two opposing forces are described as cohesive/centripetal forces that are re sponsible for clustering/agglomeration and dispersion/centrifugal forces that are responsib le for the diffusion of economic activity. Fujita and Thisse (2002) describe the observed spatial c onfiguration of economic act ivity as a result of a complicated balance of forces that push and pull consumers and firms. Agglomeration forces are of three major types. The first type is related to the size of an economic region (economies of scale). The seco nd type is related to proximity of business enterprises to specialized resources. The th ird type is based on fl ows of communication. Agglomeration economies can also be described as internal or localizatio n economies. Internal economies are achieved when a firm's average co sts decrease as the firm size increases. Localization economies are external to the firm when it locates near its suppliers or in proximity to other firms producing the same product. Th ese economies are internal to the industry but external to the firm. Location of economic activity Location and costs of economic activity are also affected by the density and differentiation of economic activity. When units are located clos e to one another, the cost of doing business decreases and this creates economie s of scale internally and extern ally. These cost savings are referred to as agglomeration cost savings that come from the clustering of economic activity.

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47 Each firm finds a location good beca use of the presence of others (Maki and Lichty, 2000). This is a positive mutual attraction ( centripetal force) rather than repulsion (centrifugal force). The explanation of such mutual attracti on clusters lies in specific characteristics of the activity itself, its market or its suppliers. An as, et al. (1998) suggested that economic concentration is limited by dispersion forces, ranging from land lim itations to the cost of communication or transportation, to local conges tion or pollution, to the un-pric ed positive externalities of proximity. Large cities and industrial clusters have b een a longstanding feature of our economic system (McCann and Sheffer, 2004). Businesses of competing enterprises cluster to gain access sharing part of a total customer base. This tota l customer base is larger than the aggregate of customers when the same business are dispersed a nd isolated from one another. An example of this type of activity center is a local shopping center that includes businesses such as supermarkets, banks, gas stations, movie rental shops, restaurants, florists, etc. Other dissimilar businesses cluster together due to their interdependencies for proximity-sensitive production input or output markets such as printing and publ ishing businesses or a li me rock and concrete business. Anas et al. (1998) suggested that comp etitive small agents locate in close proximity to each other to exploit pecuniary or non-pecuniary external economies to reduce the average cost of a local public good; exchange inputs, products or information; or increase the opportunity for good matches. As land use theory developed, incorporating urba n and rural land use aspe cts, the theory of industry location became increasingly important. While industrial locatio n decisions are supply and demand driven, labor costs, availability and site and transfer costs have become important determinants in industry locations Businesses that form clusters of interdependent industries

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48 depend on large, diverse and activ e local labor markets and effici ent transportati on to and from these activity clusters to function efficiently McCann and Shefer (2004) stated that the work of Krugman (1991) and Poter (1990), promoting the importance of industrial clusters in generating competitive advantage for firms and regions provide lessons that geography really does matter in determining economic growth and performance. Yet the actual ways in wh ich geography determines economic growth and development are highly complex. Marshall (1920) had three explanations for the existence of positive agglomeration externalities, which focu s on the roles played by information spillovers, non-traded local inputs, and sk illed local labor pools. Labor costs are important for both existing and new businesses. Rural areas generally have lower labor costs than urban areas. In addi tion to lower labor costs, rural areas generally have lower site costs as well (land and environmen tal). These lower labor and site costs provide incentives for industry expansion in rural areas. These incentives are more attractive in the exurban/transitional areas than those between majo r metropolitan areas in the distant rural areas, where growth may be greater than in the metropo litan areas. The low labor and site costs in these ex-urban/transitional areas have become an important location attraction for startup businesses entering a new market with a new product. This is contrary to the experience of longestablished metropolitan areas currently losing much of the formal industrial base to these exurban rural areas. Some of the other site cost s of importance in dete rmining industry location include government imposed land regulations such as impact fees, infrastructure and facilities; pollution abatement; industry regulation; envi ronmental protection and energy costs. The role of infrastructure in regional developm ent must also be examined in the context of governmental decision-making. Marshall (1929 ) stated that the pr ovision of regional

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49 infrastructure can act as a catalyst for the gene ration of local agglomeration economies, because infrastructure can be regarded as a local non-tr aded input (McCann and Scheffer, 2004). Glaeser (1998) argues that the transportatio n costs involved in ensuring that people have both widespread and frequent face-to-face contact across a range of individuals is necessa ry to facilitate the transfer of tacit information. Th is transfer of information is th e crucial driving force behind the generation of modern cities and industrial clusters. Transportation costs and transfer costs are also of great importance in industry location. These transfer costs include input and output cost s. They include shipping costs for inputs and outputs from trucking, warehousing, air transportation and satel lite communications. In areas where population and traffic congestion are issues transportation costs can be lower and more attractive in rural areas. Transportation costs coul d be prohibitively high in rural areas due to the need of locating in proximity to other industrie s due to interdependencie s. Agglomeration of economic activity happens, given transportation co sts are minimized below a critical threshold (Fujita and Thisse, 2002). Technological cha nges are largely responsible for reducing many aspects of spatial transactions cost, thereby potentially bene fiting peripheral economies (McCann and Shefer, 1994). Road congestion bears ma ny hidden costs to both the employee in communing costs and to the employer in ground tr ansportation costs. The overcoming of increased modern spatial information transaction costs is now regarded in many circles as being the primary rationale underlying the existence of modern cities (McCann and Shefer, 1994)

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50 CHAPTER 3 CASE STUDY METHODS AND DATA This chapter will describe the data and met hods used to explain the manner in which the study area developed, why these patterns of development might have occurred, how these patterns of development relate land use a nd development to economic theory and how development decisions were made for the area. This will be accomplished by using a case study research method to analyze, explain and de scribe contemporary, co mplex, social phenomenon and characteristics of the real life events in la nd use and development of the Jonesville-Alachua County Road (CR) 241 corridor in Alachua County, Florida between 2000 and 2006. Due to the contemporary nature of the devel opment patterns of the study area, the data cannot be manipulated and the boundaries betwee n what we observe and what actually happened are not clearly evident. Because there are so many factors that contributed to the development pattern, the study must rely on multiple data s ources. These data sources are from direct observations, primary/secondary documents and physic al artifacts. The hi story of the actual development in the study area is the source of direct obser vation and from Alachua County Department of Growth Management policies, its Office of Planning and Development and other legislative documents. These data are used to expand and generalize three land use theories: location, central place and agglomeration. Thes e theories are then used to describe the theoretical patterns to compare and contrast these with the actual observed patterns to theorize/generalize the reasons for contra dictory patterns of development. Case Study Design A single case study design is used for this rese arch to study the patterns of development (residential, agricultural and commercial) of the Alachua-Jon esville Florida CR 241 corridor between 2000 and 2006. Three subsets of land use th eories will be used to compare and contrast

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51 how well each of these individual theories can explain the devel opment pattern. Each subset has a specific set of ideas, as well as circumstances, within which the implications are believed to be true. In this case, economic theory will be used to confirm, challenge or imply further studies and/or additional explanations of the development patterns. It is suspec ted that no subset alone will totally confirm or challenge theory but some aspects of each theory will be relevant. The strategy for the case is to combine the theori es and use them as a whole to explain the development pattern of the study area. Within the 2000-2006 time periods, the study area has had a sharp increase in growth both residential and commercial. In 1989, the Jonesvil le community consisted of a small handful of service-oriented firms and a community churches. This population growth is thought to be a spillover from the growing City of Gainesville. Growth in Gainesville has moved in a western fashion towards the JonesvilleAlachua area. This growth has been facilitated through connecting infrastructures and access to services such as employment, shopping, medical, airport, etc. from the City of Gainesville. Th e designation of the Jonesv ille area as an activity center has also contributed to this growth. Th is designation has impelled developers to pursue the advantage and perks provi ded through this designation. On the other end of the study area is the City of Alachua. Alachua has been growing in population as well as industry. It has a county designated rura l employment center and has become the home of many corporations (some national), technology incuba tors, local businesses and start-up companies. Much of this growth has been attributed to its location close to Interstate 75 and U.S. Highway 441, both of which connect it to the City of Gainesville as well as many other major cities. County Road 241 connects Alachua to Jonesville, creating a triangular pattern between the three areas.

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52 Population growth pressure has increased in the area as well as the use of exurban/transitional land for resident ial and commercial purposes. This increase in land-usage has also increased the demand for land extending the rural boundary which consequentially increases land values, housing prices and tax bills/revenue Although the land convers ions and settlement patterns differ between these three areas, CR 241 and Newberry Road connect these two areas, and thus creating interdependencie s as well as centripetal and centr ifugal forces of development. The resulting development patterns that tran spire through the dynamics of each area and the county growth management plan ar e neither directly predictable nor easily rationalized. This lack of information has become an increasing governmental concern and the need for effective policy and predictable outcomes has emerged. Ther efore there is an increas ing need for effective policy recommendations to manage land use at the local level and to mitigate potential negative social, economical, political a nd environmental impacts. This economic study of land use development patterns can help in understanding the choices and impacts of development and the effects of current and proposed development policies. Therefore there is a need to determine the effectiveness of economic theory to explain deve lopment patterns and to provide effective policy recommendations Data and Methods Data used for the case study were obtained from three main sources: the Alachua County Property Appraisers office, th e Alachua County Department of Growth Management and the U.S. Census Bureau. The following will describe what data was used for each analysis, how the data was obtained and how it was used for the analysis. In order to conduct the analys is on location theory geographi cal data was needed. This data was obtained from two sources: the Alachua County Department of Growth Management Geographical Information Systems (GIS) a nd Mapping Division and the Alachua County

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53 Property Appraisers Office. The countys proper ty parcel data was obtained from the GIS and Mapping Division. The study roads were determined using the detailed roads file (see Chapter 4 Classical Location Theory for details) and ArcGIS software was used to form a one mile buffer from each side of the road study area. A sel ection was made using only those parcels whose centroid fell within the buffered area. This sel ection created the study area parcels that were used for the analysis. The acreage of each pa rcel was then calculated using ArcGIS. The Alachua County Property Appraisers market valu e tax data was obtained and joined with the attribute data tables for the selected study area pa rcels. The parcel market value data was used with the parcel acreage data to calculate the land values per acre. The 2000 GDP deflator was then used to deflate the land values pe r acre into consta nt 2000 dollars. Once this data was obtained, the study area parc els were converted into point files. The data was categorized by land use types: agricultural, residential and commercial/industrial. Only parcel points for these three land uses were used in the analysis. These points were inputted into the ArcGIS spatial analysis tool interpolat ion using the inverted distance weight (IDW) technique. The per acre land valu es were used in the z-value fiel d in a raster analysis setting using a cell size of 100 and the one mile buffer as a mask to cr eate the land value surfaces. These values were then separated into classifi cations by value and color (see Figures 4-2 to 422). Central place analysis data we re obtained from an Alachua county map created using the GIS and Mapping Division data (obt ained from their GIS server (www.nikos.alachua.fl.us ). The County boundary, major road, detailed roads and muni cipality shape file were used to construct the map. The municipality shape file was converted to points to obtain the central location of the city/municipality. Straight line distances were calculated using a straight-line distance calculator

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54 (http://www.findlocal weather.com/how_far_is_it/dc/washington.html ) to determine the distances between cities/municipal ities (see Figure 4-23). The agglomeration analysis data was obtaine d from the Alachua County Department of Growth Management Development Services Divi sion. The section, township, and range for the study area was determined and used to obtain th e study areas developmen tal and planning data. This data was obtained in spreadsheet form and was sorted according to ye ar and then plotted on the timeline of developmental activity (see Figure 4-24). Location Theory Location theory studies the effects of ge ography on economic activities. Space/geography affects economic relationships through market activities in adjacent locations (neighborhood effects) and in the movement of people and goods (Beckmann, 1968). Within this broad category described as location theory, there are three generalized subcat egories that will be discussed with reference to the land-use devel opment patterns of the case study area. These three subcategories will be referred to as clas sical location theory, cen tral place theory and agglomeration economics. Although each of these subcategories have somewhat different ideas and perspectives, they are all relevant in explaini ng the development patterns of this case study. Classical Location Theory To apply the classical location theories in this case study, the initial focus will be on the relationship between land use change and la nd rent over the study pe riod using von Thnens theory. The focus here is on the distance betw een the CBD (Gainesville) and the sub-centers (Newberry and Alachua) on CR 241 and Newberry Ro ad (State Road 26) with the Jonesville community as a central point. The study will obse rve the changes in land use (agricultural, residential and commercial/industrial) and land re nt (land value will be substituted for rent) as the distance increases from the CBD and sub-cen ters. GIS data from the Alachua County

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55 Growth Management GIS Department will be used to calculate changes in land values at the subcenters and the CBD. Land values were divided into value per acre cla ssifications using GIS data from the Alachua County Property Appraiser. According to this theory, land rent/value will decrease as the distance from the CBD increases Land use will change in intensity from high intensive uses (firms and other larger devel opments) to low intensive uses (rural housing and subdivisions) with distance from CBD. Due to the interdependencies an d the influences of adjacent CBD and sub-centers (i.e ., neighborhoods have an affect) one can expect a blurring of the land values and a distorted non-theoretical ring pattern. The second classical location theory to be a pplied is Alonsos bid-rent function. This theory assumes that firms are indifferent to th eir location to the CBD along a bid-rent function and subject to fixed transportation budgets and costs. This theory will be used to analyze location behavior by determining how and if la nd values affect location and the average land values in the study area were de termined over time. Hi storical land development data were used to determine the location and type of developmen t and to determine the pattern of development and land uses associated with land values. Histor ical GIS parcel data were collected from the Alachua County Department of Growth Manageme nt to conduct this study. The Alachua County Department of Growth Management Office of Planning & Developmen t provided historical development data from 1997 to 2007 and tax data were obtained from the Alachua County Property Appraisers Office for land values. Central Place Theory The study area was evaluated to determine if hi erarchies exist within the study area and if so, are the hierarchies consistent with the hier archies of central plac es in theory? Are the distances between central places equidistance forming equilateral tria ngles? The state of Floridas requirements for incorporated places do es not distinguish between cities, villages and

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56 towns. The requirements for a town or village ar e the same as for a city. The city designation requires at least 1,500 residents in counties with greater than 50,000 residents and 5,000 residents for other counties. The 2000 U.S. Ce nsus Bureau population estimate for Alachua County was 217,995. Since there is no official distinguishing characteristics between cities/central places, a central place population hierarchy in th ree ordered increments will be designated: population less than 1000, 1000 to 10,000 and population greater than 10,000. This can be generalized because the market area/size dete rmines the central place, not the city size. Central place theory is used in this study to he lp identify the factors that most influence the development pattern. This is done by analyzi ng the hierarchy of centr al places and spatial structures. Agglomeration Theory The focus of agglomeration economics is to attempt to explain the main causes of agglomeration in the study area. The analysis will focus on the agglomeration effects of increasing returns to scale/cost savings, externa lities and imperfectly competitive markets. The use of agglomeration of central places in this case study is used to determine the factors that most influence the development patterns. The policy and the private sector impacts on development patterns will also be analyzed. Th e results of this study ca n assist in developing and modifying policies to obtain desired growth and development. Assuming that firms behave in a competitive manner, central places will optimize market area through clustering of activities. To test or illustrate this in the study area, a timeline of development activity will be used to observe area growth, cluste ring activities and the interaction of firms over time. An analysis of policy im pacts (growth management) and private sector activities (developers activities) on the development patterns will also conducted. The data used for this portion of the analysis were obtained fr om the Alachua County (Florida) Department of

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57 Growth Management Office of Planning and Deve lopment. This data included development plans reviewed or approved by the Alachua C ounty Development Review Committee within the study area from 1997 to 2007. In this study area, the cities of Alachua, Gainesville and Newberry have already been established. An interesting aspect of Jonesville is that it is not a city or municipality; it is a neighborhood of the city of Newberry. It has no local government but functions somewhat as if it is one or may become one. Economists, geogr aphers and historians consider increasing return due to economies of scale the most crucia l factor in explaining economic agglomerations and the emergence of cities. The question is: Will Jonesville turn into an independent city/municipality due to the agglomeration forces or will be annexed into the City of Gainesville or Newberry?

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58 CHAPTER 4 RESULTS This chapter presents the results of the locati on theory analyses appl ied to the study area. Three location theory methods were used: classi cal location theory, centr al place theory and agglomeration economics. Each will be disc ussed in detail in th e following sections. Classical Location Theory GIS analysis was applied to demonstrate von Thnens classical location theory of concentric rings. GIS parcel data from the years 2000-2006 we re obtained from the Alachua County Growth Management Office and 2000-20 06 GIS tax data from the Alachua County Property Appraisers office. These data were combined to form one data set. The data set was divided into three land use categ ories: agricultu ral, commercial and industrial and residential. Parcel market value and acreage for each parcel we re used to calculate the land value per acre. All values were normalized using the 2000 Gross Domestic Product deflator. The study area for this analysis is a one-mile buffer from the north and south sides of Newberry Road (State Road 26) and east and we st of County Road 241. These roads cover the area on Newberry Road from the City of Newberry to SW 34th Street in Gainesville and on CR 241 from the City of Alachua to the Jonesvil le Community on Newberry Road (Figure 4-1). The study area buffer was used to select the pa rcel shape files that have their centroids within the study area. The study area parcel shape files were then converted to point files to be used in the spatial analysis. Shape files are defined by Environmental Systems Research Institute, Inc. (ESRI) as a vector data storage fo rmat for storing the location, shape and attributes of geographic features. A shapefile is stored in a set of relate d files and contains one feature class. Interpolation spatial analysis of the land values per acre were used to estimate the surface values at unsampled points based on known surface va lues of surrounding points. In this case an

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59 inverse distance weighted (IDW) interpolation was used to estimate cell values in a raster form of a set of sample points that have been weighted so that the farther a sample point is from the cell being evaluated, the less weight it has in the calculation of the cells value. The term raster is defined by ESRI as a spatial data model that defines space as an array of equally sized cells arranged in rows and columns, and composed of single or multiple bands. Each cell contains an attribute value and location coordinates. Unlike a vector structure, wh ich stores coordinates explicitly, raster coordinates are contained in the ordering of the matrix. Groups of cells that share the same value represent the same type of geographic feature. The statistics for each land use and year are provided in Tables 4-1 to 4-5. Reviewing tables 4-1 to 4-5 from 2000 to 2006 shows that th ere was an increase in the number of commercial/industrial an d residential land parcels in the study area and a decrease in the number agricultural parcels. In 2000 there were 569 commercial/industrial firms and 769 in 2006. Two hundred commercial/industrial firms (176 commercial) were established in the study are during this seven year period. During that ti me the number of reside ntial parcels increased by 1631 and the agricultural land pa rcels decreased by fourteen. The standard deviations for the three land valu e classifications (value per acre) had values larger than their mean. The large commercial/indus trial standard deviations may possibly be due to relative high market land values for profe ssional/office buildings located on relatively small parcels. Similarly residential standard deviati ons my be due in part to high market value residents such as single fam ily homes or condos on relatively small parcels of land. The agricultural land value devi ations may be due to homes with relatively high market value located on relatively small parcels designated for agri cultural uses. The Alachua County Property Appraiser designates acreage devo ted to a home site as cartilage acreage. This acreage cannot

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60 receive the agricultural classificat ion for tax purposes and is assesse d at market value therefore; the home and the cartilage are assessed sepa rately (Florida State Statute 193.461). General Land Values The study area land value maps fo r the three types (commercial /industrial, residential and agricultural) demonstrate the land values per acre. These values per acre were divided into 11 or 12 classifications (see map legends). IDW analys is was conducted on the parcel land values for each year from 2000 to 2006. Each classificatio n is a different color and represents a range/classification of land values per acre. Von Thnens theory states that land values will decrease as the distance from the CBD increases. In this case, one CBD, Gainesville, and two sub-centers, Alachua and Newberry, were identified. Viewing the land values per acre over the study period for each classification (Figures 4-2 to 4-22); there is a general tre nd of decreasing land value from the CBD, to each sub-center. This trend is described as general because each subcenter had decreasing land value trends as the distance increases from their resp ective sub-centers. Agricultural land values do not consistently display the decreasing trend fr om each sub-center or CBD. Neither land value classification trend displayed perfect concentric ri ngs, but they do show that land values decrease with distance from the CBD and sub-centers. Although imperfect, these trends are consistent with von Thnens (1862) theory of concentric rings and also conform to the contemporary modifications of Alonsos (1964) la nd rent theory. Agricultural trends as well as land use are further discussed in the following sections. Within the study time frame, one is able to s ee a trend in the intensity of land uses. The City of Gainesville is the county seat and the CBD of Alachua County. It is also the location of The University of Florida, the states largest university, and is classified as a metropolitan statistical area (MSA) by the U.S. Bureau of Stat istics. The City of Ne wberry and Alachua are

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61 small rural municipalities with populations of 3,316 and 6,098 respectively (2000 Census). The city of Alachua has recently experien ced a tremendous growth in industry. Commercial and Industrial Land Values Viewing the commercial/industrial land value maps from 2000 to 2006 (Figures 4-2 to 48), the highest land values are in the Gainesvi lle area, followed by Alachua and Newberry. The trend over the study period shows increasing land va lues. Each year shows progressive increases in the land values as the map co lors for the lower land values progressively change from the dominant pink and purple ($40,000-60,000) in Alac hua and Newberry to blue and turquoise ($60,000-350,000). The Gainesville area (CBD) land valu es, initially the highe st in value, have progressively increased in value from ye llow ($1-5 million) and green ($350,000-1,000,000) to predominantly yellow. The maps also show a dr astic increase in land values in the Jonesville area increasing from turquoise (100,0 00-350,000) to yellow ($1,000,000 to $5,000,000). The commercial and industrial la nd values along Interstate 75 are high as expected due to the access that the interstate provides. The values within the core of th e cities of Alachua and Newberry are high, due to the local goods and services they provide. Residential Land Values Looking at the overall change in residential land values over the study period (Figures 4-9 to 4-15); one finds distinctive changes in la nd values in 2004 and 2006. In 2004, there is a general increase in land values at each city and in the Jonesvil le area over time. In 2006, there was a significant increase in the land values in each city and most significantly in Jonesville. Note that the changes in land values in the Jone sville area have the greatest change in values. The map indicates color changes from pre dominately red ($2,800,000) with some orange ($50,000-100,000) to a substantia l increase in the yellow to blue ranges ($200,000-13,000,000).

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62 Agricultural Land Value The change in the agricultural land values displayed moderately increasing land value trends and also some volatility of these land values (Figures 4-16 to 4-22). One area in particular surrounds the City of Alachua. Over the study period, an undulation of the agricultural land values was observed. This undulation may be attributed to a lag in the change in land classification between land sales fr om agricultural uses to reside ntial, commercial or industrial uses. The City of Alachua has a designated ru ral employment center and has had a significant influx in industrial settlements. The high peaks in the agricultu ral land values are probably du e to high value agricultural land such as timberland and Class I grazing lands. As expected ag ricultural land values decrease significantly in the Gainesville area. The citi es of Newberry and Alachua display a weak concentration of high land values within their cen tral places which were greatly weakened by the volatility of the land value based on changes in la nd use. Land values within in the JonesvilleAlachua CR 241 corridor and the Gainesville and Ne wberry corridor, with the exception of the Jonesville community, were generally higher du e to the more rural location and the distance from the main roads/highways. Note the incr easing agricultural land values that surround the Jonesville activity center, located at the intersect ion of Newberry Road and CR 241, on all sides. As discussed previously, there has been a s ubstantial increase in co mmercial/industrial and residential land values in the Jonesville area. The concentration of high land values surrounding the Jonesville intersectio n may be due in part to inflated ag ricultural land values in anticipation of urban land uses associated with the Jonesvi lle activity center. These differences in land use and land values have fashioned a boundary that separates urban and rural land uses. The interplay between the urban/ rural spatial boundaries may be thought necessary for the

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63 agglomeration of economic activity (Walker and So lecki, 2004). The urban-rural push and pull factors at this boundary contribute to and shape the development of agglomeration Summary of Location Theory Results Overall, the results obtained from the classica l location theory analysis demonstrate that the land values for the commercial/industrial and residential land uses d ecreased with distance from the CBD and the sub-centers as demonstrated in Figures 4-25 and 4-26. However, this is not the case for agricultural la nd values. There appears to be a general trend of higher land values in the Alachua sub-centers than in th e Newberry sub-center and the Gainesville CBD. The Jonesvilles inconsistency with von Thnens theory may be due in part to its designation as an activity center. This designa tion may have biased the agricultu ral land values in anticipation of potential profits from urban us es. These results can be attri buted to the urbanization of the sub-centers, thus higher land values occur between the urban areas as demonstrated by the maps. Gainesville, being the CBD, does not have any rele vant agricultural land because it is an urban area unlike the urbanizing areas of Newberry, Alachua and Jonesville. The population growth in these ar eas contributes to the results of the three land uses. As the population within the CBD and sub-cen ters increases, the residential and commercial/industrial land values will also increa se at these centers to accommodate population growth and to take advantage of surplus economic rents. These increased land values will affect the agricultural land values because agricultural land is bid away from extensive uses, such as agriculture, to intensive urban uses. Central Place Theory Central place theory can be used to analyze urban spatial structures and policy impacts as well as dispersion of economic act ivity. Here the aim is to unde rstand where and why cities are established and look at the intera ctions of central places. Cent ral place theory attempts to

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64 explain how these interactions lead to clustering and hierarchies of cities. The objective of this theory is for firms to obtain an optimal market ar ea. This market is determined by its threshold and range (see Figures 4-27 and 4-28). The ma rket area and distance form the central place determines its threshold and thus the hierarchy an d order of the city/centr al place (see Figures 429 and 4-30). Theory suggests that neighboring ce ntral places offering the same order of goods and services will be located equidistance from ea ch other forming an equilateral triangle or hexagonal pattern where the centers are at the corners (see Figure 4-31). In this case study the cities a nd municipalities of Alachua County are divided into three orders by population: A, B and C. Ce ntral places with populati ons over 10,000 are of the highest order, order A; followed by or der B (population 1 ,000-9,999) and order C (population less than 1,000). Hi gher order markets are fewer in number and more widely distributed and cover a larger market area su ch as shopping malls, superstores, universities, central markets/commerce, etc (see Figure 4-30). Alachua County Central Place Results The straight line distances be tween cities/municipalities (r ounded to the nearest whole number) were plotted on an Alachua County map and the order of each ce ntral place was labeled (Figure 4-23; Table 4-7). The City of Ga inesville is order,A. The order B cities/municipalities are Alachua, High Springs, Newberry, Hawthorne and Archer. The order C cities/municipalities are Waldo, Micanopy and La Crosse. At first glance, the order B city distances ar e all very similar, with the exception of the distance from Archer to Alachua. Hawthorne is the only order B city on the eastside of the county. Therefore it doesnt have any direct linkages to other B order cities in Alachua but may connect to others cities/tow ns in the adjacent counties.

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65 The class C cities do not have any real dire ct linkages between them. Two are located in the northern portion of the county and one is located in the sout hern portion. If you look at the class B and C points on the eastern porti on of the county, you will find that Micanopy, Hawthorne and Waldo are approxim ately equidistance form one anot her. This may or may not be a coincidence. Hawthorne as well as Mican opy and Waldo may be a part of an adjoining county system of central places or may offer the same order of goods regardless of population size. In addition, the growth and development in the county during this study period has been concentrated in the west and nor thwest portion of the county. Note the distances between the cities joining Gainesville, Newberry and Alachua. When the straight line distances between each city is calculated the le ngths of the formed triangle have similar distances (9, 10, and 11 miles: see Figure 4-23). What does it mean? Given the theory that central places offering the same order of goods and services will be located equidistance from each other in a triangular fashion suggests th at Jonesville is in a perfect location to be converted into another cent ral place of order B. Summary of Central Place Theory Analysis Overall, looking at the plotted distances betw een the cities by order doe s not give the neat hexagonal structure suggested by Lsch (1940) (see Figure 4-31). Although Figure 4-23 does not truly demonstrate the hexa gonal structure of central place s in Alachua County, it does illustrate the equilateral triangles for the order B central places. In order to obtain a true view of the central place structure, one would have to plot the structures of the surrounding counties to obtain a truer view of the cen tral place structure. Agglomeration Theory This section will discuss the theoretical expl anations of the development activity as it relates to agglomeration economics and activity. The focus will be on the interplay between

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66 spatial boundaries; increasing returns to scale/cost savings and the existence of positive profits, externalities and imperfectly competitive market s associated with agglomeration economics and activities. A timeline of development activity was created and employed to analyze and discuss the development pattern of the st udy area as it relates to agglomer ation theory (Figure 4-24). In conclusion, there is a discussion of these developmen t activities as they rela te to the Jonesville community during this study period and in the future. Timeline of Development Activity Although the time period of this study be gins in the year 2000, the timeline of development activity begins in the year 1997 (Fi gure 4-24). The year 1997 is relevant because these activities were catalyst s for the following ac tivities. In the 1991-2011 Alachua County Comprehensive Plan, Jonesville (l ocated within the urban services area) was designated as a low activity/employment center. The initial phase of construc ting the Jonesville Crossing s hopping center began in 1997. The shopping center was developed to accommodat e 21,000 square feet of commercial space. The shopping centers commercial space was designed to accommodate retail stores, office space and restaurants. Storage and warehouse faciliti es were also built during the same year. These facilities may have been pre-planned to accomm odate construction and development activity in the area. After the initi al infrastructure was established, a bank, gas statio n/convenience store and a small business center were built to attract consumers. These types of firms form the basis of a neighborhood center that can capture and concentrate the surr ounding population needs, customer base and market area (see Figure 4-26). The market areas of the individual firms have been combined to create a larger market area a nd customer base that is shared equally by each firm. This shared customer base is the area created by the range of the market area and its customer base. The range is dependent on the maximum distance that consumers are willing to

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67 travel to get to the neighborhood center. Thus the development of firms sharing a customer base creates the market area of the neighborhood center. Realiz ing the competitive advantage of concentrating spatial economic activity, firms cluste r together to create a larger market area and customer base. This clustering positive exte rnality by increasing firms market area. Firms benefit from the increased market area which enables firms to realize positive profits. Jonesville is located approximately half wa y between Gainesville and Newberry and is approximately 10 miles from Alachua (see Figu re 4-23). The area su rrounding the Jonesville neighborhood center has captured the market area s between these central places, creating an extended built-up area of surrounding central places. This descripti on of the Jonesville area and the neighborhood center suggests th at it is an agglomeration a nd can possibly, not necessarily, become a central place. As development activ ities continue, the Jone sville neighborhood center may evolve into a higher order central place. Between 2002 and 2004, the major developments were commercial retail shops and services. These commercial activities have further devel oped the neighborhood center from basic commercial firms to more diversified firms. Some of these additional services include a drugstore, auto center (Tuffy), hardware st ore (Tractor Supply), recreational facility (gymnastics), Dollar General (basic house wares), et c. There was an explosion of offices, retail shops, restaurants, warehouses and office space th at further increased the concentration of economic activities. This expansion was acco mmodated through infrastructure improvements such as existing road improvements and the additi on of a communications tower. In the midst of the increasing commercial activity, residential development also increased to take advantage of the nearby neighborhood centers commercial ac tivity. During this time period, 722 single

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68 family homes and 60 apartment units were establis hed. This is a significantly large number of residents in this relatively small area. During the 2005 to 2007 period residential development continued to grow and 347 additional single family homes were constructed. Commercial developmen t also continued with the construction of a grocery stor e (Publix), the addition of two ba nks (one as the headquarters), a funeral home and recreational facilities. These additions have created a more self-sustaining commercial area. Area residents no longer have the need to travel to town/central places for basic necessities such as food and recreation. To further popula tion sustainment, additions and improvements were made in the areas infrastruc ture such as a sewer expansion and a new fire station. These services indicate that the area is expecting add itional growth. Future plans and proposals have been made to further increase de velopment in the area by adding a county park (Jonesville Park), additional gas stations/r estaurant/convenience stores, a power station, communications tower and storm water drainage. Increased commercial growth during this period helped to accommodate residential growth. Continued commercial and residential growth functions as centripetal forces that will multip ly the agglomeration of Jonesvilles economic activity. Regulation and Agglomeration Reviewing the timeline of development may make one wonder why development occurred in this area and not in other parts of the count y. One reason is that th e Department of Growth Management designated Jonesville as a low density activity/employment center. This activity center was designed to promote the area around th e intersection of Newberry Road and CR 241 as a low-intensity, employment-oriented mixe d-use center (i.e., commercial, open space, office/business parks, institutional and residential). The center is located within the urban cluster to provide for the concentration of mixtures of higher intensity and density land uses in the urban

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69 area. Residential development may be clustered because of the countys zoning regulations, with activity centers requiring central water and sewer. This development required a minimum population of 10,000 people per 80,000 square fe et of commercial space for neighborhood shopping centers and 35,000 people for a singl e 150,000 square-foot co mmercial community shopping center. These required guidelines were de veloped to prevent premature development. The urban activity centers polic ies address factors influencin g the timing of development such as market penetration within surrounding ma rkets; travel time, population; the number of households; median annual income; employment rates; economic development needs and jobhousing balances (see 2001-2020 Alachua Count y Comprehensive Plan, 2.0 Urban Activity Center Policies). These fact ors were studied and documente d through market and employment studies to determine the location a nd/or expansion of activity centers. Activity center policies require, whenever pos sible, that centers be confined to intersections of multi-modal corridors, and appropriate sizing to allow the development of associated activities while minimizing encroach ment on existing and future neighborhoods. The primary and secondary uses of the centers are determined based on the needs of the community, character of the surrounding area and market cons iderations identified in market studies. The design standards and policies of the activity cen ter are to create compact, multi-purpose, mixeduse centers that integrate commercial development with residential development that is pedestrian-friendly development. Commercial faci lities shall be phased with the residential component of the development to allow co mmunity green space and surface storm water management. The county evaluates and updates the Activity center Plan s to determine and maintain compliance.

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70 Considering the growth management policy above, the developm ent pattern of the Jonesville community appears to coincide with the development policies. Has this development occurred because of policy or has policy develo ped to accommodate the Jonesville development? What, if any, are the push-pull fact ors/centripetal-centrif ugal forces that influenced development in this area? Agglomeration Forces A discussion of the urban push factors and ru ral/suburban pull factors associated with the agglomeration of firms in the Jonesville study ar ea will be discussed to determine impacts on the development pattern. This discussion will addre ss the development of the Jonesville community and its interdependency with the tri-city area of Gainesville, Newberry and Alachua. The tugof-war of attracting and repe lling forces resulting in ec onomic interactions among the surrounding areas and their interdepende ncies will also be discussed. Many studies have suggested that demographics play an important role in land use change and that population demographics in urban areas have a sign ificant impact on rural land conversion. Walker and Solecki (2004) stated th at land cover and land use change results from economic and demographic interac tions between cities and hinter land, as well as from specific agricultural and urban processes. Agglomeration is said to emerge through the in terplay between spatial boundaries, trip dispersion and the existe nce of positive profits. Thus, population growth plays an important role in the agglomeration of economic activities because it modifies the spatial boundaries between urban and rural area s (review The Population Growth section of Classical Location Theory). Constant increases in populati on growth over this seven-year period have greatly fueled the agglomeration push and pull factors on the surroundi ng land uses in the study area. The cities of Newberry and Alachua, once rural, are seeing an influx in population possi bly due to a spillover

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71 of the City of Gainesville. The resulting ur ban growth has pushed the urban/rural boundary outwards in a west/northwest direction towards Alachua, Newberry and the Jonesville. Another major push factor is the limitation of availabl e urban land and the relatively lower rural land values in the rural areas of Newberry and Al achua. Higher land values within the City of Gainesville have pushed growth outside of th e city limits to accommodate further economic development (see Figure 4-1). Although the outlying land values are relative ly low, agricultural values have been increasing while the profita bility of agricultural enterprises has been decreasing. Another result of the Gainesvi lle population growth is the increase in population density, congestion and land values. Population growth in Gainesville has pushed some residents into rural/suburban areas. Lower land values and labor costs have also pulled some economic development from Gainesville in to the surrounding rura l/suburban area. Fujita in his new economic geography believes that this dyna mic process in which population gradually increases, lending to moving agricultural frontiers and the occasional formation of new cities, can generate an emergent hierarchy of central places (Krugman, 1996). Applying this statement to this study the Jonesville community could pos sibly become one of these occasional cities and part of the hierarchy of central pl aces within the study area/county. Transportation cost is an impor tant factor in the agglomerat ion of economic activities. As population growth increases, the distances betwee n urban and rural also increase. Increased distance increases the transporta tion costs of moving goods and se rvices and consumer travel costs. These costs are impacted by public i nvestment in transpor tation technologies and improved access to outlying areas. Because distance has a negative effect on transportation costs, the increase in transportation costs is thou ght to lead to the agglomeration of firms.

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72 Agglomeration of economic activity is limited by transportation costs and proximity of other firms. Firms realize cost savi ngs through clustering of economic activity (agglomeration cost savings) and the amount of cost savings has an impact on the density and differentiation of economic activity. Given these factors, infrastructu re can act as a catalyst for the formation of local agglomeration economies where consumer s benefit through reduced travel costs and increased product diversity. When transportation costs reach a critical po int, firms will relocate. Lower rural land values, density and congestion attract economic activity through cost savings. These cost savings attract other firms and these firms cluster t ogether to realize agglom eration cost savings. The agglomeration and differentia tion of firms creates a spatial competitive advantage for firms in the local area. The concept of Marshallian externalities has been used to describe these cumulative/multiplier effects of agglomeration wher e firms cluster to ulti mately realize positive profits through increasing return s and monopolistic competition. Focusing on the study area and know ing the important role of infrastructure, one of the most important features of the Jonesville commun ity was the expansion of Newberry Road (State Road 26) from a two-lane to a four-lane road. This improved access to the outlying areas and literally paved the way to the Jonesville agglomer ation of economic development. Prior to the construction of the Jonesville Activity center, there was no substantial economic activity in Newberry and Alachua. The push and pull factors; their interactions and cumulative/multiplying effects; and the tug-of-wa r between Alachua, Newberry, and the Jonesville neighborhood center have contributed to their development as central places. Geogra phically, the Jonesville neighborhood center is located between the cities of Newberry, Alachua and Gainesville (see Figure 4-23) and was the first area to experien ce the effects of tug-of -war and subsequent

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73 development. The natural features of Jonesville and its location have plac ed it in an opportune position for the agglomeration of economic activity. Agglomeration of economic activity is thought to occur through the inte ractions of spatial boundaries, trip dispersion and the existence of positive profits. The Jonesville location encompasses all these concepts of agglomeration. Due to its loca tion, it is in the center of the spatial boundary interactions of Gainesville, Newberry and Alachua. This central location minimizes trip dispersion and the relatively lo w land values and lack of competitive economic activity create the possibility of economic profits. One can clearly see the agglomeration of econom ic activity from reviewing the timeline of development activity, county policy and regulati on of economic activity and the agglomeration forces in the study area. Given the above obser vations and the many type s and definitions of agglomeration, Papageorgiou and Thisse (1985) corre ctly described it as being one of the most difficult phenomena in spatial analysis. The agglomeration of economic activity is evident but is in the middle of the tug-of-war and the centripet al/multiplicative forces or factors responsible for its initial commencement cannot be determined

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74 Table 4-1. Commercial and Industrial Land Value Data Commercial and Industrial Land Value Data Year Count Min Max Mean Std. Dev Sum 2000 569.00 4,443.28 12,720,000.00 1,147,390.87 1,584,723.86 652,865,407.30 2001 603.00 4,328.91 12,802,831.52 1,296,375.03 1,792,976.17 781,714,140.11 2002 566.00 5,889.08 12,611,689.79 1,184,768.72 1,718,962.74 670,579,095.50 2003 686.00 6,515.79 2,349,020.14 1,256,617.38 1,723,495.30 862,039,520.70 2004 735.00 11,334.72 41,451,593.35 1,417,453.73 2,420,670.13 1,041,828,491.56 2005 751.00 11,114.71 40,387,294.70 1,442,218.16 2,359,087.21 1,083,105,840.44 2006 769.00 14,832.66 21,266,716.29 1,544,633.32 1,996,353.76 1,181,823,020.49

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75 Table 4-2. Commercial Land Value Data

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76 Table 4-3. Industrial Land Value Data

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77 Table 4-4. Residential Land Value Data

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78 Table 4-5. Agricultural Land Value Data

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79 Table 4-6. Alachua County Straight Li nes Distances between Municipalities

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80 Figure 4-1. Alachua County, Florida Study Area Map

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81 Figure 4-2. 2000 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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82 Figure 4-3. 2001 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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83 Figure 4-4. 2002 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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84 Figure 4-5. 2003 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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85 Figure 4-6. 2004 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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86 Figure 4-7. 2005 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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87 Figure 4-8. 2006 Alachua County Fl orida Study Area Commercial and Industrial Land Values per Acre (2000 GDP Deflator)

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88 Figure 4-9. 2000 Alachua County Fl orida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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89 Figure 4-10. 2001 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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90 Figure 4-11. 2002 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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91 Figure 4-12. 2003 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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92 Figure 4-13. 2004 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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93 Figure 4-14. 2005 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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94 Figure 4-15. 2006 Alachua County Florida Study Area Residential Land Values per Acre (2000 GDP Deflator)

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95 Figure 4-16. 2000 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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96 Figure 4-17. 2001 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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97 Figure 4-18. 2002 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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98 Figure 4-19. 2003 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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99 Figure 4-20. 2004 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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100 Figure 4-21. 2005 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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101 Figure 4-22. 2006 Alachua County Florida Study Ar ea Agricultural Land Values per Acre (2000 GDP Deflator)

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102 Figure 4-23. Alachua County Florida Municipal ity Central Place Orders and Straight-Line Distances (miles are rounded up to the nearest whole number)

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103 Figure 4-24. Jonesville Study Area Ti meline of Development Activities

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104 Figure 4-24. Continued Figure 4-24. Continued

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105 Rent Curve 1 km5 km 10 km S = 3.14 S = 75.40 S = 235.62 1/S D 1/SS = D2Rent S = Surface area D = Distance = 3.14 CBD Figure 4-25 Land rent theo ry. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 6 Concepts, Slide # 44, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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106 Rent A Conventional CBD B Commercial / industry C High to medium density residential D Sub center E Suburbia A B C D E Rent Curve Figure 4-26 Contemporary modifications of the land rent theory. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 6 Concepts, Slide # 46, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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107 Figure 4-27 Market threshold a nd range. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 3, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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108 Threshold Range Threshold RangeAB R(A) R(B)p pSituation A: Demand > Costs Situation B: Demand < Costs Figure 4-28 Threshold range and market prof itability relationship. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 4, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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109 Figure 4-29 Market size and threshold. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 5, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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110 Figure 4-30 Conventional distance decay curves for retail activities. Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Methods, Slide # 12, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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111 A A B B B B B B B B B B ABCMarket area Order Figure 4-31 Central places theo ry (K=3). Rodrigue, J-P, et al. (2006), The Geography of Transport Systems Hofstra University, Department of Economics & Geography, Chapter 7 Concepts, Slide # 42, http://people.hofstra.edu/geotrans Date last accessed June 2007 [used with permission]

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112 CHAPTER 5 CONCLUSIONS Although the results of the classical locati on, central place and agglomeration theories have contributed to the explanation of the study area development pattern, they cannot fully explain why the development occurred in this partic ular area and not in other areas of the county. What motivated this development and what ar e the end results of this development. Reviewing the results of classical location theory suggests that population growth; urban encroachment and increasing land values have led to development of the study area. The results obtained from the classical location theory anal ysis demonstrated that the land values for commercial/industrial and residential land uses decreased with distance from the CBD and subcenters as demonstrated in Figure 4-25 and 426. This is not the case for agricultural land values. There appears to be a general trend of hi gher land values in the Alachua sub-centers than in Newberry and Gainesville. The Jonesville inconsistency with von Thnens theory may be due in part to its designation as an activity cen ter. This designation may have biased the agricultural land values in potential of anticipated profits of urban uses. These results can be attributed to the urbanization of the sub-centers thus the higher land va lues occur between the urban areas as demonstrated by the maps. Ga inesville, being the CBD, does not have any relevant agricultural land because it is an urba n area rather than an urbanizing area such as Newberry, Alachua, and Jonesville. The population growth in these ar eas contributes to the results of the three land uses. As the population within the CBD and sub-cen ters increases, the residential and commercial/industrial land values will also incr ease at these center s to accommodate the population growth and to take advantage of the surplus economic rents. These increased land

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113 values also affect agricultural land values in that agricultural land is bid away from extensive uses, such as agriculture, to intensive urban uses. Central place theory results suggest that the study area development was due to its geographical location, the surrounding central places /order and potential market areas. Noting the distances between the cities joining Gainesv ille, Newberry and Alachua, one will find that a triangle is formed between them and that each length has similar distances (9, 10 and, 11). Given the theory of central places Jonesville is in a perfect location to be come another central place of order Bif it incorporates, which is not guaranteed. Reasons cited for incorporation include dissatisfaction with service delivery by the county landuse and growth management concerns, more fiscal control, a since of re proportional representation or as a means to stav e off annexation(Legi slative Committee on Intergovernmental Relations, 2001). In order fo r the Jonesville community to become an incorporated municipality, the Florida Formation of Municipa lities Act (Ch 74-192) requires a feasibility study to ensure that the municipality has a viable community and a proposed charter that is prepared in bill form and submitted to the Legislature. Overall just looking at the plot ted distances between the cities by order does not give the neat hexagonal structure suggested by Lsch (1940) (see Figure 4-31). Although Figure 4-23 doses not truly demonstrate the hexagonal structure of central places in Alachua County, it does illustrate the equilateral triangles for an order B central place. To obtain a true view of the central place structure, one must plot the stru ctures of the surrounding co unties to obtain a truer view of the central place structure. The agglomeration of economic activity is evident but in th e middle of the tug-of-war and the centripetal/multiplicative forces or fact ors responsible for its initial commencement

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114 cannot be determined. Agglomeration of econo mic activity is thought to occur through the interactions of spatial boundaries, trip dispersion and the ex istence of positive profits. The Jonesville location encompasses al l these concepts of agglomerati on. Due to its location, it is in the center of the spatia l boundary interactions of Gainesville, Newberry and Alachua. This central location minimizes trip dispersion and the relatively low land values and lack of competitive economic activity creates th e possibility of economic profits. One can clearly see agglomeration of econo mic activity by reviewing the timeline of development activity, county policy and regulat ion of economic activity. Given the above observations and the many types and definitions of agglomeration, Papageorgiou and Thisse (1985) correctly described it as being one of the most difficult phenomena in spatial analysis. The ability of economic theory to explain the development activity of the study area is limited. Each theory contributes to the explana tion but does not explain the development. The dynamics associated with land development is mu ltifaceted and theory in unable to account for the infinite number of variables that ar e responsible for development patterns. Future Work After completing this case study many of th e case study weaknesses and shortcomings were evident. Initially, during the data collection phase it became evident that the data for this type of study was not readily avai lable or of sufficient quality. Du e to the data quality issues the case study method was chosen. The case study me thod leads to the use of qualitative models instead of quantitative. This study was limited by th e availability and capac ity of the qualitative data to explain the development patterns and by the time limitations to carry out the study. This study presented a number of data issu es and concerns. The availability and consistency of the data were problematic. The da ta used for this study was obtained from several sources; The Alachua County Property Appraiser GIS data, Alachua County Tax Collector tax

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115 data, the Department of Growth Management Offices of Planning & Development and GIS department and the U.S. Bureau of Census. Inc onsistencies of the data were very common. The GIS data that was obtained from the property ap praisers office and the Growth Management GIS department were inconsistent The parcel characteristics we re consistent but the metadata tables did not have the same or consistent information although the Growth Management Department data is obtained from the property appraisers office. Data obtained from the Department of Growth Management Office of Pla nning was not recorded in a consistent orderly fashion. The manner in which the data were or ganized left gaps in time periods and required inference to fill in the missing data, if possible. The U.S. Census data did not provide consistent data for comparison purposes. Examples include the American Community Survey data was not provided for both years 2000 and 2006; there was no information available for the zip code or City of Newberry in 2006. This information w ould have been helpful in explaining the changes in the social economic and housing characteristics. Data issues were more prevalent in the classi cal location theory anal ysis. A portion of the data issues were with the GIS interpolation spatia l analysis model used to generate the land value surfaces. The interpolation method caused some concern because the visual land value surfaces do not represent the true acreage for each la nd use category. The land value surfaces are weighted to create surface valu es at unsampled points. The un sampled points are those that are included in the remaining two categories. Us ing all sample points to create the land value surface would not provide a suitable representation of land values. The weighted surface values also contributed to the large standard deviati ons from the sample means. Reviewing the land value statistics from this analysis revealed large standard deviations from the sample mean. The standard deviation values may have been minimized if the median value was used instead of the

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116 mean. Other useful information may have been obtained through analyzi ng the acreage statistics for the three different land uses. Other weaknesses of this case st udy are due in part to time lim itations. Obtaining the best and most accurate data for this case study would require an in-depth de tailed investigation to accurately obtain the required historical data from the diffe rent county agencies. Another weakness in the study limited by time was the lack of interviews or survey of the community and agencies to triangulate the results of the case stud y. In order to provide true triangulation of the case study, a survey would need to be create d to obtain the data for triangulation. The results of this study i ndicate that there is much work to be done to explain development patterns. The field of new ec onomic geography is making great attempts to develop theory that will address the dynamics of spatial economics. More comprehensive and intensive multidisciplinary studies are necessa ry to obtain a more thorough understanding of dynamics of the spatial economics. Implications Reviewing the results of the analysis for the three land use theory a pplications, the central place theory analysis proved to be the most a pplicable in explaining the study area development pattern. The results of this analysis may be useful in implying the geographical location of possible central places within Alachua County, Florida. As an exercise, utilizing the results of the study area analysis may be extended to imply the next possible central place in Alachua County. Alachua Countys development growth has been primarily in the western portion of the county an d over the years the easte rn half of the county has received little development. This exercise is not intended to explain why development occurred in this manner but to point out that the development potential in western half of the

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117 county is nearing its carrying capacity. Given geographical limitation, the countys development and population growth must locate in the less deve loped portion of the county, the eastern half. Using central place analysis and applying it to Alachua County s eastside figure 5-1 suggests that the next possible cen tral place for the county may be located on the east side of the county and the general location is indicated by the red highlighted area. The approximate location may be within the area created by the intersection of Lake S hore Drive, Hawthorne Road and East University Avenue. This loca tion and the cities of Hawthorne and Waldo are approximately equidistance form each other. Theo ry suggests that cities offering the same order goods and services will be equi distance from each other creati ng an equilateral triangle. Although these three areas are approximately equidi stance (straight-line dist ances) the cities of Waldo and Hawthorne have different orders of goods and services. At present, Hawthorne offers a higher order of goods and services (order B) than Waldo (order C). Given the counties past and current rates of growth and developmen t the order of these cities may possibly change. To address the possible changes in order for the cities of Waldo and Hawthorne, one can look at the infrastructure to determine the de velopmental carrying capac ity for each location. Hawthorne Road and Waldo Road are both f our lane roads and provide ample access for development. In addition to the four lane roads, the Gainesville Airport is located between Waldo and the maps highlighted implied central pl ace. Given the location of the airport and the possible development it may generate, the city of Waldo has the possibility of becoming a higher order central place (order B). If this was to happen and Hawthorne remained a central place of order B, the possible implied central pla ce will be consistent with theory. The location of this implied central place is a speculation suggested by theory. Only time can determine if this location wi ll develop into the next central place in Alachua County. Central

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118 place theory also suggest that given the current order of western central places, the likelihood of developing additional order B central places in the same portion of the county is small. If other order B central places were to develop they would be located outside Alachua County. Another possibility would be that one or more of the order B central places could become annexed into the city of Gainesvi lle. In summary, the future development of an order B central in Alachua County is very likely to occur in the eastern area but the exact location of the development can only be determined over time.

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119 13 Jonesville Order:A B C 6 Major Roads Figure 5-1 Central place theorys implied ne xt possible central pl ace in Alachua County

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128 BIOGRAPHICAL SKETCH Sophia Janene Glenn was born in Youngstown, Oh io. She was the second child of seven. She grew up in Youngstown, Ohio, and graduate d from Woodrow Wilson High School in June 1996. As a high school senior she was accepted in to The Ohio State University undergraduate program. During her senior year, at age 17, she also enlisted in th e U.S. Army Reserve to assist in paying for her college educat ion expenses. She attended the U.S. Army Basic Training and Advanced Individual Training at Fort Jackson, South Carolina, one month after her high school graduation. She began her undergraduate studies at Th e Ohio State University in January 1987, majoring in economics. During the fall quarter 1987, she joined the Army ROTC 2-year program and graduated in 1989 with a commission in the Ordinance Branch. In the midst of her undergraduate education, in 1991, she was mobilized to Fort Lee, Virginia, in support of Operation Desert Storm/Shield. She graduate d in 1992 with a degree in economics and was offered an assistantship to peruse a specialized masters degree in agricultural economics at The Ohio State University. She began her masters degree studies in 1992 and again was called for military duty in 1993 for the mandatory Officers Basic Course at Aberdeen Proving Ground, Maryland. In June 1995, she completed her mast ers degree in agricu ltural economics with a concentration in natural resource economics. After graduation she accepted a position at the Florida A&M Un iversity as an assistant professor in extension. Her duties were concentr ated in the USDA Small Farmer and Technical Assistance Program as a farm financial manageme nt specialist. In 1995, she decided to further her academic career and was accepted into the University of Florida Food and Resource Economics doctoral program. In 2003, she was on ce again called to military duty in support of Operation Iraqi/Enduring Freedom.