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Rural-urban fringe--continuum or dichotomy?

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Title:
Rural-urban fringe--continuum or dichotomy? a study of the high-growth area, Seminole County, Florida
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Richards, Storm L., 1950-
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[s.n.]
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xii, 173 leaves : ill. ; 28 cm.

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Agricultural land ( jstor )
Censuses ( jstor )
Cities ( jstor )
City planning ( jstor )
Counties ( jstor )
Data lines ( jstor )
Datasets ( jstor )
Employment ( jstor )
Fringe ( jstor )
Land use ( jstor )
Cities and towns -- Growth -- Florida -- Seminole County ( lcsh )
Dissertations, Academic -- Geography -- UF
Geography thesis Ph. D
Urbanization -- Florida -- Seminole County ( lcsh )
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bibliography ( marcgt )
non-fiction ( marcgt )

Notes

Thesis:
Thesis (Ph. D.)--University of Florida, 1987.
Bibliography:
Bibliography: leaves 157-165.
General Note:
Typescript.
General Note:
Vita.
Statement of Responsibility:
by Storm L. Richards.

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University of Florida
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Copyright [name of dissertation author]. Permission granted to the University of Florida to digitize, archive and distribute this item for non-profit research and educational purposes. Any reuse of this item in excess of fair use or other copyright exemptions requires permission of the copyright holder.
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AFC1687 ( NOTIS )

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RURAL-URBAN FRINGE--CONTINUUM OR DICHOTOMY?
A STUDY OF THE HIGH-GROWTH AREA,
SEMINOLE COUNTY, FLORIDA











By

STORM L. RICHARDS


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


1987

















To Jeanne and Emerson
















ACKNOWLEDGMENTS


My gratitude must first be expressed to the members

of my supervisory committee. I am indebted particularly to

my chairman, Dr. David Niddrie, who has been supportive of

my work for many years. Most important has been his

personal concern for my academic and professional careers.

Dr. Edward Malecki, who has served as cochairman, provided

me with the direction in making the necessary revisions of

this study. For this, and for his seemingly endless

patience, I thank him. Additionally, I would like to

express my gratitude to Dr. Louis Paganini, who taught me

the value of field geography, which has been important in my

professional career. I would also like to thank Dr. Earl

Starnes for his participation in review of my dissertation.

Finally, I should like to thank Dr. William Maples, whom I

have known and respected since I first came to the

University of Florida, for his direction, his support, and,

above all, his honesty.

I wish also to express my gratitude to the

individuals who have worked with and shared my concerns in

completion of this dissertation, including Dr. Kathy Ross,

Dr. Monte Blair, Dr. John Braaksma, and Dick Haury. My


iii









sincere appreciation goes to Sofia Kohli for editing and

word processing this dissertation.

I wish most of all to express profound gratitude to

my wife, Jeanne Fillman-Richards, who always listened,

supported, and put up with the things necessary to complete

this work.
















TABLE OF CONTENTS


ACKNOWLEDGMENTS...................................... .

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

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

ABSTRACT...... .........................................

CHAPTER

I INTRODUCTION................................

Review of Census Definitions of
Urban, Urban Fringe, and Rural.........
The Urban Fringe....................
The Extended City ...................
Rural Areas..........................
Problem Statement and Purpose of
Present Research.......................
Purpose of Research..................
Study Area ..........................
Intent of the Research..............

II LITERATURE REVIEW............................

Urban and Rural Definitions.............
United States Definitions...........
International Definitions...........
Rural-Urban Definitions.............
Urban Form and Land Use: Models
and Analyses...........................
The Three Classical Models of
Urban Form.........................
Concentric-zone model..........
Sector model...................
Multiple-nuclei model..........
Criticisms of the classical
models. .....................


Page

iii

viii

ix

xi



1


4
7
8
9

11
12
12
18

21

22
24
25
30

32

33
33
34
35

36












Social Area Analysis and
Factorial Ecology.................... 37
Social area analysis.......... 37
Criticisms of social area
analysis..................... 38
Factorial ecology............. 39
Criticism of factorial
ecology .................... 40
Von Thunen's Theory of Agricultural
Land Use............................ 40
Criticisms of Von Thinen's Theory... 41
Alonso's Theory of Urban Land
Market.................. ...... ..... 42
Criticisms of Alonso's Theory........ 43
The Rural-Urban Fringe................. 44
Models of Land Use in the Rural-
Urban Fringe....................... 45
Empirical Studies of the Rural-
Urban Fringe.............. ......... 46
General loss of farmland....... 48
Encroachment of urban
land uses onto the
rural-urban fringe.......... 51
Land-Use Conversion within the
Rural-Urban Fringe of
High-Growth Areas ................. 53
Seminole County as a High-
Growth Area................. ..... .. 54
Conclusion.................... ..... ... .. 55

III METHODOLOGY............... .................. 58

Traffic Zones as a Standard Areal
Measurement............................ 59
History of Traffic Zones............ 59
Use of Traffic Zones in
Seminole County ................... 63
Use of the Traffic Zone in
the Present Study ......... ......... 68
Definitions of the Variables............ 71
The Roles of Distance and Density........ 74
Regression Analysis................. 74
F-Values.................. ........... 76
Z-Score Statistic.......... ......... 77
Summary................... ........ .....** 77

IV ANALYSIS.................................. .. 79

Analysis and Data Sets................... 79
Presentation of Findings................ 80












Population--Distance
Relationships...................... 81
Single-Family Housing--
Distance Relationships............ 86
Multi-Family Housing--
Distance Relationships............. 92
Persons per Household--
Distance Relationships............ 96
Resident Employment--Distance
Relationships...................... 97
Attendant Employment--Distance
Relationships ..................... 103
Retail Employment--Distance
Relationships...................... 103
Income--Distance Relationships....... 107
Conclusions ............................. 112

V SUMMARY AND CONCLUSIONS..... .................. 117

Summary of Findings..................... 118
Conclusion.............................. 124
Future Studies of the Rural-
Urban Fringe........................... 126

APPENDIX: SOCIOECONOMIC DATA--1980 ................... 132

REFERENCES..... ........... ............................. 157

SUPPLEMENTAL BIBLIOGRAPHY............................. 166

BIOGRAPHICAL SKETCH........................ ............ 172


vii
















LIST OF TABLES


Table Page

1. Seminole County Population, 1930-1980........ 17

2. Sources of Comprehensive Planning Data
for Cities in Seminole County, Florida...... 64

3. Population and Distance from Node............ 82

4. Single-Family Housing and Distance
from Node....................... ............. 88

5. Multi-Family Housing and Distance from
Node....................... .................. .. 93

6. Persons per Household and Distance
from Node.................... ..... ... ........ 98

7. Resident Employment and Distance from
Node...................... ................... 100

8. Attendant Employment and Distance
from Node........ ............................ 104

9. Retail Employment and Distance from
Node....................... .................. .. 108

10. Income and Distance from Node............... Ill

11. Comparison of Means of Density
Populations................... ............ .. 115

12. Comparisons of F-Value and Significance
Levels (95-Percent Confidence Level)......... 122

13. Comparisons of Values for Incorporated
and Unincorporated Intersections............. 123


viii
















LIST OF FIGURES



Figure Page

1. Seminole and adjacent counties............. 13

2. Counties included in the Orlando
Metropolitan Statistical Area and
the Orlando Urban Area Metropolitan
Planning Organization........................ 14

3. Model describing land use in the
rural-urban fringe ........................... 47

4. Seminole County traffic zones............... 65

5. Seminole County census tracts............... 67

6. The incorporated cities and urban
node of Seminole County.................... 70

7. Regression lines for incorporated
and unincorporated population size
planning data............................... 83

8. Regression lines for incorporated
and unincorporated population density
data ................................... ..... 84

9. Major transportation arteries in
Seminole County.................... .......... 87

10. Regression lines for incorporated
and unincorporated single-family
housing planning data................ ...... 90

11. Regression lines for incorporated
and unincorporated single-family
housing density data......................... 91

12. Regression lines for incorporated
and unincorporated multi-family
housing planning data....................... 94










Figure Page

13. Regression lines for incorporated
and unincorporated multi-family
housing density data......................... 95

14. Regression lines for incorporated
and unincorporated persons-per-
household planning data...................... 99

15. Regression lines for incorporated
and unincorporated resident
employment planning data................... 101

16. Regression lines for incorporated
and unincorporated resident
employment density data.................... 102

17. Regression lines for incorporated
and unincorporated attendant
employment planning data................... 105

18. Regression lines for incorporated
and unincorporated attendant
employment density data...................... 106

19. Regression lines for incorporated
and unincorporated retail
employment planning data.................... 109

20. Regression lines for incorporated
and unincorporated retail
employment density data............... ...... 110

21. Regression lines for incorporated
and unincorporated income dollars
planning data..................... ........... 113

22. Regression lines for incorporated
and unincorporated income dollars
density data................... .............. 114
















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



RURAL-URBAN FRINGE--CONTINUUM OR DICHOTOMY?
A STUDY OF THE HIGH-GROWTH AREA,
SEMINOLE COUNTY, FLORIDA

By

Storm L. Richards

December 1987

Chairman: David L. Niddrie
Cochairman: Edward J. Malecki
Major Department: Geography

Despite a growing interest in urban, rural, and

rural-urban fringe, it has been difficult to define these

terms precisely. Within the United States, the criteria set

by the Bureau of the Census are most used as definitions.

These are set out in such a way, however, that they are

often inappropriate for local decision-making. Yet

economic, political, and administrative decisions often

depend on whether or not areas are labeled "urban" or

"rural."

At present, decisions, particularly in high-growth

areas such as Seminole County, Florida, are often made on

the basis of a regional data set which may or may not

reflect characteristics of rural and urban. This study










examines, through various statistical analyses, the utility

of one such data set in differentiating urban and rural

populations and areas.

The analysis describes and compares the relationship

between distance from the urban node and eight socioeconomic

variables in each of six data sets. The F-tests show that x,

distance from the node, is useful in predicting y, increase

or decrease in the socioeconomic variables in many of the

cases.

Thus, the study supports a distance-decay function

of the variables in several of the data sets. Because of

the gradient within these data sets, the study also suggests

the existence of a rural-urban fringe which is a continuum

between rural and urban areas of the county.


xii
















CHAPTER I
INTRODUCTION


Unfortunately, there is no universally accepted
distinction between urban and rural.
--Murphy 1966:1

In the last ten years, a large proportion of the
theoretical work in urban geography and other
disciplines in the urban realm has been devoted to
the problem of definition.
--Sayer 1984:279

Throughout the United States, and especially in

high-growth areas such as Florida, cities are expanding

beyond their incorporation boundaries. Near these cities,

areas which had once been rural countryside, farms,

pastures, and woods are now sprouting residential,

commercial, and industrial developments. The amount and

direction of urban growth are often unprecedented and

unpredicted, and the effects of the growth on the

surrounding rural areas are poorly understood. The greatest

amount of change, however, and therefore the greatest effect

on the countryside occurs within that nebulous area often

called the rural-urban fringe.

Despite a growing interest among geographers,

planners, and anthropologists in urban, rural, and rural-

urban fringe areas, it has been difficult to define these












terms precisely. Definitions become particularly difficult

within regions which have been subjected to rapid urban

development with their residential, commercial, and office-

complex growth. Within these rapid-growth regions, the

distinctions among urban, rural, and fringe areas may be

obscure and assessments are often based on inadequate

information.

The terms urban and rural have wide and diverse

meanings both geographically and culturally. It is not

difficult, therefore, to understand that defining these

terms is among the most problematic area of any rural-urban

fringe study. In order to determine where rural and urban

areas interface to form the rural-urban fringe, it is

clearly necessary to know what constitutes a rural area and

an urban area. As Fesenmaier et al. (1979:255-256) point

out, "There seems,to be little prospect of a more adequate

Definition of the limits of the rural-urban fringe since the

question simply begs the far greater one of defining urban

and rural."

A better knowledge and, ultimately, the definitions

of urban, rural, and rural-urban fringe require the

differentiation of characteristics, or gradations of

characteristics, which are urban or rural. The

identification, precise description, and quantification of

these characteristics, or variables, is essential, not only













to academicians studying urban areas, but also to planners

and policy-makers who are involved in urban growth and rural

management.

In historical terms, areas designated as rural or

urban have been treated as opposites with few, if any,

characteristics in common. The reason for the urban or

rural designation may be as arbitrary as the placement of an

incorporation line. In such instances, the incorporation

boundary is analogous to the wall of a medieval "walled

city." The area not within the "wall" was not considered

part of the city even when construction and population moved

beyond the wall. It was not until the wall was moved to

encompass the newly built-up area that the rights and

protection of the city dwellers were conferred on that area.

In the United States, incorporation boundaries,

population, and, to a lesser extent, population density and

economic development, have been the major factors used by

the Bureau of the Census to define urban. A review of the

various definitions used by the Census since the turn of the

century illustrates the emphasis placed on these few factors

in the designation of urban, rural, and fringe areas. The

Census criteria are particularly important because

. most people follow the lead of the Bureau of the

Census which defines certain types of areas as urban"

(Murphy 1966:1).














Review of Census Definitions
of Urban, Urban Fringe, and Rural

The 1910 Census established the most important

element in all subsequent Census definitions of urban. In

that year all incorporated places with 2,500 or more

inhabitants were designated urban (U.S. Bureau of the Census

1913).

From 1910 until 1950, the basic definition of urban

remained unchanged. Each Census, however, also included

special rules to cover certain areas which were not

incorporated, but contained a substantial population. In

1910 and 1920, all towns (townships) in Massachusetts, Rhode

Island, and New Hampshire with populations of 2,500 or more

were included whether or not they were incorporated because

in these states incorporation is not granted until the

population reaches 10,000. In 1930, the Census special

rules stated that all townships in Massachusetts, Rhode

Island, and New Hampshire were included in the urban

designation if they had a population of 2,500 and "certain

urban characteristics" which were not specified in the

Census. The category was also expanded to include "a few

large townships in other states." Again, the criteria for

inclusion were nebulous.

In 1940, the special rules became more exacting.

Townships in the three previously mentioned New England













states were included if they contained one village with a

population of 2,500 or several villages whose combined

population was greater than 50 percent of the total

population of the township. In other states, townships, or

other political subdivisions, were included if they had a

population of 10,000 and a density greater than 1,000

persons per square mile (U.S. Bureau of the Census 1913,

1923, 1933, 1942). Thus, the 1910, 1920, 1930, and 1940

Census definitions of urban were based almost entirely on a

combination of incorporation lines and a minimum population

standard. There was only peripheral recognition of some

areas which were equally populous or densely settled, but

remained unincorporated.

By 1950, growing concern with a more precise

separation of urban from rural fostered major additions to

the basic Census definition of urban. For the first time,

the term "urban territory" was used and the concepts of

"places," "urbanized areas," and "urban fringes" were

included. These terms have to be described in detail

because they continue through the 1980 Census, with only

minor revisions, to be the basis for most urban, rural, and

urban-rural fringe determinations in the United States.

The 1950 Census defines the urban territory as

incorporated places with populations of 2,500 or more, the

urban fringe around cities with 50,000 or more inhabitants,













and unincorporated places outside of the urban fringe with

populations of 2,500 or more. Since the territories

described in the latter two categories are not legally

defined, the Bureau of the Census set up boundaries prior to

enumeration (U.S. Bureau of the Census 1952). These

boundaries were based on the concepts of "places,"

"urbanized areas," and "urban fringe" described in the

Census.

Places are concentrations "of population regardless

of legally prescribed limits, powers, or functions" (U.S.

Bureau of the Census 1962:xiv). Two types of places,

incorporated and unincorporated, are recognized by the

Bureau of the Census. Places are considered urban only when

their population meets or exceeds the minimum limit of 2,500

(U.S. Bureau of the Census 1952, 1962, 1972, 1982).

An urbanized area (UA) consists of one or more

central city or cities and the urban fringe. The central

city continues to be defined as the largest city in the

area, but exact population requirements for a central city

have changed over time. In 1950, the largest city was

required to have a population of 50,000 or more for central

city designation. The second- and third-largest cities

could also be central cities if their populations were one-

third that of the largest city and at least 25,000 (U.S.

Bureau of the Census 1952). By 1980, the minimum population













requirement for central city designation had been abandoned.

Instead, a minimum population of 50,000 for the entire

urbanized areas was substituted (U.S. Bureau of the Census

1982).


The Urban Fringe

The second element of an urbanized area is the urban

fringe which lies without, but contiguous to, the central

city or cities. The following criteria define those areas

included in the urban fringe:

1. Incorporated places with a population of

2,500 or more

2. Incorporated places with a population of

less than 2,500 if the area has at least 100

dwelling units and a density of 500 or more

units per square mile which is equivalent to

a density of 2,000 persons per square mile

(in 1980 this requirement was dropped to

1,000 persons per square mile)

3. Unincorporated areas with a density of 500

dwelling units per square mile

4. Commercial, recreational, industrial, and

other functionally related areas












5. Outlying noncontiguous areas where the

required dwelling unit density located

within 1.5 miles of the primary contiguous

urbanized portion, as measured by the

shortest connecting highway, as well as by

other outlying areas within 0.5 mile of said

noncontiguous areas "which meet the minimum

residential density rule" (U.S. Bureau of

the Census 1952:xiv).


The Extended City

In 1970, another concept, that of the "extended

city," was recognized. An extended city is a city whose

incorporation boundary has been expanded to include

substantial territory which is rural in character. Only the

urban parts of an extended city are considered the central

city if such a designation applies (U.S. Bureau of the

Census 1972, 1982).

As has been shown, recent Census definitions of

urban, which include the urban fringe, have become more

complex and more specific than previous definitions. While

there is a continued reliance on corporate boundaries and

minimum population, other factors, such as population

density and dwelling-unit density, are now considered,

especially in the definition of the urban fringe.













Rural Areas

By contrast, the Census definition of rural remains

the same as it was at the turn of the century. With one

exception, no specific characteristics have been assigned to

describe rural areas. The exception is that of an extended

city. In 1970, when the concept of the extended city was

recognized, the "Bureau of the Census examined patterns of

population density and classified a portion or portions of

each such city as rural" (U.S. Bureau of the Census 1972:v).

The rural classification required that the population

density be less than 100 individuals per square mile in an

area of at least five square miles or 25 percent of the

incorporated area (U.S. Bureau of the Census 1972). Aside

from this one instance, the Census definition of rural

simply states that any area not classified as urban is

rural.

The criteria for urban, urban fringe, and rural

which are established by the Census have been delineated

because these are the most widely accepted and utilized

definitions currently available in the United States. The

criteria also determine the various categories of Census

data. Thus, if the criteria and, therefore, the categories,

are flawed, the data are flawed. This could significantly

affect research into urban, rural, and rural-urban fringe












because virtually all of that research is based on Census

data.

Several problems with the Census definitions and

data are apparent. Even the 1980 Census acknowledges that

the absolute lower limit for urban designation has caused

consternation among those who inhabit smaller places.

"Within small counties, measurements of urban and rural

populations over time may be significantly affected by the

increase or decrease of a place's population across the

2,500 population threshold, e.g., the increase of 1 person

to a place of 2,499 results in an increase of 2,500 to the

county's urban population" (U.S. Bureau of the Census

1982:51). By the same token, the place itself wavers back

and forth between a rural and an urban designation depending

on the 2,500th individual.

Other problems are encountered in the urban fringe

criteria for urban areas. Boundaries for the urban fringe

are based on population density and contiguity or proximity

to areas with certain population densities. For example,

industrial and office parks are included in the fringe only

if they are within densely settled areas. Since land use,

even if it would seem typically urban, is not considered, it

is possible to conceive a situation, especially in a rapidly

developing area, where large segments of land devoted to

office, research, or industrial parks are relegated to rural













status simply because they are beyond areas with certain

population density limits.

For large-scale, generalized research, the Census

criteria may be adequate. Local research and planning,

especially in rapidly developing areas, however, requires

more precise definitions of urban, rural, and rural-urban

fringe. Unfortunately, such definitions do not exist.


Problem Statement
and Purpose of Present Research

In much of the United States, development is

spilling beyond the incorporation boundaries of cities into

what were regarded as rural areas. The consequences of

rapid urbanization on the countryside are dramatic and, in

some cases, seem almost instantaneous. A recent Wall Street

Journal article (March 26, 1987) described the phenomenon in

the following terms:

From Plano, Texas, to Middlesex County, New
Jersey, from Aurora, Colorado, to Gwinnett County,
Georgia--places once considered rural and idyllic
and far from the central-city blues--the scenario is
the same. Offices and shopping centers shoot up,
subdivisions follow, and it gets harder to tell
urban from suburban from rural. Mini-cities seem to
be everywhere. (Morris 1987:1)

In high-growth areas across the country, urban

researchers, planners, and governmental decision-makers face

the problem of distinguishing urban, rural, and rural-urban

fringe areas. Such information is essential for













comprehensive plans which outline growth and development

guidelines, transportation documents that give direction to

federal, state, and local roadway plans, grants for housing,

capital improvements, property acquisition, and local

governmental policy.


Purpose of Research

Efforts to locate precisely and predict urban,

rural, and fringe areas are often hindered because the

process and characteristics of urbanization in rapidly

developing rural areas are poorly understood. The purpose,

then, of the present research is to analyze urbanization in

a rapidly developing rural area, to improve the

understanding of the characteristics associated with rapid

urbanization, and to contribute to a better definition of

the rural-urban fringe.


Study Area

The geographic focus of this study, Seminole County,

is located in Central Florida adjacent to Orange, Lake, and

Volusia Counties (see Figure 1). It is included, along with

Orange and Osceola Counties, in the Orlando Metropolitan

Statistical Area (MSA) and the Orlando Urban Area

Metropolitan Planning Organization (OUAMPO) (see Figure 2).

Seminole County was selected as the study area

because it is exhibiting several signs of rapid






























































Figure 1. Seminole and adjacent counties





























































Figure 2. Counties included in the Orlando Metropolitan
Statistical Area and the Orlando Urban Area
Metropolitan Planning Organization













urbanization. Agricultural employment and rural residence,

according to Census criteria, are dropping. Total

population and urban residence, again according to Census

criteria, are rising rapidly and population density is among

the highest in the state.

Historically, the county has been predominantly

agricultural, producing truck crops, such as celery,1

cabbage, and watercress, and the agricultural sector has

provided the major employment. In recent decades, however,

the percentage of agricultural employment has dropped

dramatically. In 1940, 3,290 individuals, or 36 percent, of

the total labor force of 9,134 were employed in agriculture

(U.S. Bureau of the Census 1942). By 1980, less than 2

percent, or 1,622, of the 82,316 employed individuals in the

county worked in the agricultural sector (U.S. Bureau of the

Census 1982).

Rural residence, based on the Census criteria for

rural, has also decreased sharply. Between 1970 and 1980,

rural residence dropped from 31,709 to 15,578 within the

county. This represents a -50.9 percent change within one

decade. By contrast, urban residence has risen from 51,983

in 1970 to 164,174 in 1980, representing a 215.8 percent



IThe nickname of the county seat, Sanford, is still
Celery City even though celery is no longer grown in the
county.













increase in the urban population (U.S. Bureau of the Census

1982). The percentage of rural residence decrease is second

only to Pinellas County, while the percentage of urban

residence increase is the third greatest in the state.

With 603.2 persons per square mile, Seminole County

was the sixth most densely settled county in Florida in

1980. It also experienced the seventh greatest percentage

of population increase--114.8 percent, between 1970 and 1980

when the population rose from 83,692 to 179,752 (see

Table 1).

Despite the county's seemingly dense population and

high percentage of population increase, the population is

not evenly distributed. There are some sections of the

county which appear clearly urban, others which seem rural,

and still others which may not fit in either category. Yet,

the Census has separated the population, and thus the land

area, into rural and urban contingents based solely on

incorporation lines, population size, and/or population

density. These may not be the most important and diagnostic

criteria for such classifications. While the "city wall"

incorporation limits may differentiate urban from rural for

carrying out governmental policy, other definitions of urban

and rural must now be considered. A functional definition,

particularly in high-growth areas such as Central Florida,

is required. Areas well beyond incorporation limits often




















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exhibit characteristics similar to those in the city, while

areas which appear rural according to a functional

definition and governmental policy may be viewed quite

differently by developers, who base their perspective on

profitability. The present research, therefore, utilizes

alternative types of data which may lead to a clearer

distinction between, and ultimately understanding of, urban,

rural, and rural-urban fringe areas in rapidly developing

sections of the country.


Intent of the Research

The intent, then, of the presen- research is first

to characterize the various areas of Seminole County,

Florida, using a standard socioeconomic data set derived

from a variety of sources (East Central Florida Regional

Planning Council 1984:v) and which is divided into "traffic

zones" (TZs). Such information is used by regional, county,

and municipal governments as well as planning agencies in

Central Florida. The data include population

characteristics, housing types, employment, income, and

education. (See page 71 in Chapter III.)

Secondly, through the manipulation of the standard

data set, it is possible for areas in Seminole County to be

more clearly defined and designated as rural, urban, or

rural-urban fringe. At present, for planning purposes,













areas of the county which are incorporated are simply

considered urban and those which are unincorporated are

considered rural, but these simple designations of urban and

rural are unacceptable. Even the greatly criticized Census

designations no longer depend solely on incorporation

boundaries to distinguish urban from rural.

Thirdly, areas defined as urban, rural, and rural-

urban fringe as a result of this study are mapped and

compared with areas which have been designated similarly by

the Census. Based on these comparisons, recommendations for

criteria which may more accurately depict urban, rural, and

rural-urban fringe areas are enumerated.

It may be argued that the conversion of rural lands

to urban has little to do initially with population data.

Thus, a single calculation of population change, especially

without determining which characteristics represent urban

and which represent rural, does little to explain, or

accurately describe, rural-to-urban conversion either from a

geographic or planning perspective. Yet, the most widely

accepted and used definition of urban, and, therefore,

rural-urban fringe and rural, in the United States is based

largely on the single characteristic of population. As a

result, any studies of urban expansion, rural conversion, or

rural-urban fringe development in an area rely almost

entirely on population change. Alternative characteristics










20


must be, and are, explored in the present study of an area

experiencing phenomenal growth.
















CHAPTER II
LITERATURE REVIEW


The urban-rural boundary becomes so blurred that
the dichotomy becomes arbitrary and
essentially meaningless. No one has been able to
demarcate the boundary of a city in a consistent
fashion.
--Bourne and Simmons 1978:22

[Yet, while] abstractt social theory can .
abstract from the contingencies of spatial form,
research on concrete effects must take them
into account.
--Sayer 1984:282

The urban-rural boundary has not been, and may never

be, demarcated in a manner which is satisfactory for many

types of urban and rural research. While the Bureau of the

Census definitions and criteria are used for much of the

urban and rural research conducted in the United States,

these designations are not adequate for local research and

planning. They are also unacceptable for studies in other

countries which depend on their own census definitions of

urban and rural.

Despite the fact that there is no universally

accepted differentiation of rural and urban, many

disciplines, including geography, sociology, planning, and

anthropology, have developed subfields of study based on an

urban-rural dichotomy. Each subfield has its own

21













considerable and specialized body of literature.

Nevertheless, because the boundaries between urban and rural

are often ambiguous and contrived, areas of research within

the separate subfields occasionally overlap. This is

particularly true in the case of rural-urban fringe studies.

The literature reviewed for the present study is

drawn mainly from urban and rural geography; however,

sources from other, closely related disciplines are also

discussed. Sociology, anthropology, and planning each have

urban and rural contingents in which problems of definition

similar to those encountered within geography must be

confronted. The literature review, then, is set out,

regardless of discipline, within the broad themes of urban

and rural.


Urban and Rural Definitions

One technical aspect that causes some concern is
the actual delimitation of geographic areas that can
be regarded as urban. Such delimitation is
necessary, particularly in studies focusing on .
rural-urban land conversion.
--Yeates 1987:64

Because there is no consensus among researchers on

the exact definition of urban, it is difficult to pinpoint

areas, particularly peripheral areas, which are, or may

become, urban. For some urban investigators, this

difficulty in defining specific areas as urban has become a

moot question. In fact, it has been suggested "that the













concept of a separate urban phenomenon, defined spatially,

is irrelevant to understanding society" (Johnston 1986:103).

To bolster this position, the researchers argue that, in

more developed countries, factors such as mass media,

migration, and transportation networks have spread the

"urban way of life" to such an extent that rural-urban

distinctions can no longer be studied (Dunleavy 1982, Lang

1986). Others, however, contend that there are urban-rural

distinctions and issues which may be studied only through

the bounding of discrete areas into urban and rural (Sayer

1984, Johnston 1986, Lang 1986, Yeates 1987).

If the position that urban areas must be delimited

in order to address urban issues and questions adequately is

accepted, then the problem of urban definition must be

confronted and specific characteristics of urban must be

explored. In this context, several characteristics

attributed to urban areas are commonly used to discriminate

between urban and rural places. One of the most widely used

criteria is "high" population density (Cadwallader 1985,

Yeates 1987). The determination of exactly what level of

density constitutes "high," however, falls upon the

individual researcher (Yeates 1987). Another popularly

employed characteristic is nonagrarian-related occupations

(Cadwallader 1985, Johnston 1986, Lang 1986). Johnston

(1986) used this criterion in his study of political












attitudes and location by designating British constituencies

with less than 3 percent agricultural employment as urban.


United States Definitions

Within the United States, the criteria set by the

Bureau of the Census are most often used to define urban and

rural areas (Murphy 1966, Lang 1986). The major factors

employed by the Census to determine urban areas are

population size, incorporation boundaries, and, to a lesser

extent, population density and economic development. The

major factor determining designation of rural areas is that

the areas are not urban by census definition.1

Unfortunately, the census criteria and, therefore,

the census definitions, are not always sufficient. In a

recent study of the adequacy of census definitions, Lang

found that policyiy makers and census data users across the

United States are calling for revisions of the definitions

or urban and rural population and places currently used by

the U.S. Census Bureau. They contend that the definitions

are outdated and do not reflect the current realities of

population distribution, lifestyles, and settlement

patterns" (Lang 1986:118). Despite these criteria, the

census data remain at present the most comprehensive and



1Census definitions of urban and rural have been
discussed in greater detail in Chapter I, pages 4-11.













immediately available source of urban and rural information.

Therefore, whether or not they are based on adequate

definitions, these data will continue to be used for much of

the recent research in the United States.


International Definitions

If comprehensive definitions of urban and rural for

the United States have proven elusive, such definitions at

an international level have been impossible. Numerous

problems have been encountered which negate an international

consensus of criteria for urban and rural. In most cases,

comparable data are simply not available. Many countries

lack the skills necessary to collect detailed information,

while others do not deem detailed census data a national

priority either for economic or cultural reasons. Also,

where the data are available, there is often inconsistency

of nomenclature and of geographic bounding of urban areas

between countries. The result is a "bewildering variety of

definitions of 'urban' and 'rural'" (United Nations

Secretariat 1975:18).

By describing just one of the problems, that of data

comparability, it becomes easy to understand why the United

Nations has allowed that standard international definitions

of urban and rural are not, and may not be, possible (Lang

1986). The problem of comparable data is illustrated in two













ways. The first is a discussion of which general census

criteria are used to establish urban areas in different

countries and the second is to describe how the criteria are

interpreted and applied to the delimitation of urban areas

in specific, selected countries around the world.

The ways in which different countries determine

urban areas range from simple to complex to bewildering. In

a survey of the characteristics used in various national

censuses to indicate urban areas, the United Nations

Secretariat (1975) found great diversity. Some countries

used only one characteristic, others used two or more, and

still others (56) did not indicate what they used.

Population size, the most common criterion, was employed

singly in 23 cases and in combination with other criteria in

49. Housing or population density, while used as the

indicator in only one census, was combined with other

characteristics in 11 censuses. Major economic activity was

also used as the criterion in only one instance, but was

used in concert with others in eight censuses. Type or

structure of government appeared alone three times and

combined with other characteristics three times. Finally,

various urban indicators not included in the other

categories were used by themselves in three censuses and in

combination with other characteristics in 16 others (United

Nations Secretariat 1975:18-19).













The astonishing array of characteristics and

combinations of characteristics used to define urban in the

various censuses is only part of the problem faced by the

urban researcher who is trying to compare international

data. Because each country sets its own values for, and

interpretations of, the criteria it chooses, comparisons

become even more difficult. The following descriptions of

census criteria for urban and rural in several countries

illustrate these points.

In some countries, designations of urban and rural

are based on concepts similar to the "places" designations

in the U.S. Census. Legal boundaries and powers are

disregarded and concentrations of population are used

instead. In Ghana, population size of places is the major

determinant of urban and rural. Concentrations of 5,000 or

more inhabitants are considered urban. The Swedish urban

and rural designation system combines population size with

housing density. Places with 200 or more residents in

dwellings that are 200 or less meters apart are considered

urban (Wander 1975). The Canadian Census is similar to the

U.S. Census in that it uses both population size and

population density as urban designators. Areas with a

population of 1,000 or more and a density of at least 400

per square kilometer are considered urban (Yeates 1987).













By contrast, some countries require official

bounding for urban designation. Argentina, for example,

considers an area urban if its population is 2,000 or

greater and it has official boundaries. All other areas,

regardless of population concentration, are rural (Wander

1975). India classifies legally recognized cities and towns

with populations of 5,000 or more as urban if they also have

a population density of 1,000 per square mile and three-

quarters of those employed work in other than the

agricultural sector of the economy (Bose 1975, Wander 1975,

Jordan and Rowntree 1982).

Still other countries define urban areas "in terms

of minor civil divisions which have fixed boundaries

and some local government status" (Wander 1975). Until the

1960 Census, only "shi," cities with populations of 30,000

or more, were recognized as urban in Japan. The rest of the

country was considered rural, or "gun." However, as in

Extended Cities in the U.S. Census, "shi" often contained

extensive areas which might better be classified as rural so

the Japanese Bureau of Statistics devised the concept of

Densely Inhabited District (DID). A DID is defined as any

area of contiguous enumeration districts with a population

of 5,000 or more and a density of at least 4,000 persons per

square kilometer. The grouping of enumeration districts












must also be within the boundaries of a "shi," "machi"

(town), or "mura" (village) (Wander 1975, Yamaguchi 1984).

The Dutch system divides municipalities into urban,

urbanized rural, and rural using a variety of

characteristics. Urban municipalities are those with

overall population densities of 300 persons per square

kilometer. These areas must contain at least one nucleus in

which 70 percent of the area's population (a minimum of

2,000 individuals) lives. This settlement must also have a

population density of 2,000 per square kilometer and at

least 90 percent of the male population must be

nonagriculturally employed. In urbanized rural areas, these

characteristics are considered. The most important is that

less than 20 percent of the male population is employed in

agriculture. Also, the major settled area has a population

less than 20,000. The third characteristic employed is

commuter patterns. Rural municipalities are those with more

than 20 percent of the male population employed in the

agricultural sector. These areas have less than 5,000

inhabitants in the major settlement and less than 300

persons per square kilometer overall density (Wander 1975,

Borchert 1984).

While only a few, selected examples of the criteria

used in different countries to determine urban or rural

status of areas have been described, it is apparent that













cross-cultural comparisons of urban and rural data are

difficult at best. It is also evident that none of the

combinations of criteria, even the relatively complex Dutch

system, is adequate for differentiating urban, rural, and

rural-urban fringe at the local level.


Rural-Urban Definitions

The most recent U.S. Census definition (1980) (see

Chapter I, pp. 8-9, of this study) of the rural-urban

fringe, also known as the "urban fringe" or the urbann

fringe" (Champion 1983:30), differs only slightly from the

earliest academic descriptions. In 1937, T. L. Smith

described the rural-urban fringe as "the built-up area just

outside the corporate limits of the city" (Pryor 1971:59).

In an article entitled "Urban-Rural Fringe" written

in 1942, Wehrwein outlined the inevitable growth which must

occur when there is an absence of land-use control within

the zone of transition which lies between areas of well-

recognized urban development and lands devoted to

agriculture. In his summary, Wehrwein predicted that the

availability of transportation, cheap land, lower taxes, and

fewer land-use controls in rural areas would become the

incentives for industrial relocation from the city to these

transition areas (Wehrwein 1942).













In 1946, Rodehauer defined the rural-urban fringe as

"that area in which the land is utilized in an urban manner,

while at the same time certain attributes of the rural area

are present" (Rodehauer 1946:50). This general description

continues to be quoted in the literature (Fesenmaier et al.

1979).

Russwurm's study (cited in Fesenmaier et al. 1979)

differentiated a rural-urban fringe based on density of

population and the presence or absence of farming. He

specified that 50 percent or more of the fringe population

should be nonfarming individuals and that in the large

Canadian urban areas with populations of 100,000 or more,

the fringe should be more than 10 miles wide.

During the same year, 1971, Pryor suggested the

following detailed definition:

The rural-urban fringe is the zone of transition in
land use, social and demographic characteristics, lying
between (a) the continuously built-up urban and suburban
areas of the central city, and (b) the rural hinterland,
characterized by the almost complete absence of nonfarm
dwellings, occupations and land use, and of urban and
rural social orientation; an incomplete range and
penetration of urban utility services; uncoordinated
zoning or planning regulations; areal extension beyond
although contiguous with the political boundary of the
central city; and an actual and potential increase in
population density, with the current density above that
of surrounding rural districts but lower than the
central city. These characteristics may differ both
zonally and sectorally, and will be modified through
time. (Pryor 1971:62)













After elaborating on his definition of the fringe

area, Pryor states that the characteristics he describes are

not based on empirical evidence. He then calls for further

investigation by other researchers.


Urban Form and Land Use:
Models and Analyses

S. geographers have been chiefly associated with
the description and analysis of urban form. What
theory there is of urban form in geography, however,
is largely derived from other fields. One is urban
sociology, especially the human ecology school of
Chicago (Park, Burgess, and others). Another is
land economics .
--Agnew, Mercer, and Sopher 1984:12

In their pursuit of generalizations and laws which

explain and predict urban form and urban and rural land use,

geographers have used a number of models and analyses.

Certain of these have had considerable impact on geographic

thought and continue to be discussed and criticized in the

literature. They include the classical models of urban

form: concentric zone, sector, and multiple nuclei; social

area analysis and factorial ecology; and von Thunen's

agricultural land-use theory and Alonso's land-rent theory.

While none of these studies has dealt directly with the

problem of urban and rural definitions, each has contributed

to a better understanding of the characteristics of urban or

rural areas.













The Three Classical Models of Urban Form

The three classical models of urban form--concentric

zone, sector, and multiple nuclei--were developed in

response to the desire to understand the type and direction

of urban growth (Light 1983). While all three were based on

the ecological theory, each presents a different description

of city form (Jordan and Rowntree 1982, Light 1983).


Concentric-zone model

Burgess (1925), University of Chicago sociologist,

advanced the concept of concentric zones for urban

development. His theory suggested that urban land use and

growth could be described in terms of five concentric, and

internally homogeneous, zones. At the center of his model

is the central business district, the core of the city.

Surrounding the central business district is the area he

termed the "zone of transition." The urban characteristics

of this area include a mixture of land uses and diversity of

residential areas, often in a state of deterioration. The

third zone consists largely of "blue-collar" homes. The

fourth zone is another residential area catering mainly to

"white-collar" workers and middle-class families. The

outermost zone, the commuter zone, lies outside the

corporate boundary and contains higher-income residential

areas (Palm 1981, Jordan and Rowntree 1982, Light 1983,












Cadwallader 1985). The fifth zone probably corresponds with

what has been called the rural-urban fringe, although

Burgess did not explicitly refer to it.


Sector model

In 1939, approximately 10 years after Burgess

published his work on the morphology of the city, Hoyt

provided fresh insights into the patterning of residential

land use. He postulated that residential land uses "tend to

be arranged in wedges or sectors radiating from the center

of the city along the lines of transportation" (Murphy

1966:211). These sectors were divisible and Hoyt elaborated

on both their physical composition and evolution. He stated

that the gradient or outward progression of residential

properties moved "downward" from high-rent2 areas to less

affluent sectors. The "low"-rent areas occupy different

sectors which may occur in a variety of urban areas (Hoyt

1939, Palm 1981, Jordan and Rowntree 1982, Light 1983).

The dynamics of the sector concept are associated

with high-rent areas. According to Hoyt, high-price areas

exert an influence on the direction of residential growth





2Rent is defined as monies paid in the form of
purchase or lease for occupying space (Jordan and Rowntree
1982).












and real-estate agents may influence the direction of high-

rent growth (Palm 1981).


Multiple-nuclei model

The concept of the multiple-nuclei forms of the city

evolved from studies by R. D. McKenzie (1939), author of The

Metropolitan Community. It was elaborated by Harris and

Ullman in 1945. In this model, a separate function for each

nucleus from one metropolitan area to another is specified.

The relationship of urban ares is derived from a clear

distinction between the central business district and other

identifiable areas (Palm 1981, Jordan and Rowntree 1982,

Light 1983).

Harris and Ullman identified four factors which they

believed caused the emergence of separate nuclei in urban

land use:

1. The interdependence of certain types of

activities and their need to be located in

close proximity

2. A natural clustering tendency among certain

types of activities

3. A repetition of certain types of activities,

and












4. The related factor of high rents or high

land costs which can be an attractive or

repelling force


Criticisms of the classical models

The classical models have been the subjects of much

criticism. Both the theoretical underpinnings of the models

and the models themselves have come under fire.

Urban ecology, the theory which is the basis for the

concentric ring, sector, and multiple-nuclei models,

describes a process of invasion-succession land-use change

in which the mechanism is economic competition (Light 1983).

Critics suggest that there is too much emphasis on

mechanistic causal forces (Ley 1983). Unlike competition in

the animal world, human actions are subject to laws,

institutions, and conventions (Cadwallader 1985). The

theory also fails to account for sentiment and social values

which may be important in the determination of land use

(Murphy 1966, Ley 1983, Light 1983).

Other criticisms are directed at the models. It is

charged that they are too simplistic and lack universality

(Ley 1983). They exaggerate rigid land-use boundaries which

cannot be proven empirically (Murphy 1966, Ley 1983). Also,

the homogeneity of the various zones and sectors has been

questioned (Ley 1983). "But the very fact that controversy












continues and the debate remains current underlines [their]

immense value .. .in an initial examination of urban

social areas" (Ley 1983:74).


Social Area Analysis and Factorial Ecology

Unlike the classical models, social area analysis

and factorial ecology do not rely on the assumption that

distance from the center of the city is a major factor in

residential differences. Instead, these analyses are based

on the idea that residential areas within a city can be

grouped on the grounds of demographic and social

characteristics (Palm 1981).


Social area analysis

Social area analysis as a method of social

differentiation of urban areas was developed by Shevky and

Bell during the early 1950s (Cutter 1985). The analysis

groups areas of like socioeconomic status based on three

constructs: economic status (social rank); family status

(urbanization); and ethnic status (segregation). Using

various criteria for each theme, census tracts are

classified and grouped into social areas (Palm 1981, Ley

1983, Cadwallader 1985, Cutter 1985). Shevky and Bell

(1955), thus, provided a scheme for the analysis of changes

in social areas based on statistical differences between

census tracts. The results of their studies provided













information about what actually existed in the city rather

than preconceived notions derived from earlier descriptive

models.


Criticisms of social area analysis

Much of the criticism of social area analysis hinges

on its theoretical background. The theory espoused by

Shevky and Bell suggests that, since society produces the

city, any understanding of the social forms of the city must

be "within the context of the changing character of the

larger containing society" (Shevky and Bell 1955:3). The

three constructs represent broad characterizations of that

society (Ley 1983).

The theory does little to explain differences and

similarities between residential areas (Cadwallader 1985).

Nor, does it address the understanding of the "process of

residential or social patterning of a city" (Cutter

1985:21). It also does not justify the use of the three

particular constructs (Palm 1981, Cadwallader 1985).

The methodology is described as unsophisticated and

the selection of variables which are used for the constructs

has been questioned. It is also suggested that the

variables do not test the empirical validity of the

constructs (Palm 1981, Cadwallader 1985).













Factorial ecology

As a reaction to the criticisms of social area

analysis, the factorial ecology methodology was developed in

the 1960s (Cutter 1985). This analytical process differed

from earlier types of analyses in the number of variables

used and its greater emphasis on spatial patterns associated

with the variables. Using the statistical technique, factor

analysis, a large number of variables is distilled into

"factors" which describe patterns of correlation among the

data (Palm 1981). The factors are then used to cluster

similar census tracts (Ley 1983). Analysis of geographic

distribution of census tracts attempts to explain patterning

in terms of existing conditions rather than accepting

preconceived model predictions.

Because factorial ecology studies have focused on

predominantly urban residential areas, such studies have

contributed little to urban-rural differentiation. The

approach of wide-ranging empirical analysis, however, is

applicable to rural-urban fringe areas as in the study by

Fesenmaier et al. (1979), in which urbanizing areas were

divided into subzones on the basis of statistical analysis,

shows.













Criticism of factorial ecology

While factorial ecology is widely used and

considered a "highly refined and technically elegant method

of clustering like census tracts" (Palm 1981), it has not

escaped criticism. It has been argued that the technique

fails to identify processes that cause residential

differentiation so that it is of limited use because it only

describes the patterns (Cadwallader 1985). The validity of

the variables, and thus the factors, in discriminating

census patterns has also been questioned (Ley 1983,

Cadwallader 1985). It suggested that the census tract, as

the geographic unit, is too large and too diverse to be of

value (Palm 1981, Cadwallader 1985). Additionally, some

researchers have shown that by using several variations of

factor analysis, different results are obtained for the same

areas (Ley 1983, Cadwallader 1985). None of these

criticisms, however, negate the value of using wide-ranging

empirical studies in describing and differentiating discrete

geographic areas.


Von Thunen's Theory of
Agricultural Land Use

While von Thunen's well-known model is an

agricultural land-use model, and might more appropriately be

discussed in a rural section of the literature review, it is

the basis for the neo-classical urban land-rent models. It













is, therefore, included briefly in this section as a

background for Alonso's classic theory of urban land rent

(Alonso 1971, 1983).

In the early nineteenth century, von Thunen

developed a model of agricultural land use based on his

observations in and around his estate in Germany. He

believed that agricultural land-use patterns were determined

by the value of the land and the crops produced for market

and the distance to that market. Based on a simplifying set

of assumptions including an "isolated" and "uniform" plane

and "economic man," he described the processes that caused

the patterns (Palm 1981). Competition between different

types of land use was controlled by "Economic Rent, defined

. as return from investment in the land" (Sinclair

1967:73). Transportation costs which rose with distance

from the city were important in determining rent. The

further the land was from the city, the more the farmer

would have to invest in transporting his product to market.

Therefore, to receive a reasonable return on his land, the

farmer had to invest in products which would either cost

less to transport or to produce (Sinclair 1967, Palm 1981).


Criticisms of Von Thunen's Theory

While the patterns and processes of von Thunen's

agricultural land-use model may still occur in













lesser-developed countries, the utility of the model in

developed areas is questioned. In such areas, new modes of

transportation, declines in cost of transportation, and the

advent of refrigeration have lessened the effect of

transportation on siting of agricultural production.

Markets have expanded from the single central market to

regional, national, or international markets. Production

techniques favor large-scale agricultural enterprises.

Finally, and probably most important, land used for urban

purposes has become far more valuable than land used for

agriculture. Thus, the competition, especially in rapidly

developing areas, is no longer between different

agricultural uses, but between agricultural and urban uses

(Sinclair 1967).


Alonso's Theory of Urban Land Market

The foundations of the formal spatial analysis
of agricultural rent and location are found in the
work of J. von Thunen, who said, without going into
detail, that the urban land market operated under
the same principles.
--Alonso 1983:1

Based on von Thunen's ideas of economic rent and

land use, Alonso developed a model of urban land use. He

began with a set of assumptions similar to those of von

Thtnen. The physical environment of the urban area is

homogenous so that no area has any particular physical

advantage. There is only one central business district in













the urban area. Transportation is easily available and

costs increase with distances from the urban center. Also,

the land, which is sold for maximum profit, may be developed

in any manner, unencumbered by governmental, environmental,

or zoning restrictions (Dennis and Clout 1980, Palm 1981,

Cadwallader 1985). By using these assumptions, Alonso

calculated bid-rent curves and isolated the bid-rent

function involved in the urban land market (Palm 1981).

"Thus, each plot of land is sold to the highest and best

use: highest in the sense of being the highest bidder, and

best in the sense of being the type of land use that is best

able to take economic advantage of that particular plot"

(Cadwallader 1985:35-36).

One important concept relating to urban land use is

derived from Alonso's model when it is applied to

residential location. THe so-called "distance-decay

function," that is, decrease with distance from the center

of the urban area, should describe both land values and

population density of the urban area (Dennis and Clout

1980).


Criticisms of Alonso's Theory

Alonso's theory has not escaped criticism. Several

of the problems are related to applicability of the

underlying assumptions to urban areas, especially in












developed countries. Few urban areas now have one central

area utilized by all inhabitants (Palm 1981). By assuming a

totally free market and optimum usage of land, the model

fails to address a modern fact of life. Governmental

restrictions often preclude "highest" and "best" usage

(Dennis and Clout 1980). Nor does the model take into

account the involvement of large development and real-estate

corporations which undoubtedly influence the urban land

market (Cadwallader 1985). In addition, as with all models

which assume "economic man," there is the objection that man

is never "all knowing" and rarely acts in the most rational

manner (Palm 1981).

Despite its simplicity, or because of it, as Palm

(1981) suggests, Alonso's model persists. Even some of its

most determined critics, Dennis and Clout, admit that "the

model has proven remarkably, perhaps uncomfortably,

successful in predicting patterns of land use and population

distribution" (1980:102), even though, as Thrall points out,

it does not explain "the underlying forces for behavior of

the system" (1987:9).


The Rural-Urban Fringe

What has become known as the rural-urban fringe has

been central to few urban geographic models and studies.

Emphasis instead has been on the central district (CBD) and












industrial, residential, or commercial areas and on suburban

development and does not include urban expansion into rural

lands and the resulting rural land-use changes. Early

studies of suburban development, which would have been

likely to include rural and agricultural conversion,

probably did not because the development was not far enough

removed form the city to compete with rural land uses.

Within the past two decades, however, the rural-urban fringe

has received more attention in the literature.


Models of Land Use in
the Rural-Urban Fringe

The urbanization of rural lands and the influence of

urban development on nearby rural areas in "high-growth"

areas were discussed by Sinclair in his seminal article "Von

Thunen and Urban Sprawl" (1967). After outlining von

Thunen's model, Sinclair said that while it had been

appropriate in the past and continued to apply to less-

developed areas, it no longer describes processes occurring

in areas of rapid urban expansion. He suggested that there

is still a decline in rent with distance from the urban

area, but that this is not related to the urban market as it

was in von Thunen's model. New factors now influence

patterns of agricultural land use near cities and the most

important of these is what has been called "the anticipation













factor," which is defined as the effects of the perception

of encroaching urban development. He stated that,

As the urbanized area is approached from a distance, the
degree of anticipation of urbanization increases. As
this happens, the ratio of urban to rural land values
increases. Hence, although the absolute value of the
land increases, the relative value for the agricultural
utilization decreases. (1967:78)

Another model describing land use in the rural-urban

fringe was set out by Pryor (1971) (see Figure 3).

Described as a "process-response model," the model shows

relationships between percentage of urban and rural land use

and distance from areas which are 100 percent urban at one

extreme and 100 percent rural at the other. The process

involved is urbanization and the response is land-use

change. Pryor (1971:62) suggested that this model be used

in conjunction with other models to study urban encroachment

into rural areas.


Empirical Studies of
the Rural-Urban Fringe

Urban encroachment, ingress of urban influences to

areas which have been traditionally rural, is a major theme

of empirical studies of the rural-urban fringe. Such

studies focus on land-use change, particularly loss of farm

lands and encroachment of urban land uses (Furuseth and

Pierce 1982, Champion 1983).


























RURAL-URBAN FRINGE
x
Percentage Distance Urban to Rural
3 25 50 75 1C


x Boundary of Totally Urban
y Boundary of Totally Rural


Adapted from Pryor 1971









Figure 3. Model describing land use in the rural-urban
fringe













General loss of farmland

Geographers, using both qualitative and quantitative

analyses, have tried to explain the decline of the

countryside. While specific studies are varied in depth and

focus, a recurring theme is the loss of farmland (Bryant

1976, 1981, Rodd 1976, Troughton 1976, White and Silverwood

1983).

The reasons for loss of farmlands are complex and

numerous and range from economic to political to

environmental (Johnson 1970, Lindeman 1976, Brown and

Roberts 1978, Brown et al. 1981, Healy 1985, Koenig 1985).

The types and importance of factors which cause decline of

the countryside vary from region to region and from country

to country (Noble 1962, Patterson 1968, Bryant and Russwurm

1979, Bryant et al. 1981, Warren and Rump 1981, Crewson and

Reed 1982). In some cases, land-use change results from

expansion of urban land uses into the rural-urban fringe;

however, this is not the only factor.

To examine agricultural land-use change in an area

less subject to urban influences, Crewson and Reed (1982)

studied an area in south-central Ontario which was well away

from large urban areas. Six independent variables including

farm-capitalization, size of farms, occurrence of part-time

farming, the extent of developable shoreline, and the age of

the farm operators were analyzed for a period of 20 years.













The data show the "best predictor" of loss of farmlands,

based on statistical analysis, was the frequency of part-

time farmers. The fact that large-scale farms were not

being managed and operated by full-time farmers appeared, in

this area, to be most indicative of the decline of the rural

farming business. Crewson and Reed (1982:359) conclude that

"(t]he percentage of part-time farmers is increasing

steadily because off-farm income is vital to the maintenance

of the economic viability of farming today." Thus, the loss

of farmland in this particular study area is attributed

ultimately to an economic factor.

Certainly economic factors were important in Hart's

study of rural 'and-use change in the southeastern United

States (Hart 1980). In describing the demise of a major

cash crop--cotton--Hart outlined the evolution of once-

great agricultural holdings in the Piedmont counties of

Georgia and South Carolina. A pronounced change in land use

occurred between 1939 and 1974. During that period, nearly

4-1/2 million acres of productive farmland and 1-1/3 million

acres of cleared land were sold by farmers to nonfarmers

(Hart,1980:492). One reason for the transfers of ownership,

particularly those which involved subdivision for

development, was demonstrated in the answers Hart received

when he asked about the value of land in Carroll County,

Georgia. He was told that "old, worn-out cotton land was












worth about $150 to $200 an acre for forestry. Farmers were

paying $600 to $700 an acre for such lands. Realtors .

[said] that the price of five-acre lots in the northeastern

half of the county--the side toward Atlanta--begin at around

$7,000 ." (Hart 1980:525).

A national study of farmland loss conducted by the

U.S. Department of Agriculture (Zeimetz et al. 1976) found

that, in general, factors other than urbanization accounted

for the majority of cropland loss. In particular, marginal

croplands were converted to pasture and other agricultural

lands were idled as new technology made farming of those

areas uneconomical (Zeimetz et al. 1976:ii).

Plaut (1976) states that many researchers agree that

the direct conversion of agricultural land to urban uses

does not have a significant impact on amount of land devoted

to farming at a national level. Despite this commonly held

belief, it is well to keep in mind Hart's observation (1980)

that land which is fallow may be returned to production at

some time in the future, but that subdivision and

development of rural lands results in irreversible change.

There are indications that such change is occurring in the

rural-urban fringe of high-growth areas.













Encroachment of urban land uses
onto the rural-urban fringe

While direct conversion of rural lands to urban

purposes is considered of little consequence to the national

agricultural production of the United States, such

conversion along with other effects of urbanization may

produce considerable change in land use within the rural-

urban fringe of rapidly developing urban areas (Plaut 1976).

In fact, urbanization is often considered the dominant

process by which change occurs within the rural-urban fringe

(Plaut 1976, Champion 1983, Everitt 1984).

In 1976, Plaut explored the idea that "urbanization

[has] a substantial impact on the loss of farmland on the

rural-urban fringe" (1976:27). Using regression analysis,

he analyzed the changes in land use in Standard Metropolitan

Statistical Areas in the United States. The variables

included in the analysis were number of housing units built

in the county between 1960 and 1970, class of soil

productivity, age of the farmer, and productivity of

farmlands. Based on this analysis, he determined that there

were strong relationships between land-use change and

urbanization in the rural-urban fringe areas of the Midwest

and Northeast (Plaut 1976).

Another author (Pierce 1981) investigated the rate

of conversion of rural land to urban uses within the













rural-urban fringe of Canadian cities. Seven variables,

"population change, dominant economic function, city size,

average residential land values, population density,

geographic region, and agricultural capability of the land"

(Pierce 1981:164), were used. Data, gleaned from various

sources, were subjected to several statistical analyses to

measure both collective and relative impacts of the

variables on urban expansion. Only three variables,

population change, economic function, and agricultural

capability, proved useful. Pierce states that the large

degree of unexplained variation results from the complexity

of the problem and the lack of "more precise measures of

urban form and process and land-use data ."

(1981:171).

Zeimetz et al. (1976) also analyzed rate of

conversion of rural lands in fringe areas. In their study

of 53 rapidly developing counties throughout the United

States, they found that, while there was considerable

variation between areas, an average of 0.173 acres of rural

land was converted for each person increase in population.

They also found that the overall rate of conversion of land

to urban uses in the 53 counties between 1960 and 1970 was

3.4 percent, which they did not consider high (Zeimetz et

al. 1976). However, even though the Department of

Agriculture does not consider the rate of land-use













conversion "high," the results of the conversion are

receiving considerable attention, especially in high-growth

areas.


Land-Use Conversion within the
Rural-Urban Fringe of High-Growth Areas

The Sunday real-estate ads make Fairfax County
sound like one big hunt club. .But,
increasingly, chrome and glass office towers sprout
from northern Virginia woods.
--Morris 1987:1

In high-growth areas across the country, more and

more attention is focused on the movement of urban land uses

and population from the urban area into the rural-urban

fringe. Newspapers and magazine articles describe and

lament the passing of the countryside and planners,

politicians, businessmen, and "just ordinary" people discuss

the positive and negative affects of the changes. Some

suggest that their quality of life is being damaged (Morris

1987), while others see great business opportunities

(Leinberger 1987).

A major contributor to the movement of population

and business into the fringe areas has been the growth of

the service and information industry (Brotchie et al. 1985,

Institute of Traffic Engineers 1985, Leinberger 1987, Morris

1987). This sector of the economy does not require a

central city location and businesses are free to move to

cheaper, more attractive locations away from the urban area.












As the jobs relocate, so do the employees. In some areas,

the relocations of these businesses have produced "suburban

megacenters" which rival cities in employment and size. The

Coastal Corridor in West Los Angeles with 40 million square

feet of office space and 186,000 daytime employees and City

Post Oak near Houston with 3.3 million square feet of retail

and 16 million square feet of office space employing 60,000

people are but two examples (Institute of Traffic Engineers

1985). In other cases, whole new "urban villages," low-

density housing surrounding a central core of businesses,

appear in the midst of previously rural land (Long 1987).

Near St. Louis, Chesterfield Village grew out of a cow

pasture and Fair Lakes, south of Washington, D.C., appeared

on fallow farmland (Leinberger 1987).


Seminole County as a
High-Growth Area

Similar types of urban expansion are occurring in

Seminole County, Florida. A recent Department of

Transportation study of satellite data showed that the

county had lost 21.63 percent of its agricultural land

between 1973 and 1984. This loss in Seminole County was the

fifth greatest percentage loss among the 67 counties in the

state (Jean 1987).

An average of 1,000 persons per month move into the

county. Most of these are white-collar workers with













relatively high incomes. In fact, the median family income,

$20,873, was the highest in the state in 1980 (Kemp 1985).

Most of the new construction is in smaller

developments located generally in the southern part of the

county. Two larger "urban villages," however, are in the

first phases of growth. Earlier this year, 1987, South

Seminole Corporation paid $12 million for a 783-acre tract

of long-idle rural land in south central Seminole County.

The area, Alafaya, will contain 3,835 homes and 65 acres of

office and retail space (Snyder 1984).

The second urban village, Heathrow, adjacent to

Interstate-4 in the northwest quadrant of the county, covers

1,248 rural acres. In addition to 4,000 houses, the

development will have a shopping center and several hundred

thousand square feet of office space (Snyder 1984). This

development has already attracted the national headquarters

of the American Automobile Association and others are

expected to follow.


Conclusion

There exists at present no satisfactory definition

of either rural or urban. In the United States, the

definitions set out by the Bureau of the Census are most

frequently used, but other countries define rural and urban

by their own standards so that definitions are rarely












compatible. Since data are collected based on the various

census definitions, it is difficult to make cross-cultural

comparison of the data. Even within the United States, the

census definitions and data are often not adequate,

especially for studies at the local level where finer

distinctions are required. Without adequate definitions of

urban and rural, a definition of the rural-urban fringe is

difficult, although several have been advanced.

Various models and analyses have contributed to the

understanding of the characteristics of urban, rural, or

fringe areas. None of the models, however, address the

problems of urban and rural differentiation.

Empirical studies of the rural-urban fringe

concentrate on loss of farmlands and encroachment of urban

land uses. While these changes seem to have little effect

on land use at a national level, they receive considerable

attention at the local level.

As urban land uses and population move into the

countryside in rapidly developing areas, change becomes more

evident. Depending on the point of view of the observer,

the changes may appear positive or negative. They may also

seem subtle or dramatic. In other words, the amount and

direction of change depends oftentimes on one's perception

and on whether or not one will benefit or lose as a result

of the change.












Attempts to measure change at the local level are

often stymied by lack of definition, data, and technique.

Census definitions are vague. Census data based on those

definitions are not available in the format necessary for

detailed local planning. For example, while detailed data

in census block form are available in urbanized areas, only

census tract data, which encompass a much larger areal unit

of measurement, exist for nonurban areas. Thus, if

comparisons are to be made using census data, only the

larger census tract material can be used. Technique depends

on time, money, data, and knowledge available to the

investigation. Local planning efforts often suffer as the

result of these limitations.

Planning staffs in rapidly growing Seminole County

have attempted to overcome data discrepancies by using

Regional Planning Council (RPC) data which are divided into

traffic zone units instead of census tracts or blocks. The

present study of urban, rural, and rural-urban fringe in

Seminole County will also use RPC traffic zone data, both in

original form and with modifications.
















CHAPTER III
METHODOLOGY


The review of literature in Chapter II shows that

current definitions of urban, rural, and rural-urban fringe

are inadequate and many of the models and analyses upon

which current research is based do not address the

fundamental issue of distinguishing characteristics of rural

and urban. Yet economic, political, and administrative

decisions often depend on whether areas are "defined" as

rural or urban.

At present, decisions, particularly in high-growth

areas such-as Seminole County, are often made on the basis

of a regional data set which may or may not reflect

characteristics of rural and urban. This study examines,

through various statistical analyses, the utility of one

such data set in differentiating urban and rural populations

and areas.

The data set selected for study is generated by the

East Central Florida Regional Planning Council (1984).

Instead of the more widely used census tract, the geographic

base for the data set is the traffic zone, a unit which was

originally set up for transportation planning.













Nevertheless, these data are the basis for all regional,

county, and virtually all municipal planning in Seminole

County and therefore become the basis for subsequent

definitions of urban, rural,and the rural-urban fringe.


Traffic Zones as a
Standard Areal Measurement

A city is first divided into subareas, using
spatial units such as blocks, census tracts, or
traffic zones.
--Cadwallader 1985:2

Decision-making at the local level requires some

basis for division of the area, city, county, or region into

urban or rural contingents. In Central Florida the traffic

zone has been chosen as the standard unit of areal

measurement.


History of Traffic Zones

Although traffic zones did not come into common

usage as geographic units for transportation studies until

the early 1960s, they were first used in the 1916 Chicago

Transit Study, which analyzed home-to-work ridership. They

were also used in an origin-destination study in 1947-48

called the McGuire Report for the Boston Area. Then, in the

early 1950s, transportation studies in Detroit and Chicago

brought both traffic zones and computer usage to national

attention (Roger Creighton 1987, Roger Creighton Associates,

consulting engineers, Delmar, NY, personal interview).













The recent evolution of planning in the United

States as it applies to federal funding of transportation

projects corresponds roughly with the application of

advanced computer technology, an increased awareness of the

need for more precise urban and rural socioeconomic data for

modeling transportation, land use, and housing, and a

greater demand by private citizens for involvement in

governmental decisions. In the early 1960s, the Federal

Highway Administration began developing alternative models

for transportation planning. During the period traffic

zones (TZs) came into general use as an areal measurement.

The impetus for the growth of transportation

planning was the Federal-Aid Highway Act of 1962. The Act

required that after July 1, 1965, all federally aided

highway projects in metropolitan areas with populations over

50,000 be based on transportation modeling. A major

requirement of the Act was that "the Secretary [of

Transportation] shall not approve any program .

unless he finds that such projects are based on a continuing

comprehensive transportation planning process carried on

cooperatively by states and local communities .

(Morehouse 1969:160). This "Three C" (cooperative,

comprehensive, and continuing) process endures today and is

the basis for the establishment of Florida's Metropolitan

Planning Organizations (MPOs).













One of the major goals of the MPOs was to

demonstrate the transportation needs of their regions to

both the state and federal transportation agencies.1

Justification for new or improved roads was based on a

priority system, which was shown by development and use of

transportation models. The models projected, usually for a

20-year time period, average daily traffic and volume

capacity ratio, that is, the number of vehicles using the

road and the number of vehicles for which the road was

designed.

One of the problems of transportation modeling

identified early on was a need for accurate, consistent

data. As early as 1961, data requirements were articulated

in a joint policy statement by the American Institute of

Planners and the Institute of Traffic Engineers. The

organizations agreed that planning responsibilities included

collection of all land use and socioeconomic data on a zone-

by-zone basis (Joint Policy Statement of the American

Institute of Planners and the Institute of Traffic Engineers

1961:70). In this 1961 report, however, the term "zone" was

not defined.





-Roads considered were federal, state, and county.
Municipal roads which were not part of those systems were
not modeled and were maintained by local funding.













The U.S. Census provided much of the data for the

transportation planning models, but a number of problems

came to light. For example, Census data are collected only

every 10 years, but transportation plans are based on 5-

year intervals and required updating annually. The models

also required very detailed information on small geographic

areas. Such data were not available in the appropriate

format or within an appropriate time frame from the Census

data.

One solution to the problem of standardizing data

for traffic models and revising the data routinely was the

use of traffic zones (TZs). While traffic zones had been

used on a routine basis in some areas, it was not until 1977

that the Federal Highway Administration outlined the

criteria for standardizing the zones in areas with

populations of 50,000 or greater:

The transportation analysis units are known as
zones. These zones vary in size depending on density or
nature of urban development. In the central business
district (CBD), zones may be as small as a single block
and in the undeveloped area they may be as large as 10
or more square miles. An area with a million people
might have 600 to 800 zones and an area of 200,000
people might have 150 to 200 zones. These zones attempt
to bound homogeneous urban activities; that is, a zone
may be all residential, all commercial, all industrial,
etc. Zones also should consider natural boundaries and
census designations.
An important consideration in establishing zones is
their compatibility with the transportation network to
be used. As a general rule, the network should form the
boundaries of the zones (U.S. Federal Highway
Administration 1977:2-3)












Since county participation was required if federal and state

transportation funds were to be allocated, directions were

given for creating TZs for both "developed land [and]

the undeveloped land that the urban area will encompass in

the next 20 to 30 years" (U.S. Federal Highway

Administration 1977:2-2).

As early as 1963, the East Central Florida Regional

Planning Council staff converted all census tract data into

traffic zones. The conversion of data was based on

allocation of Census data to smaller areas and while traffic

zones could be made up of block data, more often it

corresponded with road networks and not neighborhoods.

These data were based on collective county/city policy, but

did not change the state population figures. Thus,

socioeconomic data from the 1960 Census were converted into

TZs, which became the standard geographic base. These data,

initially, applied only to the Urban Transportation Planning

Process (UTPS) (Heaton 1987).


Use of Traffic Zones in
Seminole County

While traffic zones were developed initially for

federal and state transportation planning, they have been

adapted for use in comprehensive planning in Seminole County

(see Table 2 and Figure 4). They are used instead of census

tracts as a geographic base because
















Table 2
Sources of Comprehensive Planning Data
for Cities in Seminole County, Florida


Transportation Density
City Zones Census Other Measurement


Oviedo Yes No No No

Lake Mary Yes No No No

Maitland No No Yes No

Longwood Yes Yes No No

Sanford Yes No No No

Altamonte
Springs No Yes No No

Winter
Springs Yes Yes No Yes


Source: Cohen 1987, personal interview; Delk 1987, personal
interview; Koch 1987, personal interview; Marder
1987, personal interview; Nagle 1987, personal
interview; Weaver 1987, personal interview; Wells
1987, personal interview.










65








I
















^yr




r 8'



4-
n 3



0









0
\^Ni4 t o
t rr
















. i-. (-


\ n













1. Census tracts are generally too large to use

for detailed data analysis, especially in

the unincorporated areas (see Figure 5), and

2. The Census is based on a decennial count and

detailed information becomes available only

several years after each enumeration. The

TZ data, by contrast, is completed and

reviewed every five years and has a 20-year

planning horizon (Price 1987)

While traffic zones are smaller units than census

tracts and some of the TZ data are derived from census

materials, aggregations of TZs do not correspond necessarily

with census tracts (see Figures 4 and 5). This is because

of a difference in philosophy between the U.S. Census Bureau

and the Federal and State Departments of Transportation.

Census tracts, blocks, and enumeration districts do not

split neighborhoods and have a primary function of grouping

like areas. On the other hand, transportation data are

based primarily on street networks. The splitting of

neighborhoods is a common feature of traffic zones in

Seminole County (Price 1987).

Another common feature of the TZs in Seminole County

is that they are not based on density, even though the

Federal Highway Administration Study (1977) defining traffic

zones suggests that density be considered (see Table 2). In










67


































iC^ i ( ', E E m
t\ Lu


DcD










,"4












7 c0
Zrt
\ 1.--


































C144
C) "; *4







/Y, ~ ~ ~ P ^ ^ l^^s^>
f~~ ~~ ^^s^2^^^
/-Jo ^^s cs~ne
--*^\j '-^ p _0iK?0 ^r15'*a
's'^) *~ "I^ XiXSiS~tL 1-




i u3 P u c c
s; 04 !
iF01
i *r1
~ij~ 2













fact, according to regional, county, and city planners, no

calculations of area in various traffic zones in Seminole

County have ever been made (Delk 1987, personal interview;

Gilbrook 1987, personal interview; Grovdahl 1987, personal

interview; Heaton 1987, personal interview; Marder 1987,

personal interview; Nagle 1987, personal interview; Price

1987, personal interview; Ross 1987, personal interview;

Thompson 1987, personal interview; Weaver 1987, personal

interview; Wells 1987, personal interview).

There will be one exception in the future. The

planner in Winter Springs, one of the seven cities in the

county, intends to use Census data and density figures in

the city's Comprehensive Plan Update. The Winter Springs

Planning Department, which in 1987 is just beginning to

receive detailed 1980 Census data, plans to use block data

cross-referenced with Seminole County Traffic Zone data. It

also intends to calculate densities for population, housing,

and employment all to be used in future planning (Koch

1987).


Use of the Traffic Zone
in the Present Study

The traffic zone was chosen as the areal unit in

this study because it is the unit used most often by

planning agencies in Seminole County. In addition, it is

the unit on which the socioeconomic variables generated by













the RPC and used by the county to describe urban and rural

areas is based.

Despite the obvious disparity in traffic zone sizes

in the county (see Figure 4), neither area nor density data

have been calculated by the planning agencies. In the past,

comparisons of socioeconomic data have been based solely on

absolute data values. These values comprise the first major

data set of the study and are called the planning data.

In order to standardize comparison of traffic zones,

each of the 181 TZs in the research area has been

planimetered and the area calculated. Using these areas,

the planning data are converted to a second major data set

called density data (see Appendix).

For planning purposes in Seminole County,

incorporated areas are considered urban while the

unincorporated areas are designated rural. For this reason,

each of the major data sets is divided into two subsets:

1. Incorporated traffic zones which lie either

totally or partially within the incorporated

city limits of Altamonte Springs,

Casselberry, Winter Springs, Longwood, Lake

Mary, and Sanford (see Figure 6), and

2. Unincorporated TZs which correspond to the

rural portions of the county





































































































I--






-J
Z



ar













For each of the traffic zones a centroid has been

estimated, which is used to calculate the distance to a

common point located at State Road 436 and Interstate 4 in

the major urban center of Altamonte Springs. This area was

chosen as the urban node because it is the economic and

transportation focal point for Seminole County and is

adjacent to Orange County and in close proximity to the City

of Orlando (see Figure 6).

Of the 181 traffic zones in Seminole County, 175

zones were used in this research. Six zones were deleted

because population data were recorded as zero and they would

have produced questionable analysis results.2


Definitions of the Variables

The variables used in the present study include

(1) population, (2) single-family housing, (3) multi-family

housing, (4) resident employment, (5) attendant employment,

(6) retail employment, (7) median family income, and

(8) persons per household. The data for the first

seven of these variables were obtained from the






20f the traffic zones which were omitted, three--82,
85, and 160--were agricultural or vacant land in 1980. The
other three--42, 124, and 137--were totally industrial
retail or commercial retail areas. These traffic zones are
small and scattered throughout Seminole County.













Orange-Seminole-Osceola Statistical Data, 1980-20053 (East

Central Florida Regional Planning Council 1984). Persons

per household was calculated by the author because it is

commonly used for planning purposes.

The variables are defined by the East Central

Florida Regional Planning Council (1984:vi-x) as

1. Population is defined as the total number of

civilian and military individuals whose

principal residence is in a particular

traffic zone. Excluded from these figures

are seasonal and transient residents.

Population allocations to traffic zones are

based primarily on 1980 U.S. Census data and

the total figures are allocated by Regional

Planning Council, County and City

governmental staff.

2. Single-family housing is defined as the

total number of completed single-family

dwellings and mobile homes, whether they are

occupied or vacant. Not included in the



3Two variables listed in the document, hotel/motel
units and school enrollment, grades 1-12, were not used in
this research. Hotel/motel units was excluded because only
20 TZs had more than one unit. While 39 TZs had values for
school enrollment, this variable would only indicate where
schools are since student population is assigned to the
location of the school and not the home.













count are seasonal or migratory mobile-home

units.

3. Multi-family housing includes completed,

occupied, or vacant units where two or more

units occur in a single structure. Multi-

family housing does not, however, include

units which are considered group quarters.

4. Resident employment counts full- and part-

time employed individuals by place of

residence. If a person holds more than one

job, he/she is counted only once.

5. Attendant employment counts full- and part-

time employed persons by place of work. In

this case, if an individual holds more than

one job, he/she is counted at each place of

employment.

6. Retail employment is a subset of attendant

employment and counts only those individuals

employed in retail trade. A person is

considered employed in retail activities if

his employer has a two-digit Standard

Industrial Classification between 52 and 59

(inclusive).

7. Median family income describes the income

level in each traffic zone for which half












the families in a particular area have

incomes below the median and half the

families have incomes above the median.

The data for the preceding variables have been

compiled by the East Central Florida Regional Planning

Council and represent the most comprehensive computation

available to the planning offices in Central Florida. As a

result, these are the data used in the area from day to day

for planning, policy, and land-development decisions.


The Roles of Distance and Density

The concept of the "distance-decay function" is

derived from Alonso's theory of urban land market (Dennis

and Clout 1980). This concept was applied to the rural-

urban fringe in Pryor's model (Pryor 1971) and is the basis

for using the variable "distance from the node" in the

present study. Pryor's model (see page 47 of this study)

shows the relationship between percentage of urban and rural

land use and population characteristics and distance from

areas which are 100 percent urban at one extreme and

100 percent rural at the other.


Regression Analysis

The statistical method of least-squares regression

is employed to describe the relationships between distance

from the node and each socioeconomic variable in the study













(Sincich 1982). For each variable, six regressions are run,

regressing the socioeconomic variable against the distance

from the traffic zone nodes to the urban node at the

intersection of State Road 436 and Interstate 4. These six

regression analyses include (a) combined planning data,

(b) incorporated planning data, (c) unincorporated planning

data, (d) combined density data, (e) incorporated density

data, and (f) unincorporated density data.

Two scattergrams are plotted for each variable. The

first describes the combined planning data and the second

shows the combined density data. On each, the "best fit"

regression lines for the incorporated and unincorporated

subsets are plotted.

It is assumed throughout that the characteristics of

the urban node are 100 percent urban. It is also assumed

that at some unspecified distance from the urban node there

exists an area which is totally rural. Each of the

variables analyzed represents an "urban"characteristic which

will be at its peak at a city center Orlando for Orange

County and perhaps Altamonte Springs in Seminole County at

the county urban node. As the regression line for a

variable's incorporated data increases in distance from the

urban node, the TZs become less urban in terms of that

particular characteristic. By the same token, the

regression line for the variable's unincorporated data













should indicate increasingly urbanized characteristics as

one approaches the urban node. Thus, the intersection of

the two regression lines on each graph represents the

juxtaposition of the characteristics of urban and of rural

traffic zones, or the rural-urban fringe, for the variable

exhibited in the graph.

Then, as a final step, the distance from the

intersection of the regression lines to the urban node has

been calculated for both planning and density data and the

two distances compared. The data are represented in charts

and graphs which illustrate the similarities and differences

in "urban" and "rural" as they apply to zones at various

distances from the urban center of Seminole County.


F-Values

The F-values were calculated to test whether or not

the regression analysis was useful in predicting y. The

formula used is that devised by Sincich in his text

(1982:467)



F =R 2/k
(1 R2)/[n (k + 1)]


where













R2 = multiple coefficient of determination

n = number of observations

k = number of B parameters in the model

(excluding B0)


Z-Score Statistic

The Z-score statistic was employed to determine

whether the incorporated and unincorporated populations are

statistically similar or dissimilar. The formula for

comparing the means of the two populations is derived from a

study by Walker and Lev (1958:233)


(XI X2 (P P2)
1 2 ^1 -- -- 2-
2 2
1 + s2
/ N^ N2
1 N2


where

p = population means

X = mean

s = sample standard deviation

N = sample size


Summary

The terms urban, rural, and rural-urban fringe have

never been adequately defined, yet developmental and

planning decisions must be based on these concepts. Local

governments often set their own criteria for differentiating













such areas. In Seminole County, the bases for

distinguishing urban from rural are the incorporation

boundaries and the characteristics described in the data set

referred to in this study as the planning data set.

The analyses to follow are intended to determine the

viability of the characteristics in (1) determining urban

and rural and (2) distinguishing the rural-urban fringe.

Toward these ends, the data, in original form (and after

modification to account for density), are subjected to

several statistical examinations.
















CHAPTER IV
ANALYSIS


The Census data are set out in such a way that they

seem difficult, and often inappropriate, for local decision-

making. For this reason, smaller governmental units, such

as cities and counties often bypass census data and choose

alternative data sets which seem more appropriate in areal

unit size, collection interval, and detail. Such is the

case in Seminole County, where rapid growth requires

continual monitoring and re-evaluation of land use.

The data set chosen by the county and most of the

city governments is produced by the East Central Florida

Regional Planning Council and based on traffic zones. These

data are in general use for daily governmental and private

planning decisions and, while the effectiveness of the data

in differentiating urban, rural, and rural-urban fringe

areas is assumed, it has not been proved. The present

analysis seeks to test the validity of this assumption.


Analysis and Data Sets

The analysis presented in this chapter uses the

statistical technique, regression analysis, to describe and













compare two major data sets. These sets are called the

combined data in the analysis.

The first set, planning data, is the one in general

use in the county. It consists simply of total counts for

each traffic zone.

The second data set, density data, was calculated by

the author. Because the area of each traffic zone had not

been previously determined, density figures for traffic zone

variables have not been available to local governments.

These data, however, would be useful for planning purposes

because they better reflect the distribution of population

and population characteristics than do the planning data.

Each of the major, or combined, data sets is

subdivided into incorporated and unincorporated data sets.

Thus, a total of six data sets is used in the analysis.


Presentation of Findings

The results of the analysis are presented as a

series of table and graphs. Relationships between each

variable and distance are described in two ways:

1. Tabular--A table lists analysis results of

planning and density data within

incorporated, unincorporated, and combined

traffic zones, and













2. Graphical--Two graphs in the form of

scattergrams are presented for each

variable. The first is based on planning

data, while the second is based on density

data.


Population--Distance Relationships

The statistical findings in Table 3 describe the

relationships between population and distance to the urban

node for each of the six traffic zone data sets. Several of

these are of particular interest.

The R2 values suggest little systematic association

between traffic zone population and distance from the node

in any data set. It is clear, however, that by adjusting

the planning data for traffic zone size--that is, converting

the planning data to density data--higher values for R2 are

achieved.

The slope of the regression line is negative, as

expected, indicating that the greater the distance from the

node, the smaller the population. This relationships exists

for all six data sets, but it is more pronounced in the

three density data sets (see Table 3 and Figures 7 and 8).

The ranges shown in the planning data results

represent the differences between the highest and lowest

absolute traffic zone populations, while the ranges within





















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SEMNOLE COUNTY


0 40 0 120 160 200


Dstancs to Ide (tenfts of ma)
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Incorporated Unincorporated Incorporated


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the density results show the differences between the highest

and lowest population density figures. Thus, ranges for

absolute population in incorporated and unincorporated

populations for the traffic zones are 3,923 and 4,681,

respectively. The population density, however, has a range

of 5,923 persons per square mile for incorporated traffic

zones and 4,984 persons per square mile for unincorporated

traffic zones.

Although the distribution is scattered, the expected

intersection of the urban and rural planning data regression

lines indeed takes place at 11.84 miles from the node (see

Table 3 and Figure 7). When the data are adjusted to

reflect density, the intersection of the regression lines

moves outward to 15.59 miles from the node (see Table 3 and

Figure 8). The approximately 30 percent difference between

the two intersections could make a difference in

governmental and private planning decisions. The planning

data suggest a break between rural and urban at 11.84 miles

from the node. Since these are the data used to make

governmental decisions, this would typically be where

governmental services abate. The density data, however,

suggest that development has advanced beyond the 11.84-mile

limit, as far as 15.59 miles. Therefore, the outermost

development may not receive essential services.













There are several factors which could influence

population values in both planning and density data sets.

Large portions of the county are protected from development

by federal, state, and county environmental regulations.

Most developable areas of the county are serviced by at

least one major transportation artery. These roads include

Interstate 4, U.S. 17-92, S.R. 436, S.R. 434, S.R. 419,

C.R. 46, and Lake Mary Boulevard (see Figure 9).

Furthermore, the influence of Orange County and Orlando to

the south should not be discounted. Seminole County has

been historically a "bedroom community" (Osinski 1985)and

provided residential housing for Orange County while

employment opportunities are more prevalent in Orange

County. Thus, the traffic zones in the southwest and south

central part of the county are more densely populated than

the rest of Seminole County.


Single-Family Housing--Distance Relationships

Based on R2 there appears to be only a weak

relationship between single-family housing and distances to

the node. The planning R2 values are .009 for the

incorporated areas and .150 for unincorporated areas of the

county. These values are raised only slightly to .079 and

.209, respectively, when the planning data are adjusted for

density (see Table 4).












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Full Text
30
cross-cultural comparisons of urban and rural data are
difficult at best. It is also evident that none of the
combinations of criteria, even the relatively complex Dutch
system, is adequate for differentiating urban, rural, and
rural-urban fringe at the local level.
Rural-Urban Definitions
The most recent U.S. Census definition (1980) (see
Chapter I, pp. 8-9, of this study) of the rural-urban
fringe, also known as the "urban fringe" or the "rurban
fringe" (Champion 1983:30), differs only slightly from the
earliest academic descriptions. In 1937, T. L. Smith
described the rural-urban fringe as "the built-up area just
outside the corporate limits of the city" (Pryor 1971:59).
In an article entitled "Urban-Rural Fringe" written
in 1942, Wehrwein outlined the inevitable growth which must
occur when there is an absence of land-use control within
the zone of transition which lies between areas of well-
recognized urban development and lands devoted to
agriculture. In his summary, Wehrwein predicted that the
availability of transportation, cheap land, lower taxes, and
fewer land-use controls in rural areas would become the
incentives for industrial relocation from the city to these
transition areas (Wehrwein 1942).


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128
Department of Environmental Regulation, and the various
Water Management Districts. These lands may be restricted
permanently from development and, therefore, must be
considered rural.
A regional analysis of urban service areas, or those
areas where utilities and capital improvements exist, or are
planned, should pinpoint the rural-urban fringe. These
areas possess the potential for rapid urbanization. This
information is included in county and city comprehensive
planning documents which are required by the State of
Florida. Again, there is a problem with accuracy because
developers may create their own urban setting. Even though
an area does not have, or is not projected to have, urban
services, such as water, sewage, and other utilities, the
developer may provide these at his own expense.
While none of the variables mentioned would
singularly define urban or rural, these data could be
combined with the density data to produce an index. Such an
index might better distinguish rural, urban, and fringe
areas.
With more diagnostic variables, methods of analyses
other than those employed in this study may become
appropriate. For example, factor analysis could be used to
determine which variables are more characteristic of urban,
rural, or rural-urban fringe. Further distinctions could


154
Zone
Square Mile
51
$4,458.61
52
S4.223.95
53
S34.893.48
54
S25.226.47
55
S27.667.74
56
S35.737.50
57
S21,442.50
59
S16.817.65
60
SI,802.44
61
S7,307.21
62
S4.246.60
63
SI,615.74
68
S886.57
69
S8.070.33
70
S7.878.17
71
SI,657.18
72
S21,120.21
73
S14,180.71
74
S24,210.98
75
S8.272.08
76
Sll,153.37
77
S12,105.49
78
S3,129.12
83
SI9,138.61
84
S26.999.11
86
S13.215.00
87
S9,524.32
88
S15.547.06
89
S30.205.71
90
S20,330.77
91
S30,205.71
92
S68,880.00
93
S33,329.03
94
S19,869.23
95
S22.460.87
96
S5.691.15
97
S36,992.50


73
count are seasonal or migratory mobile-home
units.
3. Multi-family housing includes completed,
occupied, or vacant units where two or more
units occur in a single structure. Multi
family housing does not, however, include
units which are considered group guarters.
4. Resident employment counts full- and part-
time employed individuals by place of
residence. If a person holds more than one
job, he/she is counted only once.
5. Attendant employment counts full- and part-
time employed persons by place of work. In
this case, if an individual holds more than
one job, he/she is counted at each place of
employment.
6. Retail employment is a subset of attendant
employment and counts only those individuals
employed in retail trade. A person is
considered employed in retail activities if
his employer has a two-digit Standard
Industrial Classification between 52 and 59
(inclusive).
7. Median family income describes the income
level in each traffic zone for which half


92
controlling traffic zone data for area, no such distinction
may be made anywhere in the country for single-family
housing.
Multi-Family HousingDistance Relationships
All traffic zones which contain population
statistics were employed regardless of the number of multi
family units. Even zones with zero values were included
because the absence of multi-family housing is as important
as its presence. In Central Florida multi-family housing is
o
generally found in urban high-growth areas. The R values
for all six multi-family data sets are low (see Table 5).
The highest value, .106, occurs in these density data for
incorporated traffic zones. The R2 values for multi-family
housing for unincorporated areas do not show a strong
relationship with distance to the node.
The regression lines for planning data cross at
13.65 miles from the node (see Figure 12). The density data
regression lines cross at 10.75 miles (see Figure 13). In
both graphs (Figures 12 and 13), few multi-family housing
units occur beyond the intersection of the incorporated and
unincorporated regression lines. Based on the assumption
that the intersection of these two regression lines
represents the difference between rural and urban, multi
family housing is a predominantly urban characteristic.


77
R2 =
= multiple coefficient of determination
n =
= number of observations
k =
= number of B parameters in the model
(excluding Bq)
Z-Score Statistic
The Z-score statistic was employed to determine
whether the incorporated and unincorporated populations are
statistically similar or dissimilar. The formula for
comparing the means of the two populations is derived from a
study by Walker
and Lev (1958:233)
z =
(Xj *2, (Hj h2)
/ 2 2
/S1 + S 2
y n2
where
=
population means
X =
mean
s =
sample standard deviation
N =
sample size
Summary
The terms urban, rural, and rural-urban fringe have
never been adequately defined, yet developmental and
planning decisions must be based on these concepts. Local
governments often set their own criteria for differentiating


162
Osinski, T.
1985 County Role: A Bedroom Community. The_0rlando
Sentinel. The Little Sentinel, Seminole County
(February 24 ) : 1 11.
Pacione, M., ed.
1983 Progress in Rural Geography. Totowa, NJ: Barnes &
Noble Books.
Palm, R.
1981 The Geography of American Cities. New York:
Oxford University Press.
Park, R. E., E. W. Burgess, and R. D. McKenzie
1925 The City. Chicago: University of Chicago Press.
Patterson, H. L.
1968 Ontario's Disappearing Agricultural Land.
Agricultural Institute Review 23:7-10.
Pierce, J. T.
1981 Conversion of Rural Land to Urban: A Canadian
Profile. Professional Geographer 33(2):153-173.
Plaut, T.
1976 The Effects of Urbanization on the Loss of Farmland
at the Rural-Urban Fringe: A National and Reg_iona 1
Perspective. RSRI Discussion Paper Series: No. 94.
Philadelphia: Regional Sciences Research Institute.
Pryor, R. J.
1971 Defining the Rural-Urban Fringe. In Internal
Structure of the City: Readings on Space and
Environment. L. S. Bourne, ed. Pp. 59-68. New York:
Oxford University Press.
Rodehaver, M. W.
19 4 6 The Rural-Urban Fringe: An Interstitial Area.
Ph.D. Dissertation. Department of Geography, University
of Wisconsin.
Rodd, R. S.
1976 The Crisis of Agricultural Land in the Ontario
Countryside. Plan Canada 16:160-170.
Sayer, A.
1984 Defining the Urban. GeoJournal 9(3):279-285.


7
requirement for central city designation had been abandoned.
Instead, a minimum population of 50,000 for the entire
urbanized areas was substituted (U.S. Bureau of the Census
1982) .
The Urban Fringe
The second element of an urbanized area is the urban
fringe which lies without, but contiguous to, the central
city or cities. The following criteria define those areas
included in the urban fringe:
1. Incorporated places with a population of
2,500 or more
2. Incorporated places with a population of
less than 2,500 if the area has at least 100
dwelling units and a density of 500 or more
units per square mile which is equivalent to
a density of 2,000 persons per square mile
(in 1980 this requirement was dropped to
1,000 persons per square mile)
3. Unincorporated areas with a density of 500
dwelling units per square mile
4. Commercial, recreational, industrial, and
other functionally related areas


53
conversion "high," the results of the conversion are
receiving considerable attention, especially in high-growth
areas.
Land-Use Conversion within the
Rural-Urban Fringe of High-Growth Areas
The Sunday real-estate ads make Fairfax County
sound like one big hunt club. . But,
increasingly, chrome and glass office towers sprout
from northern Virginia woods.
Morris 1987:1
In high-growth areas across the country, more and
more attention is focused on the movement of urban land uses
and population from the urban area into the rural-urban
fringe. Newspapers and magazine articles describe and
lament the passing of the countryside and planners,
politicians, businessmen, and "just ordinary" people discuss
the positive and negative affects of the changes. Some
suggest that their quality of life is being damaged (Morris
1987), while others see great business opportunities
(Leinberger 1987).
A major contributor to the movement of population
and business into the fringe areas has been the growth of
the service and information industry (Brotchie et al. 1985,
Institute of Traffic Engineers 1985, Leinberger 1987, Morris
1987). This sector of the economy does not require a
central city location and businesses are free to move to
cheaper, more attractive locations away from the urban area.


97
that one of the traffic zones has an average of greater than
16 persons per household (see Table 6).
The mean persons per household, however, does rise
slightly from 2.53 in incorporated traffic zones to 2.84 in
unincorporated zones. Also, the regression lines intersect
within the county at 20.43 miles from the urban node (see
Figure 14).
Resident Emp1oyment--Distanee Relationships
The relationship between resident employment, or
where those who are employed live, and distance to the urban
node is described in Table 7. All R^ values are low.
O
However, the highest R values occur in the data which have
been adjusted to reflect density.
The planning data regression lines intersect at
11.28 miles from the urban node (see Table 7 and Figure 15).
The intersection of the density data occurs at 15.45 miles
(see Table 7 and Figure 16). Thus, the density data
intersection is 4.17 miles farther from the urban node than
the planning data intersection.
The value of using resident employment as an
indicator of rural or urban is questionable at best because
the variable simply measures the number of employed people
within each traffic zone. Since there is no indication of
type of employment, for example, agricultural, industrial,


37
continues and the debate remains current underlines [their]
immense value ... in an initial examination of urban
social areas" (Ley 1983:74).
Social Area Analysis and Factorial Ecology
Unlike the classical models, social area analysis
and factorial ecology do not rely on the assumption that
distance from the center of the city is a major factor in
residential differences. Instead, these analyses are based
on the idea that residential areas within a city can be
grouped on the grounds of demographic and social
characteristics (Palm 1981).
Social area analysis
Social area analysis as a method of social
differentiation of urban areas was developed by Shevky and
Bell during the early 1950s (Cutter 1985). The analysis
groups areas of like socioeconomic status based on three
constructs: economic status (social rank); family status
(urbanization); and ethnic status (segregation). Using
various criteria for each theme, census tracts are
classified and grouped into social areas (Palm 1981, Ley
1983, Cadwallader 1985, Cutter 1985). Shevky and Bell
(1955), thus, provided a scheme for the analysis of changes
in social areas based on statistical differences between
census tracts. The results of their studies provided


34
Cadwallader 1985). The fifth zone probably corresponds with
what has been called the rural-urban fringe, although
Burgess did not explicitly refer to it.
Sector model
In 1939, approximately 10 years after Burgess
published his work on the morphology of the city, Hoyt
provided fresh insights into the patterning of residential
land use. He postulated that residential land uses "tend to
be arranged in wedges or sectors radiating from the center
of the city along the lines of transportation" (Murphy
1966:211). These sectors were divisible and Hoyt elaborated
on both their physical composition and evolution. He stated
that the gradient or outward progression of residential
properties moved "downward" from high-rent2 areas to less
affluent sectors. The "low"-rent areas occupy different
sectors which may occur in a variety of urban areas (Hoyt
1939, Palm 1981, Jordan and Rowntree 1982, Light 1983).
The dynamics of the sector concept are associated
with high-rent areas. According to Hoyt, high-price areas
exert an influence on the direction of residential growth
O
*-Rent is defined as monies paid in the form of
purchase or lease for occupying space (Jordan and Rowntree
1982) .


15
urbanization. Agricultural employment and rural residence,
according to Census criteria, are dropping. Total
population and urban residence, again according to Census
criteria, are rising rapidly and population density is among
the highest in the state.
Historically, the county has been predominantly
agricultural, producing truck crops, such as celery,1
cabbage, and watercress, and the agricultural sector has
provided the major employment. In recent decades, however,
the percentage of agricultural employment has dropped
dramatically. In 1940, 3,290 individuals, or 36 percent, of
the total labor force of 9,134 were employed in agriculture
(U.S. Bureau of the Census 1942). By 1980, less than 2
percent, or 1,622, of the 82,316 employed individuals in the
county worked in the agricultural sector (U.S. Bureau of the
Census 1982).
Rural residence, based on the Census criteria for
rural, has also decreased sharply. Between 1970 and 1980,
rural residence dropped from 31,709 to 15,578 within the
county. This represents a -50.9 percent change within one
decade. By contrast, urban residence has risen from 51,983
in 1970 to 164,174 in 1980, representing a 215.8 percent
^The nickname of the county seat, Sanford, is still
Celery City even though celery is no longer grown in the
county.


20
must be, and are, explored in the present study of an area
experiencing phenomenal growth.


160
Hoyt, H.
1939 The Structure and Growth of Residential
Neighborhoods in American Cities. Washington, DC :
Federal Housing Administration.
Institute of Traffic Engineers
1985 The Suburban Office Boom: Implications for
Metropolitan Mobility. Paper distributed at the
National Conference on Site Development and
Transportation Impacts. Orlando, Florida. Pp. 17-112.
Jean, C.
1987 Growth Grabs More Land from Agriculture. The
Orlando Sentinel (September 22):B1,B5.
Johnson, 0. E. G.
1970 A Note on the Economics of Fragmentation. Nigerian
Journal of Economic and Social Studies 12:175-184.
Johnston, R. J.
1986 Places and Votes: The Role of Location in the
Creation of Political Attitudes. Urban Geography
7(2):103-117.
Joint Policy Statement of the American Institute of Planners
and the Institute of Traffic Engineers
1961 Professional Responsibility of City Planners and
Traffic Engineers in Urban Transportation. Journal of
the American Inst itut e of PJanners 27:70-73.
Jordan, T. G., and L. Rowntree
1982 The Human Mosaic: A Thematic Introduction to
Cultural Geography. New York: Harper & Row.
Kemp, L.
1985 The Boom Goes On and On. The _0rjlando^Sentinel .
The Little Sentinel, Seminole County (February 28}:1,3.
Koenig, J.
1985 Where Do Our Citrus Growers Go from Here? Florida
Trend (June):60-66.
Lake, R. W., ed.
1983 Readings in Urban Analysis: Perspectives on Urban
Form and Structure. New Brunswick, NJ: Center for
Urban Policy Research.


6
and unincorporated places outside of the urban fringe with
populations of 2,500 or more. Since the territories
described in the latter two categories are not legally
defined, the Bureau of the Census set up boundaries prior to
enumeration (U.S. Bureau of the Census 1952). These
boundaries were based on the concepts of "places,"
"urbanized areas," and "urban fringe" described in the
Census.
Places are concentrations "of population regardless
of legally prescribed limits, powers, or functions" (U.S.
Bureau of the Census 1962:xiv). Two types of places,
incorporated and unincorporated, are recognized by the
Bureau of the Census. Places are considered urban only when
their population meets or exceeds the minimum limit of 2,500
(U.S. Bureau of the Census 1952, 1962, 1972, 1982).
An urbanized area (UA) consists of one or more
central city or cities and the urban fringe. The central
city continues to be defined as the largest city in the
area, but exact population requirements for a central city
have changed over time. In 1950, the largest city was
required to have a population of 50,000 or more for central
city designation. The second- and third-largest cities
could also be central cities if their populations were one-
third that of the largest city and at least 25,000 (U.S.
Bureau of the Census 1952). By 1980, the minimum population


40
Criticism of factorial ecology
While factorial ecology is widely used and
considered a "highly refined and technically elegant method
of clustering like census tracts" (Palm 1981), it has not
escaped criticism. It has been argued that the technique
fails to identify processes that cause residential
differentiation so that it is of limited use because it only
describes the patterns (Cadwallader 1985). The validity of
the variables, and thus the factors, in discriminating
census patterns has also been questioned (Ley 1983,
Cadwallader 1985). It suggested that the census tract, as
the geographic unit, is too large and too diverse to be of
value (Palm 1981, Cadwallader 1985). Additionally, some
researchers have shown that by using several variations of
factor analysis, different results are obtained for the same
areas (Ley 1983, Cadwallader 1985). None of these
criticisms, however, negate the value of using wide-ranging
empirical studies in describing and differentiating discrete
geographic areas.
Von Thnen1s Theory of
Agricultural Land Use
While von Thnen's well-known model is an
agricultural land-use model, and might more appropriately be
discussed in a rural section of the literature review, it is
the basis for the neo-classical urban land-rent models. It


74
the families in a particular area have
incomes below the median and half the
families have incomes above the median.
The data for the preceding variables have been
compiled by the East Central Florida Regional Planning
Council and represent the most comprehensive computation
available to the planning offices in Central Florida. As a
result, these are the data used in the area from day to day
for planning, policy, and land-development decisions.
The Roles of Distance and Density
The concept of the "distance-decay function" is
derived from Alonso's theory of urban land market (Dennis
and Clout 1980). This concept was applied to the rural-
urban fringe in Pryor's model (Pryor 1971) and is the basis
for using the variable "distance from the node" in the
present study. Pryor's model (see page 47 of this study)
shows the relationship between percentage of urban and rural
land use and population characteristics and distance from
areas which are 100 percent urban at one extreme and
100 percent rural at the other.
Regression Analysis
The statistical method of least-squares regression
is employed to describe the relationships between distance
from the node and each socioeconomic variable in the study


164
U.S. Bureau of the Census
195 2 Census of Population, Volume_II 1_950 .
Washington,DC: United States Government Printing
Office.
1962 Census of Population, Volume I, 1960. Washington,
DC: United States Government Printing Office.
1972 1970 Census of Population. Detailed
Characteristics, Florida. Washington, DC: United
States Government Printing Office.
198 2 1980 Census of Population Volume I, Part II.
Washington, DC: United States Government Printing
Office.
U.S. Federal Highway Administration
1977 An Introduction to Urban Travel Demand Forecasting:
A Self-Instructional Text. N.p.: U.S. Department of
Transportation.
Walker, H. M., and J. Lev
1958 Elementary Statistical Methods. New York: Holt,
Rinehart, and Winston.
Wander, H.
1975 Basic Data Needed for the Study of Urbanization:
An Examination of Data on the Urban Population in the
Censuses of Selected Countries. In Basic Data Needed
for the Study of Urbanization. S. Goldstein and D. Sly,
eds. Pp. 33-69. Dolhain, Belgium: Ordina Editions.
Warren, C. L., and P. C. Rump
1981 The Urbanization of Rural Land in Canada 1966-1971
and 1971-1976. Ottawa: Environment Canada, Lands
Directorate.
Wehrwein, G. S.
1942 The Rural-Urban Fringe. Economic Geography 18
(July):217-228.
White, A., and M. Silverwood
1983 Farming on the Urban Fringe. Town and Country
Planning 52:113-114, 150-151.


33
The Three Classical Models of Urban Form
The three classical models of urban formconcentric
zone, sector, and multiple nucleiwere developed in
response to the desire to understand the type and direction
of urban growth (Light 1983). While all three were based on
the ecological theory, each presents a different description
of city form (Jordan and Rowntree 1982, Light 1983).
Concentric-zone model
Burgess (1925), University of Chicago sociologist,
advanced the concept of concentric zones for urban
development. His theory suggested that urban land use and
growth could be described in terms of five concentric, and
internally homogeneous, zones. At the center of his model
is the central business district, the core of the city.
Surrounding the central business district is the area he
termed the "zone of transition." The urban characteristics
of this area include a mixture of land uses and diversity of
residential areas, often in a state of deterioration. The
third zone consists largely of "blue-collar" homes. The
fourth zone is another residential area catering mainly to
"white-collar" workers and middle-class families. The
outermost zone, the commuter zone, lies outside the
corporate boundary and contains higher-income residential
areas (Palm 1981, Jordan and Rowntree 1982, Light 1983,


REFERENCES
Agnew, J. A., J. Mercer, and D. E, Sopher, eds.
1984 The City In Cultural Context. Boston: Allen &
Unwin.
Alonso, W.
1971 A Theory of the Urban Land Market. In Internal
Structure of the City: Readings on Space and
Environment. L. S. Bourne, ed. Pp. 154-159. New York:
Oxford University Press.
1983 A Theory of the Urban Land Market. In Readings in
Urban Analysis. Perspectives on Urban Form and
Structure. R. W. Lake, ed. Pp. 1-10. New Brunswick,
NJ: Center for Urban Policy Research.
Borchert, J. G.
1984 The Dutch Settlement System. In Urbanization and
Settlement Systems: International Perspectives. L. S.
Bourne, R. Sinclair, and K. Dziewonski, eds. Pp. 200-
225. New York: Oxford University Press.
Bose, A.
1975 Basic Data Needed for the Study of Urbanization: A
Case Study of the Indian Census. In Basic Data Needed
for the Study of Urbanization. S. Goldstein and D. Sly,
eds. Pp. 71-100. Dohain, Belgium: Ordina Editions.
Bourne, L. S., ed.
1971 Internal Structure of the City: Readings on Space
and Environment. New York: Oxford University Press.
Bourne, L. S., and J. W. Simmons, eds.
1978 Systems of Cities. New York: Oxford University
Press.
Bourne, L. S., R. Sinclair, and K. Dziewonski, eds.
1984 Urbanization and Settlement Systems: Internationa1
Perspectives. New York: Oxford University Press.
157


CHAPTER II
LITERATURE REVIEW
The urban-rural boundary becomes so blurred that
the dichotomy . becomes arbitrary and
essentially meaningless. No one has been able to
demarcate the boundary of a city in a consistent
fashion.
--Bourne and Simmons 1978:22
[Yet, while] [a]bstract social theory can . .
abstract from the contingencies of spatial form,
. . research on concrete effects must take them
into account.
Sayer 1984:282
The urban-rural boundary has not been, and may never
be, demarcated in a manner which is satisfactory for many
types of urban and rural research. While the Bureau of the
Census definitions and criteria are used for much of the
urban and rural research conducted in the United States,
these designations are not adequate for local research and
planning. They are also unacceptable for studies in other
countries which depend on their own census definitions of
urban and rural.
Despite the fact that there is no universally
accepted differentiation of rural and urban, many
disciplines, including geography, sociology, planning, and
anthropology, have developed subfields of study based on an
urban-rural dichotomy. Each subfield has its own
21


75
(Sincich 1982). For each variable, six regressions are run,
regressing the socioeconomic variable against the distance
from the traffic zone nodes to the urban node at the
intersection of State Road 436 and Interstate 4. These six
regression analyses include (a) combined planning data,
(b) incorporated planning data, (c) unincorporated planning
data, (d) combined density data, (e) incorporated density
data, and (f) unincorporated density data.
Two scattergrams are plotted for each variable. The
first describes the combined planning data and the second
shows the combined density data. On each, the "best fit"
regression lines for the incorporated and unincorporated
subsets are plotted.
It is assumed throughout that the characteristics of
the urban node are 100 percent urban. It is also assumed
that at some unspecified distance from the urban node there
exists an area which is totally rural. Each of the
variables analyzed represents an "urban"characteristic which
will be at its peak at a city center Orlando for Orange
County and perhaps Altamonte Springs in Seminole County at
the county urban node. As the regression line for a
variable's incorporated data increases in distance from the
urban node, the TZs become less urban in terms of that
particular characteristic. By the same token, the
regression line for the variable's unincorporated data


CHAPTER V
SUMMARY AND CONCLUSIONS
Many of the most critical problems which mankind
will have to face and solve between now and the end
of the twentieth century are related ... to the
particular pattern of settlement and increasing rate
of growth and concentration in areas regarded as
"urban." Yet, despite the importance of
urbanization and population redistribution they
remain the demographic (and geographic) phenomena
about which the least is known.
--Goldstein and Sly 1975:7
The research described in this study was undertaken
in order to develop a clearer understanding of urban and
rural characteristics and their relationship with distance
from the urban node in high-growth areas. Distance
relationships are virtually ignored in the most commonly
used urban, rural, and rural-urban fringe definitions and
data sources, including those of the U.S. Census. These
relationships, however, are the basis for much of the
theoretical and applied work in urban and rural geography,
planning, sociology, and anthropology.
To test the reliability and significance of the
distance-decay function of certain variables in determining
the urban, rural, and fringe areas of a high-growth county,
several statistical procedures were applied to the variables
and data commonly used in Seminole County, Florida. It is
117


ai
Ion
51
52
53
54
55
56
57
59
60
61
62
63
68
69
70
71
72
73
74
75
76
77
78
83
84
86
87
88
89
90
91
92
93
94
95
96
97
149
Resident
Attendant
Employment/
Attendant
Employment/
Square Mile
Employment
Square Mile Income
102.22
284
78.89
516,051.00
5.00
501
131.84
516,051.00
1550.00
124
269.57
516,051.00
350.00
391
575.00
517,154.00
520.97
47
75.81
S17,154.00
395.83
137
285.42
517,154.00
695.00
70
87.50
S17,154.00
181.37
15
14.71
517,154.00
27.22
139
15.44
516,222.00
29.73
80
36.04
516,222.00
52.62
1388
363.35
516,222.00
7.27
92
9.16
SI6,222.00
29.88
89
4.48
517,625.00
136.99
150
60.98
519,853.00
145.24
164
65.08
519,853.00
13.27
47
3.92
519,853.00
2.13
1
1.06
S19,853.00
178.57
178
127.14
519,853.00
9.76
27
32.93
S19,853.00
154.58
515
214.58
519,853.00
97.75
304
170.79
S19,853.00
15.24
0
0.00
SI9,853.00
31.49
14
2.10
S20,865.00
612.66
140
88.61
530,239.00
76.79
101
90.18
S30.239.00
24.38
25
15.63
521,144.00
29.28
4
1.80
521,144.00
91.18
7
5.15
521,144.00
208.57
7
10.00
S21,144.00
487.50
25
24.04
S21,144.00
1551.43
209
298.57
521,144.00
1786.67
64
213.33
520,664.00
12.90
164
264.52
S20,664.00
367.31
1161
1116.35
S20,664.00
388.04
164
178.26
S20,664.OO
385.77
253
97.31
514,797.00
1777.50
58
145.00
514,797.00


Table 7
Resident Employment and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
. 082
. 225
. 062
.215
. 157
. 195
Intercept
(Constant)
556
1,016
530
1,086
671
621
Slope
-2.22
-6.53
-1.95
-6.97
-3.20
-3.96
F-value
15.47
51.13
9.25
38.39
5.96
7.76
Range
1,703
2,308
1,340
2,307
1,703
2,039
Average (Mean)
402
566
403
634
397
282
Value of
Intersection


11.28 miles
15.45 miles
11.28 miles
15.45 miles
100


86
There are several factors which could influence
population values in both planning and density data sets.
Large portions of the county are protected from development
by federal, state, and county environmental regulations.
Most developable areas of the county are serviced by at
least one major transportation artery. These roads include
Interstate 4, U.S. 17-92, S.R. 436, S.R. 434, S.R. 419,
C.R. 46, and Lake Mary Boulevard (see Figure 9).
Furthermore, the influence of Orange County and Orlando to
the south should not be discounted. Seminole County has
been historically a "bedroom community" (Osinski 1985)and
provided residential housing for Orange County while
employment opportunities are more prevalent in Orange
County. Thus, the traffic zones in the southwest and south
central part of the county are more densely populated than
the rest of Seminole County.
Single-Family Housing--Distance Relationships
O
Based on R there appears to be only a weak
relationship between single-family housing and distances to
the node. The planning R2 values are .009 for the
incorporated areas and .150 for unincorporated areas of the
county. These values are raised only slightly to .079 and
.209, respectively, when the planning data are adjusted for
density (see Table 4).


2
terms precisely. Definitions become particularly difficult
within regions which have been subjected to rapid urban
development with their residential, commercial, and office-
complex growth. Within these rapid-growth regions, the
distinctions among urban, rural, and fringe areas may be
obscure and assessments are often based on inadequate
information.
The terms urban and rural have wide and diverse
meanings both geographically and culturally. It is not
difficult, therefore, to understand that defining these
terms is among the most problematic area of any rural-urban
fringe study. In order to determine where rural and urban
areas interface to form the rural-urban fringe, it is
clearly necessary to know what constitutes a rural area and
an urban area. As Fesenmaier et al. (1979:255-256) point
out, "There seems^to be little prospect of a more adequate
definition of the 'limits of the rural-urban fringe since the
question simply begs the far greater one of defining urban
and rural."
A better knowledge and, ultimately, the definitions
of urban, rural, and rural-urban fringe require the
differentiation of characteristics, or gradations of
characteristics, which are urban or rural. The
identification, precise description, and quantification of
these characteristics, or variables, is essential, not only


96
Calculations using only planning datathose data presently
available to Central Florida agenciesplace the urban
fringe for this characteristic almost three miles farther
from the urban node than the density data would indicate.
It is interesting to note that within that almost-three-mile
band (10.75-13.65 miles from the urban node) there are a
number of multi-family units (see Figures 12 and 13). Based
on currently available information, this may indicate that
the developers are building within what is perceived as the
rural-urban fringe.
Persons per Household--Distance Relationships
The relationships between persons per household and
distance to the node is shown in the planning data results
in Table 6. While density data were calculated and
subjected to regression analysis, these data and the
analysis were discarded subsequently as not valid. The use
of density per square mile is an attempt to "normalize" the
data. In the case of this particular variable, however, the
data, persons per household, already reflect a type of
density measurement, but not an areal one. By trying to
combine two types of density measurement, the analysis
produces meaningless results. The illogicality of the
statistic may be seen in the range value which indicates


118
important to note that the variables used do not necessarily
represent the best socioeconomic variables for the analysis.
They, and the planning data which were used, however, are
those which are used consistently by local governmental
planners and residential, commercial, and industrial
developers in Seminole County to make developmental
decisions.
The basic planning data consist of absolute values
of the variables for the traffic zone (TZ), the unit of
areal measurement used in the co\mty. Since TZs vary in
size, the planning data set was adjusted to standardize the
information producing a second major data set called density
data. Both sets were subdivided into urban and rural
segments.
Summary of Findings
The analysis of the three planning data sets
suggested many homogeneous characteristics within the
county. The similarities in absolute numbers may be, in
part, the result of the unequal size of traffic zones. The
intent of the subdivision of the county, however, was not to
produce TZs with like population characteristics. It was
mainly to divide the county on the basis of roadway networks
(Heaton 1987).


101
SEMINOLE COUNTY

I
Incorpora ted
Distanc to Modi (tinttis of mill)
0 X
Unincorporated Incorporated
V
I
Unincorporated
Figure 15. Regression lines for incorporated and
unincorporated resident employment planning data


Table 3
Population and Distance from Node
Combined TZ Incorporated TZ Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
. 079
.224
. 059
.212
. 163
. 207
Intercept
(Constant)
1,414
2,538
1,338
2,706
1,776
1,601
Slope
-5.70
-16.23
-4.93
-17.26
-8.63
-10.17
F-value
15.80
56.0
8.80
37.85
6.24
8.38
Range
4,681
5,922
3,464
5,923
4,581
4,984
Average (Mean)
1,021
1,419
1,017
1,585
1,038
732
Value of
Intersection
11
.84 miles
15.59 miles
11.84 miles
15.59 miles


Page
Population--Distance
Relationships 81
Single-Family Housing--
Distance Relationships 86
Multi-Family Housing
Distance Relationships 92
Persons per Household--
Distance Relationships 96
Resident Employment--Distance
Relationships 97
Attendant Employment--Distance
Relationships 103
Retail Employment--Distance
Relationships 103
IncomeDistance Relationships 107
Conclusions 112
V SUMMARY AND CONCLUSIONS 117
Summary of Findings 118
Conclusion 124
Future Studies of the Rural-
Urban Fringe 126
APPENDIX: SOCIOECONOMIC DATA1980 132
REFERENCES 157
SUPPLEMENTAL BIBLIOGRAPHY 166
BIOGRAPHICAL SKETCH 172
vi i


141
Density
Single
Single Family
Multi-
Traffic
Population/
Family
Housing/
Family
Zone
Area
Housing
Square Mile
Housing
145
970.00
268
382.86
56
146
816.67
188
313.33
13
147
1740.00
344
688.00
41
148
2493.18
390
886.36
37
149
3438.10
887
1055.95
69
150
75.00
22
21.15
8
151
1120.00
88
440.00
0
152
881.58
211
277.63
12
153
1960.71
348
621.43
13
154
2920.24
726
864.29
8
155
3486.49
766
1035.14
176
156
96.43
23
27.38
4
157
1284.69
416
424.49
O
158
1913.10
523
622.62
0
166
2323.33
618
686.67
23
167
1786.00
257
514.00
44
168
3940.91
892
1013.64
167
169
2350.00
233
364.06
312
170
1583.61
526
431.15
174
171
1530.00
220
440.00
120
172
5923.91
705
1532.61
200
173
4576.47
0
0.00
939
174
5500.00
338
1536.36
120
175
2191.84
640
653.06
O
176
1366.00
215
430.00
0
177
706.67
2
6.67
72
178
137.65
75
44.12
2
179
1470.24
27
32.14
415


19
areas of the county which are incorporated are simply
considered urban and those which are unincorporated are
considered rural, but these simple designations of urban and
rural are unacceptable. Even the greatly criticized Census
designations no longer depend solely on incorporation
boundaries to distinguish urban from rural.
Thirdly, areas defined as urban, rural, and rural-
urban fringe as a result of this study are mapped and
compared with areas which have been designated similarly by
the Census. Based on these comparisons, recommendations for
criteria which may more accurately depict urban, rural, and
rural-urban fringe areas are enumerated.
It may be argued that the conversion of rural lands
to urban has little to do initially with population data.
Thus, a single calculation of population change, especially
without determining which characteristics represent urban
and which represent rural, does little to explain, or
accurately describe, rural-to-urban conversion either from a
geographic or planning perspective. Yet, the most widely
accepted and used definition of urban, and, therefore,
rural-urban fringe and rural, in the United States is based
largely on the single characteristic of population. As a
result, any studies of urban expansion, rural conversion, or
rural-urban fringe development in an area rely almost
entirely on population change. Alternative characteristics


153
Zone
Square Mile
10
$15,278.68
11
312,670.12
12
$9,445.00
13
$18,552.68
14
$23,612.50
15
$21,203.06
16
$21,644.79
17
S13,855.00
18
$23,091.67
19
$44,084.09
20
$11,410.00
21
$13,659.86
22
S9,602.48
23
$9,602.48
24
$13,395.61
25
$34,706.82
26
$25,065.52
27
$9,662.24
28
$34,564.29
29
$18,611.54
30
$10,229.88
31
$15,827.36
32
$14,716.67
33
$9,868.82
34
$6,710.80
35
$3,812.35
36
$9,530.88
37
$11,174.14
38
$47,727.27
39
$29,166.67
40
$36,790.00
41
$7,358.00
43
$11,496.88
44
$8,202.43
48
$10,369.29
49
S34,906.00
50
S6.233.21


48
General loss of farmland
Geographers, using both qualitative and quantitative
analyses, have tried to explain the decline of the
countryside. While specific studies are varied in depth and
focus, a recurring theme is the loss of farmland (Bryant
1976, 1981, Rodd 1976, Troughton 1976, White and Silverwood
1983) .
The reasons for loss of farmlands are complex and
numerous and range from economic to political to
environmental (Johnson 1970, Lindeman 1976, Brown and
Roberts 1978, Brown et al. 1981, Healy 1985, Koenig 1985).
The types and importance of factors which cause decline of
the countryside vary from region to region and from country
to country (Noble 1962, Patterson 1968, Bryant and Russwurm
1979, Bryant et al. 1981, Warren and Rump 1981, Crewson and
Reed 1982). In some cases, land-use change results from
expansion of urban land uses into the rural-urban fringe;
however, this is not the only factor.
To examine agricultural land-use change in an area
less subject to urban influences, Crewson and Reed (1982)
studied an area in south-central Ontario which was well away
from large urban areas. Six independent variables including
farm-capitalization, size of farms, occurrence of part-time
farming, the extent of developable shoreline, and the age of
the farm operators were analyzed for a period of 20 years.


43
the urban area. Transportation is easily available and
costs increase with distances from the urban center. Also,
the land, which is sold for maximum profit, may be developed
in any manner, unencumbered by governmental, environmental,
or zoning restrictions (Dennis and Clout 1980, Palm 1981,
Cadwallader 1985). By using these assumptions, Alonso
calculated bid-rent curves and isolated the bid-rent
function involved in the urban land market (Palm 1981).
"Thus, each plot of land is sold to the highest and best
use: highest in the sense of being the highest bidder, and
best in the sense of being the type of land use that is best
able to take economic advantage of that particular plot"
(Cadwallader 1985:35-36).
One important concept relating to urban land use is
derived from Alonso's model when it is applied to
residential location. THe so-called "distance-decay
function," that is, decrease with distance from the center
of the urban area, should describe both land values and
population density of the urban area (Dennis and Clout
1980).
Criticisms of Alonso's Theory
Alonso's theory has not escaped criticism. Several
of the problems are related to applicability of the
underlying assumptions to urban areas, especially in


SUPPLEMENTAL BIBLIOGRAPHY
Amedeo, D., and R. G. Golledge
1975 An Introduction to Scjentific Reasoning in
Geography. New York: Wiley.
Bergman, T.
1970 Land Consolidation in Germany. In Change in
Agriculture. A. H. Bunting, ed. Pp. 481-485. London:
Duckworth.
Berry, B. J. L.
1971 Internal Structure of the City. In Internal
Structure of the City. L. Bourne, ed. Pp. 97-103. New
York: Oxford University Press.
Best, R.
1984 Are We Losing the Land? Town and Country Planning
53(1) : 10-11.
Bosselman, F., and D. Callies
1971 The Quiet Revolution in Land-Use Control.
Washington, DC: U.S. Government Printing Office.
Bourne, L. S.
1976 Urban Structure and Land-Use Decisions. Annals of
the Association of American Geographers 66:531-547.
Bunting, A. H., ed.
1970 Change in Agriculture. London: Duckworth.
Cal1ies, D. L.
1980 The Quiet Revolution Revisited. Journal of the
American Planning Association 46:135.
Carlson, E.
1987a Florida Bound. The Wall Street Journal (April
21) : 41 .
1987b New England Offers the Jobs: What It Lacks Is Job
Seekers. The Wall Street Journal (April 21):41.
166


167
Cassetti, E.
1975 Spatial Equilibrium Distribution of Agricultural
Production and Land Values. Economic Geography 48:193-
198 .
Champion, T., M. Coombs, and S. Openshaw
1983A New Definition of Cities. Town and Country
Planning 52(11):305-308.
Chicoine, D. L.
1981 Farmland Values at the Urban Fringe: An Analysis
of Sales Prices. Land Economics 57:354-362.
Cook, T., and P. Falchi
1979 Regression Analysis and Geographic Models: Comment
Number 1. The Canadian Geographer 23(1):71-74.
Coughlin. R. E.
1979 Agricultural Land in the Urban-Rural Fringe. RSRI
Discussion Paper Series: No. 111. Philadelphia:
Regional Science Research Institute.
Cowan, R.
1983 What's Happening to Our Town? Town and Country
Planning 52(1):6-8.
Dxibbink, D.
1984 I'll Have My Town Medium-Rare, Please. Journal of
the American Planning Asosciation 50(5) -.419-433.
Dunford, R. W., C. E. Marti, and R. C. Mittelhammer
1985 A Case Study of Rural Land Prices at the Urban
Fringe Including Subjective Buyer Expectations. Land
Economics 61:10-16.
Elson, M.
1982 Farmland Loss and the Erosion of Planning. Town
and Country Planning 50(1) :20-21.
1986 Who Calls the Tune on the Green Belt? Town and
Country Planning 55(7-8) :203-204 .
Gakenheimer, R., and M. Meyers
1979 Urban Transportation Planning in Transition: The
Source and Prospects of T8M. Journal of the American
Planning Association 45(1):28-35.


99
SEMINOLE COUNTY
ti
c
r


3
O
X
k
I
a
t
c
o
f
l
I
Wstonc b Kodi (tinttis of mk)
0 X
I I
Incorporated Unincorporated Incorporated Unincorporated
Figure 14. Regression lines for incorporated and
unincorporated persons-per-household planning
data


124
intersections for the remaining variables are much higher
(see Table 13).
In both the planning data and density data, the
values of the incorporated and unincorporated intersection
of the different variables have great diversity. The
planning data intersections range from -16.56 to 33.05 miles
from the urban node and, within the density data, the range
is from -64.38 to 15.59 miles from the node. Since the
intersection of the regression lines represents the division
between urban and rural characteristics of the variable, a
rural-urban fringe for that particular variable would occur
at or near the intersection. Because of the wide variation
in intersection distance, however, it is difficult to
pinpoint an area which might be considered the rural-urban
fringe based on the combination of planning or density data
variables.
Conclusion
This study has not provided new definitions of urban
and rural. It has not narrowed the identification of
characteristics, or the degrees of a single characteristic,
which may be attributed to urban or rural. It has, however,
shown through statistical analysis that the variables and
data set chosen by many Central Florida planning agencies as
alternatives to those of the Census are wholly inadequate in


76
should Indicate increasingly urbanized characteristics as
one approaches the urban node. Thus, the intersection of
the two regression lines on each graph represents the
juxtaposition of the characteristics of urban and of rural
traffic zones, or the rural-urban fringe, for the variable
exhibited in the graph.
Then, as a final step, the distance from the
intersection of the regression lines to the urban node has
been calculated for both planning and density data and the
two distances compared. The data are represented in charts
and graphs which illustrate the similarities and differences
in "urban" and "rural" as they apply to zones at various
distances from the urban center of Seminole County.
F-Values
The F-values were calculated to test whether or not
the regression analysis was useful in predicting y. The
formula used is that devised by Sincich in his text
( 1982:467)
F
2
R /k
(1 R2)/[n (k + 1)]
where


Table 11
Comparison of Means of Density Populations
Incorporated
Variable TZs
Population 1,585
Single-Family Housing 411
Multi-Family Housing 232
Resident Employment 634
Attendant Employment 455
Retail Employment 115
$31,213
Unincorporated Significance
TZs Z-value Level (%)
732
-3,68
99
231
-2.56
99
20
-4.53
99
282
-3.80
99
9 7
-5.70
99
26
-3.75
99
$14,189
-5.55
99
Income
115


CHAPTER IV
ANALYSIS
The Census data are set out in such a way that they
seem difficult, and often inappropriate, for local decision
making. For this reason, smaller governmental units, such
as cities and counties often bypass census data and choose
alternative data sets which seem more appropriate in areal
unit size, collection interval, and detail. Such is the
case in Seminole County, where rapid growth requires
continual monitoring and re-evaluation of land use.
The data set chosen by the county and most of the
city governments is produced by the East Central Florida
Regional Planning Council and based on traffic zones. These
data are in general use for daily governmental and private
planning decisions and, while the effectiveness of the data
in differentiating urban, rural, and rural-urban fringe
areas is assumed, it has not been proved. The present
analysis seeks to test the validity of this assumption.
Analysis and Data Sets
The analysis presented in this chapter uses the
statistical technique, regression analysis, to describe and
79


TABLE OF CONTENTS
Page
ACKNOWLEDGMENTS iii
LIST OF TABLES viii
LIST OF FIGURES ix
ABSTRACT xi
CHAPTER
I INTRODUCTION 1
Review of Census Definitions of
Urban, Urban Fringe, and Rural 4
The Urban Fringe ^
The Extended City 8
Rural Areas 9
Problem Statement and Purpose of
Present Research 11
Purpose of Research 12
Study Area 12
Intent of the Research 18
II LITERATURE REVIEW 21
Urban and Rural Definitions 22
United States Definitions 24
International Definitions 25
Rural-Urban Definitions 30
Urban Form and Land Use: Models
and Analyses 32
The Three Classical Models of
Urban Form 33
Concentric-zone model 33
Sector model 34
Multiple-nuclei model 35
Criticisms of the classical
models 36
v


Traf
Zon
98
99
100
101
102
103
105
111
112
113
114
115
116
117
118
119
120
123
125
126
127
128
129
130
131
132
133
134
135
136
138
139
140
141
142
143
144
140
Density
Single
Single Family
Multi
jpulotion/
Family
Housing/
F ami 1
Area
Housing
Square Mile
Housi:
914.71
216
317.65
8
3741.67
122
1016.67
100
2942.31
514
988.46
7
2938.89
191
1061.11
12
3575.00
921
1151.25
15
1522.37
763
501.97
23
1133.85
480
369.23
60
452.70
331
149.10
7
696.94
186
189.80
100
4011.36
15
34.09
1036
461.54
10
19.23
165
3680.95
660
785.71
472
4257.41
760
1407.41
83
4206.25
0
0.00
1012
3738.10
405
964.29
402
2436.36
34 6
786.36
6
5073.81
355
845.24
615
4755.56
18
100.00
448
705.88
199
292.65
0
2978.13
435
1359.38
0
1971.05
498
655.26
40
2731.03
172
296.55
666
2727.27
35
159.09
307
2078.57
3
21.43
165
4310.71
0
0.00
744
2408.00
268
536.00
89
5200.00
637
1676.32
46
2478.57
452
1076.19
0
4547.62
87
207.14
664
70.29
10
2.94
164
350.00
0
0.00
55
2757.69
674
864.lO
35
3150.00
600
857.14
349
3075.00
14
70.00
323
1527.68
481
429.46
46
2856.25
244
762.50
2
458.00
92
184.00
18


54
As the jobs relocate, so do the employees. In some areas,
the relocations of these businesses have produced "suburban
megacenters" which rival cities in employment and size. The
Coastal Corridor in West Los Angeles with 40 million square
feet of office space and 186,000 daytime employees and City
Post Oak near Houston with 3.3 million square feet of retail
and 16 million square feet of office space employing 60,000
people are but two examples (Institute of Traffic Engineers
1985). In other cases, whole new "urban villages," low-
density housing surrounding a central core of businesses,
appear in the midst of previously rural land (Long 1987).
Near St. Louis, Chesterfield Village grew out of a cow
pasture and Fair Lakes, south of Washington, D.C., appeared
on fallow farmland (Leinberger 1987).
Seminole County as a
High-Growth Area
Similar types of urban expansion are occurring in
Seminole County, Florida. A recent Department of
Transportation study of satellite data showed that the
county had lost 21.63 percent of its agricultural land
between 1973 and 1984. This loss in Seminole County was the
fifth greatest percentage loss among the 67 counties in the
state (Jean 1987).
An average of 1,000 persons per month move into the
county. Most of these are white-collar workers with


3
to academicians studying urban areas, but also to planners
and policy-makers who are involved in urban growth and rural
management.
In historical terms, areas designated as rural or
urban have been treated as opposites with few, if any,
characteristics in common. The reason for the urban or
rural designation may be as arbitrary as the placement of an
incorporation line. In such instances, the incorporation
boundary is analogous to the wall of a medieval "walled
city." The area not within the "wall" was not considered
part of the city even when construction and population moved
beyond the wall. It was not until the wall was moved to
encompass the newly built-up area that the rights and
protection of the city dwellers were conferred on that area.
In the United States, incorporation boundaries,
population, and, to a lesser extent, population density and
economic development, have been the major factors used by
the Bureau of the Census to define urban. A review of the
various definitions used by the Census since the turn of the
century illustrates the emphasis placed on these few factors
in the designation of urban, rural, and fringe areas. The
Census criteria are particularly important because
". . most people follow the lead of the Bureau of the
Census which defines certain types of areas as urban"
(Murphy 1966:1).


127
The most readily available data are the average
daily traffic counts which are collected annually and on an
"as-needed" basis for federal, state, and county roadways.
Records of these counts may be obtained from either the
District Department of Transportation or the County Public
Works Department. An historical analysis of these data
would show increase or decrease in road usage. These data
combined with land use change may help pinpoint those areas
which can, or will, become urban.
Property conversion ratios, or the number of times a
property has sold within a specified time period, may or may
not give a true indication of urban, rural, or fringe areas.
In urban and, particularly fringe, areas the property
ownership would be expected to change more frequently than
in rural areas. These data, however, may be misleading if a
larger percentage of the property in the area is slated for
future development or is considered long-term investment by
its present owners. Despite these problems, property
conversion ratios may be extracted easily from the county
tax appraisers' records and should be considered, if only as
supplementary information.
The percentage of developable land in an area may
influence the rural or urban determination of the area.
Much of the wetland in Central Florida is under the
jurisdiction of the U.S. Army Corps of Engineers, Florida


52
rural-urban fringe of Canadian cities. Seven variables,
"population change, dominant economic function, city size,
average residential land values, population density,
geographic region, and agricultural capability of the land"
(Pierce 1981:164), were used. Data, gleaned from various
sources, were subjected to several statistical analyses to
measure both collective and relative impacts of the
variables on urban expansion. Only three variables,
population change, economic function, and agricultural
capability, proved useful. Pierce states that the large
degree of unexplained variation results from the complexity
of the problem and the lack of "more precise measures of
urban form and process and . land-use data ..."
(1981:171).
Zeimetz et al. (1976) also analyzed rate of
conversion of rural lands in fringe areas. In their study
of 53 rapidly developing counties throughout the United
States, they found that, while there was considerable
variation between areas, an average of 0.173 acres of rural
land was converted for each person increase in population.
They also found that the overall rate of conversion of land
to urban uses in the 53 counties between 1960 and 1970 was
3.4 percent, which they did not consider high (Zeimetz et
al. 1976). However, even though the Department of
Agriculture does not consider the rate of land-use


61
One of the major goals of the MPOs was to
demonstrate the transportation needs of their regions to
both the state and federal transportation agencies.1
Justification for new or improved roads was based on a
priority system, which was shown by development and use of
transportation models. The models projected, usually for a
20-year time period, average daily traffic and volume
capacity ratio, that is, the number of vehicles using the
road and the number of vehicles for which the road was
designed.
One of the problems of transportation modeling
identified early on was a need for accurate, consistent
data. As early as 1961, data requirements were articulated
in a joint policy statement by the American Institute of
Planners and the Institute of Traffic Engineers. The
organizations agreed that planning responsibilities included
collection of all land use and socioeconomic data on a zone-
by-zone basis (Joint Policy Statement of the American
Institute of Planners and the Institute of Traffic Engineers
1961:70). In this 1961 report, however, the term "zone" was
not defined.
^Roads considered were federal, state, and county.
Municipal roads which were not part of those systems were
not modeled and were maintained by local funding.


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
RURAL-URBAN FRINGECONTINUUM OR DICHOTOMY?
A STUDY OF THE HIGH-GROWTH AREA,
SEMINOLE COUNTY, FLORIDA
By
Storm L. Richards
December 1987
Chairman: David L. Niddrie
Cochairman: Edward J. Malecki
Major Department: Geography
Despite a growing interest in urban, rural, and
rural-urban fringe, it has been difficult to define these
terms precisely. Within the United States, the criteria set
by the Bureau of the Census are most used as definitions.
These are set out in such a way, however, that they are
often inappropriate for local decision-making. Yet
economic, political, and administrative decisions often
depend on whether or not areas are labeled "urban" or
"rural."
At present, decisions, particularly in high-growth
areas such as Seminole County, Florida, are often made on
the basis of a regional data set which may or may not
reflect characteristics of rural and urban. This study
xi


45
industrial, residential, or commercial areas and on suburban
development and does not include urban expansion into rural
lands and the resulting rural land-use changes. Early
studies of suburban development, which would have been
likely to include rural and agricultural conversion,
probably did not because the development was not far enough
removed form the city to compete with rural land uses.
Within the past two decades, however, the rural-urban fringe
has received more attention in the literature.
Models of Land Use in
the Rural-Urban Fringe
The urbanization of rural lands and the influence of
urban development on nearby rural areas in "high-growth"
areas were discussed by Sinclair in his seminal article "Von
Thnen and Urban Sprawl" (1967). After outlining von
Thnen's model, Sinclair said that while it had been
appropriate in the past and continued to apply to less-
developed areas, it no longer describes processes occurring
in areas of rapid urban expansion. He suggested that there
is still a decline in rent with distance from the urban
area, but that this is not related to the urban market as it
was in von Thnen1s model. New factors now influence
patterns of agricultural land use near cities and the most
important of these is what has been called "the anticipation


4
Review of Census Definitions
of Urban, Urban Fringe, and Rural
The 1910 Census established the most important
element in all subsequent Census definitions of urban. In
that year all incorporated places with 2,500 or more
inhabitants were designated urban (U.S. Bureau of the Census
1913) .
From 1910 until 1950, the basic definition of urban
remained unchanged. Each Census, however, also included
special rules to cover certain areas which were not
incorporated, but contained a substantial population. In
1910 and 1920, all towns (townships) in Massachusetts, Rhode
Island, and New Hampshire with populations of 2,500 or more
were included whether or not they were incorporated because
in these states incorporation is not granted until the
population reaches 10,000. In 1930, the Census special
rules stated that all townships in Massachusetts, Rhode
Island, and New Hampshire were included in the urban
designation if they had a population of 2,500 and "certain
urban characteristics" which were not specified in the
Census. The category was also expanded to include "a few
large townships in other states." Again, the criteria for
inclusion were nebulous.
In 1940, the special rules became more exacting.
Townships in the three previously mentioned New England


59
Nevertheless, these data are the basis for all regional,
county, and virtually all municipal planning in Seminole
County and therefore become the basis for subsequent
definitions of urban, rural,and the rural-urban fringe.
Traffic Zones as a
Standard Areal Measurement
A city is first divided into subareas, using
spatial units such as blocks, census tracts, or
traffic zones.
Cadwallader 1985:2
Decision-making at the local level requires some
basis for division of the area, city, county, or region into
urban or rural contingents. In Central Florida the traffic
zone has been chosen as the standard unit of areal
measurement.
History of Traffic Zones
Although traffic zones did not come into common
usage as geographic units for transportation studies until
the early 1960s, they were first used in the 1916 Chicago
Transit Study, which analyzed home-to-work ridership. They
were also used in an origin-destination study in 1947-48
called the McGuire Report for the Boston Area. Then, in the
early 1950s, transportation studies in Detroit and Chicago
brought both traffic zones and computer usage to national
attention (Roger Creighton 1987, Roger Creighton Associates,
consulting engineers, Delmar, NY, personal interview).


CHAPTER I
INTRODUCTION
Unfortunately, there is no universally accepted
distinction between urban and rural.
Murphy 1966:1
In the last ten years, a large proportion of the
theoretical work in urban geography and other
disciplines in the urban realm has been devoted to
the problem of definition.
Sayer 1984:279
Throughout the United States, and especially in
high-growth areas such as Florida, cities are expanding
beyond their incorporation boundaries. Near these cities,
areas which had once been rural countryside, farms,
pastures, and woods are now sprouting residential,
commercial, and industrial developments. The amount and
direction of urban growth are often unprecedented and
unpredicted, and the effects of the growth on the
surrounding rural areas are poorly understood. The greatest
amount of change, however, and therefore the greatest effect
on the countryside occurs within that nebulous area often
called the rural-urban fringe.
Despite a growing interest among geographers,
planners, and anthropologists in urban, rural, and rural-
urban fringe areas, it has been difficult to define these
1


Table 6
Persons per Household and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data3
Planning
Data
Density
Data3
Planning
Data
Density
Data3
n
175
175
141
141
34
34
R2
.003
. 226
. 002
.212
. 076
. 302
Intercept
(Constant)
2.65
5.59
2.57
6.02
3.14
3.13
Slope
-0.00
-0.03
-0.00068
-0.03
-0.00347
-0.01
F-value
0.52
56.5
0.28
37.85
2.63
13.76
Range
5.01
16.85
3.71
16.85
4.01
6.19
Average (Mean)
2.59
3.42
2.53
3.82
2.84
1.77
Value of
Intersection


20.43 miles
14.45 miles
20.43 miles
14.45 miles
aThese results, though included in the table, were discarded as not valid.


24
attitudes and location by designating British constituencies
with less than 3 percent agricultural employment as urban.
United States Definitions
Within the United States, the criteria set by the
Bureau of the Census are most often used to define urban and
rural areas (Murphy 1966, Lang 1986). The major factors
employed by the Census to determine urban areas are
population size, incorporation boundaries, and, to a lesser
extent, population density and economic development. The
major factor determining designation of rural areas is that
the areas are not urban by census definition.1
Unfortunately, the census criteria and, therefore,
the census definitions, are not always sufficient. In a
recent study of the adequacy of census definitions, Lang
found that "[p]olicy makers and census data users across the
United States are calling for revisions of the definitions
or urban and rural population and places currently used by
the U.S. Census Bureau. They contend that the definitions
are outdated and do not reflect the current realities of
population distribution, lifestyles, and settlement
patterns" (Lang 1986:118). Despite these criteria, the
census data remain at present the most comprehensive and
-Census definitions of urban and rural have been
discussed in greater detail in Chapter I, pages 4-11.


134
Distance From
Traffic
Node
Area /
Populat
Zone
(Tenths of Mile)
Square Miles
(1980
51
108-5
3.60
925
52
113.5
3.80
47
53
106.5
0.46
1787
54
103.0
0.68
603
55
101 .O
0.62
812
56
96.0
0.48
481
57
87.5
0.80
179
59
92.0
1.02
469
60
95.0
9.00
589
61
107.5
2.22
158
62
124.5
3.82
464
63
133.0
10.04
174
68
155.0
19.88
1494
69
129.0
2.46
879
70
123.5
2.52
955
71
114.5
11.98
413
72
93.5
0.94
4
73
104.5
1.40
652
74
99.0
0.82
20
75
104.5
2.40
967
76
118.5
1.78
454
77
116.5
1.64
66
78
127.5
6.67
521
83
77.5
1.58
2547
84
80.0
1.12
226
86
77.0
1.60
106
87
70.0
2.22
179
88
67.5
1.36
336
89
59.0
0.70
397
90
60.0
1.04
1376
91
54.0
0.70
2945
92
55.5
0.30
1391
93
64.0
0.62
19
94
59.0
1.04
993
95
51.8
0.92
924
96
44.5
2.60
2423
97
44.0
0.40
1716


examines, through various statistical analyses, the utility
of one such data set in differentiating urban and rural
populations and areas.
The analysis describes and compares the relationship
between distance from the urban node and eight socioeconomic
variables in each of six data sets. The F-tests show that x,
distance from the node, is useful in predicting y, increase
or decrease in the socioeconomic variables in many of the
cases.
Thus, the study supports a distance-decay function
of the variables in several of the data sets. Because of
the gradient within these data sets, the study also suggests
the existence of a rural-urban fringe which is a continuum
between rural and urban areas of the county.
xi i


85
the density results show the differences between the highest
and lowest population density figures. Thus, ranges for
absolute population in incorporated and unincorporated
populations for the traffic zones are 3,923 and 4,681,
respectively. The population density, however, has a range
of 5,923 persons per square mile for incorporated traffic
zones and 4,984 persons per square mile for unincorporated
traffic zones.
Although the distribution is scattered, the expected
intersection of the urban and rural planning data regression
lines indeed takes place at 11.84 miles from the node (see
Table 3 and Figure 7). When the data are adjusted to
reflect density, the intersection of the regression lines
moves outward to 15.59 miles from the node (see Table 3 and
Figure 8). The approximately 30 percent difference between
the two intersections could make a difference in
governmental and private planning decisions. The planning
data suggest a break between rural and urban at 11.84 miles
from the node. Since these are the data used to make
governmental decisions, this would typically be where
governmental services abate. The density data, however,
suggest that development has advanced beyond the 11.84-mile
limit, as far as 15.59 miles. Therefore, the outermost
development may not receive essential services.


Page
Social Area Analysis and
Factorial Ecology 37
Social area analysis 37
Criticisms of social area
analysis 38
Factorial ecology 39
Criticism of factorial
ecology 40
Von Thnen's Theory of Agricultural
Land Use 40
Criticisms of Von Thnen's Theory... 41
Alonso's Theory of Urban Land
Market 42
Criticisms of Alonso's Theory 43
The Rural-Urban Fringe 44
Models of Land Use in the Rural-
Urban Fringe 45
Empirical Studies of the Rural-
Urban Fringe 46
General loss of farmland 48
Encroachment of urban
land uses onto the
rural-urban fringe 51
Land-Use Conversion within the
Rural-Urban Fringe of
High-Growth Areas 53
Seminole County as a High-
Growth Area 54
Conclusion 55
III METHODOLOGY 58
Traffic Zones as a Standard Areal
Measurement 59
History of Traffic Zones 59
Use of Traffic Zones in
Seminole County 63
Use of the Traffic Zone in
the Present Study 68
Definitions of the Variables 71
The Roles of Distance and Density 74
Regression Analysis 74
F-Values 76
Z-Score Statistic 77
Summary 7 7
IV ANALYSIS 79
Analysis and Data Sets 79
Presentation of Findings 80
vi


89
The slope of the regression lines is negative for
each of the six data sets (see Table 4). The slope values
for the planning data sets are -1.02 for combined TZs, -0.60
for incorporated TZs, and -2.55 for unincorporated TZs. The
density data slopes, however, have less variation. These
values are -3.24 for the combined data, -3.00 for
incorporated data, and -3.16 for unincorporated data (see
Table 4). The regression lines for unincorporated and
incorporated planning data cross at 11.44 miles from the
node (see Table 4 and Figure 10). Since the values for the
incorporated and unincorporated density have similar slopes,
the lines do not cross in Seminole County. In fact, they
diverge slightly with distance from the node (see Table 4
and Figure 11). There is little appreciable difference
between incorporated and unincorporated single-family
housing density within the county.
The difference between the planning data and density
data findings is important because developers and investors
often make decisions based on available data. In the county
any development or planning choices must be deduced from
planning data. Thus, if the intersection of the regression
lines were interpreted as the rural-urban fringe for this
particular variable, the use of the planning data would
suggest that beyond 11.44 miles the county is more rural
than urban. The present research shows, however, that by


169
Jones, D. W.
1982Location and Land Tenure. Annals of the
Association of American Geographers 72:314-331.
Katzraan, M. T.
1974 The Von Thiinen Paradigm, the Industrial-Urban
Hypothesis, and the Spatial Structure of Agriculture.
American Journal of Agricultural Economics 56:683-696.
Kellerman, A.
1983 Economics and Spatial Aspects of Von Thiinen1 s
Factor Intensity Theory. Environment and Planning A
15 : 1521-1530.
Knack, R.
1984 How Road Impact Fees Are Working in Broward County.
Journal of the American Planning Association 50(6): 24-
25 .
Krueger, R. R.
1978 Urbanization of the Niagara Fruit Belt. The
Canadian Geographer 22f3):179-194 .
Krzymowski, T.
1974 Graphic Presentation of Thiinen' s Theory of
Intensity. Journal of Farm Economics 10:461-482.
Levinson, H. S., and R. A. Weant
1984 Transportation Planning: An Overview. Journal of
the American Planning Association 50(6):5.
Ley, D., and J. Mercer
1980 Locational Conflict and Politics of Consumption.
Economic Geography 56:89-109.
Marchand, B.
1984 Urban Growth Models Revisited: Cities as Self-
Organizing Systems. Environment and Planning A 1^6:849-
990 .
Mark, D. M., and T. K. Peucker
1979 Regression Analysis and Geographic Models: Reply.
The Canadian Geographer 23( 1) : 79-81.
McKain, W. C., and R. G. Burnight
1953 The Sociological Significance of the Rural-Urban
Fringe from the Rural Point of View. Rural Sociology
18:109-116.


LIST OF TABLES
Table Page
1. Seminole County Population, 1930-1980 17
2. Sources of Comprehensive Planning Data
for Cities in Seminole County, Florida 64
3. Population and Distance from Node 82
4. Single-Family Housing and Distance
from Node 88
5. Multi-Family Housing and Distance from
Node 93
6. Persons per Household and Distance
from Node 98
7. Resident Employment and Distance from
Node 100
8. Attendant Employment and Distance
from Node 104
9. Retail Employment and Distance from
Node 108
10. Income and Distance from Node Ill
11. Comparison of Means of Density
Populations 115
12. Comparisons of F-Value and Significance
Levels (95-Percent Confidence Level) 122
13. Comparisons of Values for Incorporated
and Unincorporated Intersections 123
viii


163
Shevky, E., and W. Bell
1955 Social Area Analysis. Stanford, CA: Stanford
University Press.
Sincich, T.
1982 Statistics by Example. San Francisco: Dellen
Publishing Company.
Sinclair, R.
1967 Von Thnen and Urban Sprawl. Annals of the
Association of American Geographers 57:72-87.
Snyder, J.
1984 Cities in the Suburbs. The Orlando Sentinel.
Florida Magazine (June 25):1, 12-13.
Thrall, G. I.
1987 Land Use and Urban Form: The Consumption Theory of
Land Rent. New York: Methuen.
Troughton, M. J.
1976 Landholding in a Rural-Urban Fringe Environment:
The Case of London, Ontario. Occasional Paper No. 11.
Ottawa: Environment Canada, Lands Directorate.
United Nations Secretariat
1975 Statistical Definitions of Urban Population and
Their Uses in Applied Demography. In Basic Data Needed
for the Study of Urbanization. S. Goldstein and D. Sly,
eds. Pp. 15-32. Dolhain, Belgium: Ordina Editions.
U.S. Bureau of the Census
1913 Abstract of the Census, 1910. Washington, DC:
Government Printing Office.
U.S. Bureau of the Census
1923 Abstract of the Fourteenth Census of the United
States, 1920. Washington, DC: Government Printing
Office.
19 3 3 Abstract of the Fifteenth _Census of the United
States, 1930. Washington, DC: Government Printing
Office.
1942 Population. Second Series. Characteristics of the
Population. Florida, 1940. Washington, DC: United
States Government*Printing Office.


150
Resident
Attendant
'raf fie
Employment/
Attendant
Employment/
Zone
Square Mile
Employment
Square Mile Income
98
382.35
409
601.47
919,276.00
99
1558.33
527
4391.67
SI 9,276.00
100
1226.92
HO
211.54
919,276.00
101
1222.22
228
1266.67
S19,276.00
102
1351.25
107
133.75
S22,837.00
103
574.34
20
13.16
S22,837.00
105
427.69
41
31.54
922,837.00
111
184.68
120
54.05
S23,684.00
112
285.71
35
35.71
923,684.00
113
1645.45
62
140.91
923,684.00
114
184.62
239
459.62
923,684.00
115
1508.33
164
195.24
S23,684.00
116
1812.96
177
327.78
918,951.00
117
1793.75
127
264.58
918,951.00
118
1595.24
364
866.67
S18,951.OO
119
995.45
178
404.55
922,026.00
120
2076.19
252
600.00
S22,026.00
123
1950.00
253
1405.56
922,026.00
125
307.35
625
919.12
917,467.00
126
1303.13
638
1993.75
917,467.00
127
861.84
190
250.00
917,467.00
128
1194.83
588
1013.79
S17,467.00
129
1131.82
297
1350.00
923.376.00
130
857.14
318
2271.43
923,376.00
131
1792.86
88
314.29
S23.376.00
132
996.00
46
92.00
S23.376.00
133
2155.26
20
52.63
923,376.00
134
1030.95
20
47.62
923,376.00
135
1885.71
485
1154.76
923,376.00
136
27.94
198
58.24
922,735.00
138
141.18
344
1011.76
S22.735.00
139
1100.00
40
51.28
922,735.00
140
1248.57
188
268.57
918,369.00
141
1220.00
823
4115.00
918,369.00
142
607.14
950
848.21
S18.369.00
143
1125.00
478
1493.75
913,200.00
144
182.00
538
1076.00
913,200.00


44
developed countries. Few urban areas now have one central
area utilized by all inhabitants (Palm 1981). By assuming a
totally free market and optimum usage of land, the model
fails to address a modern fact of life. Governmental
restrictions often preclude "highest" and "best" usage
(Dennis and Clout 1980). Nor does the model take into
account the involvement of large development and real-estate
corporations which undoubtedly influence the urban land
market (Cadwallader 1985). In addition, as with all models
which assume "economic man," there is the objection that man
is never "all knowing" and rarely acts in the most rational
manner (Palm 1981).
Despite its simplicity, or because of it, as Palm
(1981) suggests, Alonso's model persists. Even some of its
most determined critics, Dennis and Clout, admit that "the
model has proven remarkably, perhaps uncomfortably,
successful in predicting patterns of land use and population
distribution" (1980:102), even though, as Thrall points out,
it does not explain "the underlying forces for behavior of
the system" (1987:9).
The Rural-Urban Fringe
What has become known as the rural-urban fringe has
been central to few urban geographic models and studies.
Emphasis instead has been on the central district (CBD) and


To Jeanne and Emerson


Table 13
Comparisons of Values for Incorporated and Unincorporated Intersections
Variable
Planning Data
Density Data
Population
11.84
15.59
Single-Family Housing
11.44
-64.38a
Multi-Family Housing
13.65
10.75
Persons per Household
20.43
14.45c
Resident Employment
11.28
15.45
Attendant Employment
-16.56a
14.62
Retail Employment
3.07a
14.65
Income
33.05b
12.60
aDivergent
^Convergent
cStatistics not valid; see page 95 in text
123


109
SEMINOLE COUNTY
o
Distonci k Mod (tonths o mil)
0X7
Incorporated Unincorporated
Incorporated
Unincorporated
Figure 19. Regression lines for incorporated and
unincorporated retail employment planning data


136
'raffle
Distance From
Node
Area/
Populat.
Zone
(Tenths of Mile)
Square Miles
<1980
145
31.5
0.70
679
146
36.5
0.60
490
147
40.0
0.50
870
148
42.5
0.44
1097
149
48.5
0.84
2888
150
57.0
1.04
78
151
46.5
0.20
224
152
42.5
0.76
670
153
35.0
0.56
1098
154
33.5
0.84
2453
155
28.5
0.74
2580
156
30.0
0.84
81
157
25.0
O 98
1259
158
21.5
0.84
1607
166
29.5
0.90
2091
167
16.5
0.50
893
168
23.5
0.88
3468
169
18.5
0.64
1504
170
12.8
1.22
1932
171
5.5
0.50
765
172
5.5
0.46
2725
173
6.5
0.34
1556
174
14.5
0.22
1210
175
15.5
0.98
2148
176
14.5
0.50
683
177
21.5
0.30
212
178
36.5
1.70
234
179
28.0
0.84
1235


Figure Page
13. Regression lines for incorporated
and unincorporated multi-family
housing density data 95
14. Regression lines for incorporated
and unincorporated persons-per-
household planning data 99
15. Regression lines for incorporated
and unincorporated resident
employment planning data 101
16. Regression lines for incorporated
and unincorporated resident
employment density data 102
17. Regression lines for incorporated
and unincorporated attendant
employment planning data 105
18. Regression lines for incorporated
and unincorporated attendant
employment density data 106
19. Regression lines for incorporated
and unincorporated retail
employment planning data 109
20. Regression lines for incorporated
and unincorporated retail
employment density data 110
21. Regression lines for incorporated
and unincorporated income dollars
planning data 113
22. Regression lines for incorporated
and unincorporated income dollars
density data 114
x


46
factor," which is defined as the effects of the perception
of encroaching urban development. He stated that.
As the urbanized area is approached from a distance, the
degree of anticipation of urbanization increases. As
this happens, the ratio of urban to rural land values
increases. Hence, although the absolute value of the
land increases, the relative value for the agricultural
utilization decreases. (1967:78)
Another model describing land use in the rural-urban
fringe was set out by Pryor (1971) (see Figure 3).
Described as a "process-response model," the model shows
relationships between percentage of urban and rural land use
and distance from areas which are 100 percent urban at one
extreme and 100 percent rural at the other. The process
involved is urbanization and the response is land-use
change. Pryor (1971:62) suggested that this model be used
in conjunction with other models to study urban encroachment
into rural areas.
Empirical Studies of
the Rural-Urban Fringe
Urban encroachment, ingress of urban influences to
areas which have been traditionally rural, is a major theme
of empirical studies of the rural-urban fringe. Such
studies focus on land-use change, particularly loss of farm
lands and encroachment of urban land uses (Furuseth and
Pierce 1982, Champion 1983).


105
SEMINOLE COUNTY
Kstonci to Nodi (tonttis of mill)
0 X v
Incorporated Unincorporated Incorporated Unincorporated
Figure 17. Regression lines for incorporated and
unincorporated attendant employment planning data


Table 12
Comparisons of F-Value and Significance Levels
(95-Percent Confidence Level)
Combined TZ
Incorporated TZ
Unincorporated TZ
Variable
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
Population
15.80
56.00
8.80
37.85
6.24
8.38
Single-Family
Housing
4.64
21.76
1 26a
11.96
5.66
8.46
Multi-Family
Housing
1 42a
18.46
11.81
17.66
2.00a
2.04a
Persons per
Household
0.52a
56.50
0.2 8a
37.85
2.63a
13.76
Resident
Employment
15.47
51.13
9.25
3 8.39
5.96
7.76
Attendant
Employment
0.87a
20.19
0.000a
15.78
2.2 6a
4.83
Retail
Employment
2.85a
11.29
0.14a
8.50
3.08a
3.40a
Income
56.51
70.00
59.40
56.07
18.38
25.34
aNot significant at 95-percent confidence level
122


161
Lang, M.
1986 Redefining Urban and Rural for the U.S. Census of
Population: Assessing the Need and Alternative
Approaches. Urban Geography 7(2):118-134.
Leinberger, C. B.
1987 Sprawl. Builder (April):100-104.
Ley, D.
1983 A Social Geography of the City. New York: Harper
& Row, Publishers.
Light, I.
1983 Cities in World Perspective. New York: Macmillan
Publishing Co., Inc.
Lindeman, B.
1976 Anatomy of Land Speculation. Journal of the
American Institute of Planners 42(2) : 142-152.
Long, N.
1987 Urban Villages Will Mold Life Styles of the Future.
Orlando (July):43-44,114
McKenzie, R. D.
1939 The Metropolitan Community. New York: McGraw-
Hill.
Morehouse, T. A.
1969 The 1962 Highway Act: A Study in Artful
Interpretation. Journal of the American Institute of
Planners 35(3):160-168.
Morris, B.
1987 Shallow Roots: New Suburbs Tackle City Ills While
Lacking a Sense of Community. The_Wall Street Journal
(March 26):1,25.
Murphy, R. E.
1966 The American City: An Urban Geography. New York:
McGraw-Hill Book Company.
Noble, H. F.
1962 Trends in Farm Abandonment. Canadian Journal of
Agricultural Economics 10:69-77.


78
such areas. In Seminole County, the bases for
distinguishing urban from rural are the incorporation
boundaries and the characteristics described in the data set
referred to in this study as the planning data set.
The analyses to follow are intended to determine the
viability of the characteristics in (1) determining urban
and rural and (2) distinguishing the rural-urban fringe.
Toward these ends, the data, in original form (and after
modification to account for density), are subjected to
several statistical examinations.


I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
<~hftjV\d X'files'/
David L. Niddrie, Chairman
Professor of Geography
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
xx
EdwaVd J. Malecki, Cochairman
Professor of Geography
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Louis A. Paganini
Associate Professor of
Geography
I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
William R. Maples /
Professor of Anthropology


ra
Zon
1
2
3
4
6
7
8
45
46
47
58
64
65
66
67
79
80
81
104
106
107
108
109
110
121
122
159
161
162
163
164
165
180
181
5
9
147
Resident
Employment/
Square Mile
Attendant
Employment
Attendant
Employment/
Square Mile
16.44
193
16.36
115.10
117
60.94
57.50
17
3.54
123.00
41
20.50
11.64
0
0.00
25.81
0
0.00
111.54
0
0.00
7.03
60
12.05
0.00
146
70.87
529.29
173
123.57
82.50
376
470.00
16.77
71
4.53
16.84
102
2.87
7.74
4
0.28
3.45
30
1.15
53.67
86
19.72
81.29
196
70.50
70.55
28
19.18
70.69
2
3.45
14.29
24
19.05
5.56
120
133.33
74.63
204
152.24
54.00
35
35.00
1421.59
220
250.00
319.09
77
35.00
2039.58
293
610.42
420.63
90
56.25
142.44
181
31 lO
589.29
371
265.00
818.75
45
21.63
473.33
30
16.67
291.18
617
604.90
1187.50
140
175.00
345.16
10
8.06
18.88
0
0.00
0.96
383
368.27
Income
$24,522.00
$24,522.00
$24,522.00
$24,522.00
$24,522.00
S24,522.00
$24,522.00
S8,180.00
$8,180.00
$8,180.00
$17,154.00
S18,383.00
$18,383.00
$18,383.00
$17,625.00
$20.865.00
$20,865.00
$30,239.00
$22,837.00
$22.837.00
$22,837.00
$23,684.00
$23,684.00
$23.684.00
$22,026.00
$22,026.00
$36,759.00
$36.759.00
$28,666.00
S28,666.00
$28,666.00
$28,666.00
$21,398.00
S21,398.00
S24,522.00
$20,779.00


60
The recent evolution of planning in the United
States as it applies to federal funding of transportation
projects corresponds roughly with the application of
advanced computer technology, an increased awareness of the
need for more precise urban and rural socioeconomic data for
modeling transportation, land use, and housing, and a
greater demand by private citizens for involvement in
governmental decisions. In the early 1960s, the Federal
Highway Administration began developing alternative models
for transportation planning. During the period traffic
zones (TZs) came into general use as an areal measurement.
The impetus for the growth of transportation
planning was the Federal-Aid Highway Act of 1962. The Act
required that after July 1, 1965, all federally aided
highway projects in metropolitan areas with populations over
50,000 be based on transportation modeling. A major
requirement of the Act was that "the Secretary [of
Transportation] shall not approve . any program . .
unless he finds that such projects are based on a continuing
comprehensive transportation planning process carried on
cooperatively by states and local communities ..."
(Morehouse 1969:160). This "Three C" (cooperative,
comprehensive, and continuing) process endures today and is
the basis for the establishment of Florida's Metropolitan
Planning Organizations (MPOs).


27
The astonishing array of characteristics and
combinations of characteristics used to define urban in the
various censuses is only part of the problem faced by the
urban researcher who is trying to compare international
data. Because each country sets its own values for, and
interpretations of, the criteria it chooses, comparisons
become even more difficult. The following descriptions of
census criteria for urban and rural in several countries
illustrate these points.
In some countries, designations of urban and rural
are based on concepts similar to the "places" designations
in the U.S. Census. Legal boundaries and powers are
disregarded and concentrations of population are used
instead. In Ghana, population size of places is the major
determinant of urban and rural. Concentrations of 5,000 or
more inhabitants are considered urban. The Swedish urban
and rural designation system combines population size with
housing density. Places with 200 or more residents in
dwellings that are 200 or less meters apart are considered
urban (Wander 1975). The Canadian Census is similar to the
U.S. Census in that it uses both population size and
population density as urban designators. Areas with a
population of 1,000 or more and a density of at least 400
per square kilometer are considered urban (Yeates 1987).


168
Garrison, W. L.
1965 Urban Transportation Models in 1975. Journal of
the American Institute of Planners 31(2):156-158.
Grigg, D.
1981 Agricultural Geography. Progress in Human
Geography 5:268-276.
Grossman, D.
1982 Northern Samaria: A Process-Pattern Analysis of
Rural Settlement. The Canadian Geographer 26(2):110-
127 .
Hall, D.
1983 Tightening the Green Belt. Town and Country
Planning 52(10):254.
Hall, P., ed.
1966 Von Thnen1s Isolated State. Oxford: Pergamon
Press.
Hancock, T.
1980 Viewpoint Z: The Countryside in the 1980s. Town
and Country Planning 49(5) :142-143.
Healy, R. G., and J. L. Short
1979 Rural Land: Market Trends and Planning
Implications. Journal of the American Planning
Association 45(3):305-317.
Hebbert, M.
1981 The Land Debate and the Planning System. Town and
Country Planning 50(1) : 22-23.
Hembd, J., and C. L. Inflanger
1981 An Application of Trend Surface Analysis to a
Rural-Urban Land Market. Land Economics 57(3):303-322.
Janelle, D. G.
1977 Structural Dimensions in the Geography of
Locational Conflicts. The Canadian Geographer
21(4):311328.
Jones, A. P., W. I. McGuire, and A. D. Witte
1978 A Reexamination of Some Aspects of Von Thnen's
Model of Spatial Location. Journal ofRegional Science
18:1-15.


ra
Zon
98
99
100
101
102
103
105
111
112
113
114
115
116
117
118
119
120
123
125
126
127
128
129
130
131
132
133
134
135
136
138
139
140
141
142
143
145
Multi-Family
Housing/
Square Mile
11.76
833.33
13.46
66.67
18.75
15.13
46.15
3.15
102.04
2354.55
317.31
561.90
153.70
2108.33
957.14
13.64
1464.29
2488.89
0.00
0.00
52.63
1148.28
1395.45
1178.57
2657.14
178.00
121.05
0.00
1580.95
48.24
161.76
44.87
498.57
1615.00
41.07
6.25
36.00
Persons
per
Household
2.78
2.02
2.94
2.61
3.06
2.94
2.73
2.97
2.39
1.68
1.37
2.73
2.73
2.00
1.95
3.05
2.20
1.84
2.41
2.19
2.78
1.89
1.75
1.73
1.62
3.37
2.89
2.30
2.54
1.37
2.16
3.03
2.32
1.82
3.25
3.72
2.08
Resident
Employment
260
187
638
220
1081
873
556
410
280
724
96
1267
979
861
670
438
872
351
209
417
655
693
249
120
502
498
819
433
792
95
48
858
874
244
680
360
91


41
Is, therefore, Included briefly in this section as a
background for Alonso's classic theory of urban land rent
(Alonso 1971, 1983).
In the early nineteenth century, von Thnen
developed a model of agricultural land use based on his
observations in and around his estate in Germany. He
believed that agricultural land-use patterns were determined
by the value of the land and the crops produced for market
and the distance to that market. Based on a simplifying set
of assumptions including an "isolated" and "uniform" plane
and "economic man," he described the processes that caused
the patterns (Palm 1981). Competition between different
types of land use was controlled by "Economic Rent, defined
. . as return from investment in the land" (Sinclair
1967:73). Transportation costs which rose with distance
from the city were important in determining rent. The
further the land was from the city, the more the farmer
would have to invest in transporting his product to market.
Therefore, to receive a reasonable return on his land, the
farmer had to invest in products which would either cost
less to transport or to produce (Sinclair 1967, Palm 1981).
Criticisms of Von Thnen1s Theory
While the patterns and processes of von Thnen1s
agricultural land-use model may still occur in


af
ion
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
43
44
48
138
Density
Single
Single Family
Multi-
Population/
Family
Housing/
Family
Area
Housing
Square Mile
Housing
466.91
215
158.09
2
317.07
194
118.29
16
182.27
200
90.91
4
549.11
189
168.75
18
526.14
162
184.09
5
358.16
120
122.45
7
483.33
66
68.75
96
401.43
148
105.71
88
359.52
115
136.90
12
911.36
140
318.18
6
457.06
395
232.35
10
28.17
17
11.97
2
22.28
22
10.89
0
470.79
369
182.67
10
789.47
171
150.00
261
1859.09
275
625.00
47
2313.79
461
794.83
18
2105.10
664
677.55
42
2335.71
335
598.21
32
1915.38
601
577.88
18
200.61
102
62.20
3
31.13
31
29.25
0
165.79
76
66.67
3
477.65
336
197.65
8
76.00
67
26.80
3
32.94
25
14.71
9
2348.53
201
295.59
320
3713.79
404
696.55
335
2372.73
172
781.82
76
2663.89
354
983.33
120
2022.50
190
475.00
259
176.50
106
53.00
67
7.81
0
0.00
5
976.21
577
280.10
132
2342.86
llOO
785.71
42
2642.00
504
1008.00
48
284.64
331
118.21
48


144
Multi-Fami1y
Persons
Traffic
Housing/
per
Resid
Zone
Square Mile
Household
Employ]
51
6.94
2.35
368
52
0.00
3.13
19
53
169.57
2.64
713
54
182.35
2.24
238
55
6.45
2.54
323
56
12.50
2.47
190
57
5.00
0.39
556
59
7.84
3.26
185
60
0.44
2.89
245
61
1.80
2.72
66
62
1 .05
2.72
201
63
0.30
2.35
73
68
2.11
2.68
594
69
8.54
2.84
337
70
4.76
3.02
366
71
0.50
2.46
159
72
0.00
2.00
2
73
6.43
2.73
250
74
2.44
2.00
8
75
42.50
2.47
371
76
13.48
3.03
174
77
0.00
3.00
25
78
1.05
2.37
210
83
9.49
2.97
968
84
0.00
2.33
86
86
1.25
0.00
39
87
0.90
2.80
65
88
0.00
3.05
124
89
7.14
3.25
146
90
4.81
2.14
507
91
34.29
3.32
1086
92
50.00
2.68
536
93
0.00
3.17
8
94
144.23
2.45
382
95
92.39
1.96
357
96
38.46
2.33
1003
97
25.00
2.43
711


39
Factorial ecology
As a reaction to the criticisms of social area
analysis, the factorial ecology methodology was developed in
the 1960s (Cutter 1985). This analytical process differed
from earlier types of analyses in the number of variables
used and its greater emphasis on spatial patterns associated
with the variables. Using the statistical technique, factor
analysis, a large number of variables is distilled into
"factors" which describe patterns of correlation among the
data (Palm 1981). The factors are then used to cluster
similar census tracts (Ley 1983). Analysis of geographic
distribution of census tracts attempts to explain patterning
in terms of existing conditions rather than accepting
preconceived model predictions.
Because factorial ecology studies have focused on
predominantly urban residential areas, such studies have
contributed little to urban-rural differentiation. The
approach of wide-ranging empirical analysis, however, is
applicable to rural-urban fringe areas as in the study by
Fesenmaier et al. (1979), in which urbanizing areas were
divided into subzones on the basis of statistical analysis,
shows.


-ai
'.on
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
43
44
48
49
50
143
Multi-Family
Housing/
Square Mile
Persons
per Resident
Household Employment
1.47
2.93
242
9.76
2.48
199
1.82
1.97
153
16.07
2.97
235
5.68
2.77
177
7.14
2.76
135
100.00
2.86
127
62.86
2.38
235
14.29
2.38
126
13.64
2.75
127
5.88
1.92
323
1.41
2.11
17
0.00
2.05
19
4.95
2.51
396
228.95
2.08
362
106.82
2.54
329
31.03
2.80
522
42.86
2.92
762
57.14
3.56
475
17.31
3.22
724
1.83
3.13
133
0.00
1.06
13
2.63
2.39
77
4.71
2.36
328
1.20
2.71
77
5.29
1.65
19
470.59
3.07
535
577.59
2.91
722
345.45
2.10
212
333.33
2.02
398
647.50
1.80
365
33.50
2.04
159
3.91
2.00
5
64.08
2.84
846
30.00
2.87
1227
96.00
2.39
581
17.14
2.10
350


156
Trof fie
Income/
Zone
Square Mile
145
518,857.14
146
537,558.33
147
545,070.00
148
539,502.27
149
520,691.67
150
516,712.50
151
5128,725.00
152
533,875.00
153
545,973.21
154
530,648.81
155
534,790.54
156
536,700.00
157
531,454.08
158
S36,700.00
166
531,851.11
167
S50,488.00
168
S28,686.36
169
539,443.75
170
520,691.80
171
S50,488.00
172
545,002.17
173
560,885.29
174
594,095.45
175
521,123.47
176
541,402.00
177
571,326.67
178
512,587.06
179
525,473.81


69
the RPC and used by the county to describe urban and rural
areas is based.
Despite the obvious disparity in traffic zone sizes
in the county (see Figure 4), neither area nor density data
have been calculated by the planning agencies. In the past,
comparisons of socioeconomic data have been based solely on
absolute data values. These values comprise the first major
data set of the study and are called the planning data.
In order to standardize comparison of traffic zones,
each of the 181 TZs in the research area has been
planimetered and the area calculated. Using these areas,
the planning data are converted to a second major data set
called density data (see Appendix).
For planning purposes in Seminole County,
incorporated areas are considered urban while the
unincorporated areas are designated rural. For this reason,
each of the major data sets is divided into two subsets:
1. Incorporated traffic zones which lie either
totally or partially within the incorporated
city limits of Altamonte Springs,
Casselberry, Winter Springs, Longwood, Lake
Mary, and Sanford (see Figure 6), and
2. Unincorporated TZs which correspond to the
rural portions of the county


171
Tandy, J., M. Stajys, and J. Bestall
1985 Washington Corridor Phoenix Redevelopment Area
Faces "Strip Syndrome." Urban Land 44(7):8-0.
Troughton, M. J.
1977 The Rural-Urban Fringe: A Challenge to Resource
Management? Proceedings, Geography Inter-University
Resource Management Seminar 7:43-75.
U.S. Department of Transportation
1980 The Land Use and Urban Development of Beltways Case
Studies. Washington, DC: U.S. Department of
Transportation.
Visser, S.
1979 Comment on Land-Use Theory and Factor Intensities.
Geographical Analysis 11:94-97.
1980 Technological Change and Spatial Structure of
Agriculture. Economic Geography 56:311-319.
Walker, D. V. H., and M. E. Zeller
1985 Promoting Public/Private Initiatives for
Preservation of Colorado Openlands. Urban Land
44(11):12-13.
Walker, R. A., and M. K. Heiman
1981 Quiet Revolution for Whom? Annals of the
Association of American Geographers 771:67-83.
Warren, D.
1980 The Countryside Tomorrow. Town and Country
Planning 49(6):182-183.
Webber, M. J.
1973 Equilibrium of Location in an Isolated State.
Environment and Planning A 5:751-759.
Williams, L. S.
1983 The Urbanization Process: Towards a Paradigm of
Population Redistribution. Urban Geographpy 4{2):122-
137 .
Yeates, M.
1985 The Core/Periphery Model and Urban Development in
Central Canada. Urban Geography 6(2):101-121.


64
Table 2
Sources of Comprehensive Planning Data
for Cities in Seminole County, Florida
City
Transportation
Zones
Census
Other
Density
Measurement
Oviedo
Yes
No
No
No
Lake Mary
Yes
No
No
No
Maitland
No
No
Yes
No
Longwood
Yes
Yes
No
No
Sanford
Yes
No
No
No
Altamonte
Springs
No
Yes
No
No
Winter
Springs
Yes
Yes
No
Yes
Source: Cohen 1987, personal interview; Delk 1987, personal
interview; Koch 1987, personal interview; Marder
1987, personal interview; Nagle 1987, personal
interview; Weaver 1987, personal interview; Wells
1987, personal interview.


62
The U.S. Census provided much of the data for the
transportation planning models, but a number of problems
came to light. For example, Census data are collected only
every 10 years, but transportation plans are based on 5-
year intervals and required updating annually. The models
also required very detailed information on small geographic
areas. Such data were not available in the appropriate
format or within an appropriate time frame from the Census
data.
One solution to the problem of standardizing data
for traffic models and revising the data routinely was the
use of traffic zones (TZs). While traffic zones had been
used on a routine basis in some areas, it was not until 1977
that the Federal Highway Administration outlined the
criteria for standardizing the zones in areas with
populations of 50,000 or greater:
The transportation analysis units are known as
zones. These zones vary in size depending on density or
nature of urban development. In the central business
district (CBD), zones may be as small as a single block
and in the undeveloped area they may be as large as 10
or more square miles. An area with a million people
might have 600 to 800 zones and an area of 200,000
people might have 150 to 200 zones. These zones attempt
to bound homogeneous urban activities; that is, a zone
may be all residential, all commercial, all industrial,
etc. Zones also should consider natural boundaries and
census designations.
An important consideration in establishing zones is
their compatibility with the transportation network to
be used. As a general rule, the network should form the
boundaries of the zones (U.S. Federal Highway
Administration 1977:2-3)


9
Rural Areas
By contrast, the Census definition of rural remains
the same as it was at the turn of the century. With one
exception, no specific characteristics have been assigned to
describe rural areas. The exception is that of an extended
city. In 1970, when the concept of the extended city was
recognized, the "Bureau of the Census examined patterns of
population density and classified a portion or portions of
each such city as rural" (U.S. Bureau of the Census 1972:v).
The rural classification required that the population
density be less than 100 individuals per square mile in an
area of at least five square miles or 25 percent of the
incorporated area (U.S. Bureau of the Census 1972). Aside
from this one instance, the Census definition of rural
simply states that any area not classified as urban is
rural.
The criteria for urban, urban fringe, and rural
which are established by the Census have been delineated
because these are the most widely accepted and utilized
definitions currently available in the United States. The
criteria also determine the various categories of Census
data. Thus, if the criteria and, therefore, the categories,
are flawed, the data are flawed. This could significantly
affect research into urban, rural, and rural-urban fringe


26
ways. The first is a discussion of which general census
criteria are used to establish urban areas in different
countries and the second is to describe how the criteria are
interpreted and applied to the delimitation of urban areas
in specific, selected countries around the world.
The ways in which different countries determine
urban areas range from simple to complex to bewildering. In
a survey of the characteristics used in various national
censuses to indicate urban areas, the United Nations
Secretariat (1975) found great diversity. Some countries
used only one characteristic, others used two or more, and
still others (56) did not indicate what they used.
Population size, the most common criterion, was employed
singly in 23 cases and in combination with other criteria in
49. Housing or population density, while used as the
indicator in only one census, was combined with other
characteristics in 11 censuses. Major economic activity was
also used as the criterion in only one instance, but was
used in concert with others in eight censuses. Type or
structure of government appeared alone three times and
combined with other characteristics three times. Finally,
various urban indicators not included in the other
categories were used by themselves in three censuses and in
combination with other characteristics in 16 others (United
Nations Secretariat 1975:18-19).


Table 5
Multi-Family Housing and Distance from Node
Measurement
Combined TZ
Incorporated TZ
Unincorporated TZ
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
.076
. 096
.078
. 106
. 059
.060
Intercept
(Constant)
164
432
189
513
32
54
Slope
-1 14
-3.49

-1.34
-4.31
-0.19
-0.40
F-value
1.42
18.46
11.81
17.66
2.00
2.04
Range
1,036
2,761
1,036
2,761
238
495
Average (Mean)
85
191
102
232
16
20
Value of
Intersection
13.65 miles
10.75 miles 13.65 miles 10.75 miles


139
Density
Single
Single Family
Multi-
Traffic
Population/
F amily
Housing/
Family
Zone
Area
Housing
Square Mile
Housing
51
256.94
368
102.22
25
52
12.37
15
3.95
0
53
3884.78
600
1304.35
78
54
886.76
145
213.24
124
55
1309.68
316
509.68
4
56
1002.08
189
393.75
6
57
223.75
459
573.75
4
59
459.80
136
133.33
8
60
65.44
200
22.22
4
61
71.17
54
24.32
4
62
126.70
174
45.55
4
63
0.25
71
7.07
3
68
75.15
516
25.96
42
69
357.32
288
117.07
21
70
378.97
304
120.63
12
71
34.47
162
13.52
6
72
4.26
2
2.13
0
73
465.71
230
164.29
9
74
24.39
8
9.76
2
75
402.92
290
120.83
102
76
255.06
126
70.79
24
77
40.24
22
13.41
0
78
78.13
213
31.94
7
83
1612.03
844
534.18
15
84
201.79
97
86.61
0
86
66.25
39
24.38
2
87
80.63
62
27.93
2
88
247.06
110
80.88
O
89
567.14
117
167.14
5
90
1323.08
639
614.42
5
91
4207.14
863
1232.86
24
92
4636.67
504
1680.00
15
93
30.65
6
9.68
0
94
954.81
255
245.19
150
95
1004.35
386
419.57
85
96
931.92
942
362.31
lOO
97
4290.00
695
1737.50
10


Table 10
Income and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
. 243
. 287
. 297
. 286
. 364
.441
Intercept
(Constant)
24,282
50,776
23,660
55,682
29,213
26,765
Slope
-56.56
-331.84
-59.14
-376.78
-75.94
-147.21
F-value
56.51
70.0
59.4
56.07
18.38
25.34
Range
30,278
166,454
24,347
31,213
28,579
14,189
Average (Mean)
20,384
27,906
19,819
17,009
22,726
45,370
Value of
Intersection

33
.05 miles
a 12.60 miles
33.05 miles3
12.60 miles
aThe resultant
distance is
outside of
Seminole
County.
111


114
SEMINOLE COUNTY
Kstonci to Modi (tofts of mito)
0 X V
I I I I
Incorporated Unincorporated Incorporated Unincorporated
Figure 22. Regression lines for incorporated and
unincorporated income dollars density data


23
concept of a separate urban phenomenon, defined spatially,
is irrelevant to understanding society" (Johnston 1986:103),
To bolster this position, the researchers argue that, in
more developed countries, factors such as mass media,
migration, and transportation networks have spread the
"urban way of life" to such an extent that rural-urban
distinctions can no longer be studied (Dunleavy 1982, Lang
1986). Others, however, contend that there are urban-rural
distinctions and issues which may be studied only through
the bounding of discrete areas into urban and rural (Sayer
1984, Johnston 1986, Lang 1986, Yeates 1987).
If the position that urban areas must be delimited
in order to address urban issues and questions adequately is
accepted, then the problem of urban definition must be
confronted and specific characteristics of urban must be
explored. In this context, several characteristics
attributed to urban areas are commonly used to discriminate
between urban and rural places. One of the most widely used
criteria is "high" population density (Cadwallader 1985,
Yeates 1987). The determination of exactly what level of
density constitutes "high," however, falls upon the
individual researcher (Yeates 1987). Another popularly
employed characteristic is nonagrarian-related occupations
(Cadwallader 1985, Johnston 1986, Lang 1986). Johnston
(1986) used this criterion in his study of political


Zon
1
2
3
4
6
7
8
45
46
47
58
64
65
66
67
79
80
81
104
106
107
108
109
110
121
122
159
161
162
163
164
165
180
181
5
9
Distance From
Node
Area /
Populat
Tenths of Mile)
Square Miles
(1980
119.0
11.80
491
115.0
1.92
561
98.0
4.80
702
102.0
2.00
625
78.0
4.64
138
54.0
4.92
323
53.0
2.08
590
143.5
4.98
95
147.0
2.06
1
133.5
1.40
2043
75.0
0.80
336
154.5
15.68
638
193.5
35.58
1455
196.0
14.34
268
213.0
26.08
227
102.5
4.36
579
84.5
2.78
560
88.5
1.46
272
56.5
0.58
111
61.0
1.26
47
66.5
0.90
13
73.5
1.34
241
74.5
1.00
133
65.4
0.88
3051
32.5
2.20
1712
26.5
0.48
2393
28.5
1.60
1835
45.5
5.82
2262
28.5
1.40
2265
38.5
2.08
4682
47.5
1.80
2342
32.5
1.02
816
37.0
0.80
2423
39.5
1.24
1089
79.0
3.92
186
56.0
1.04
5
132


LIST OF FIGURES
Figure Page
1. Seminole and adjacent counties 13
2. Counties included in the Orlando
Metropolitan Statistical Area and
the Orlando Urban Area Metropolitan
Planning Organization 14
3. Model describing land use in the
rural-urban fringe 47
4. Seminole County traffic zones 65
5. Seminole County census tracts 67
6. The incorporated cities and urban
node of Seminole Coxmty 70
7. Regression lines for incorporated
and unincorporated population size
planning data 83
8. Regression lines for incorporated
and unincorporated population density
data 84
9. Major transportation arteries in
Seminole County 87
10. Regression lines for incorporated
and unincorporated single-family
housing planning data 90
11. Regression lines for incorporated
and unincorporated single-family
housing density data 91
12. Regression lines for incorporated
and unincorporated multi-family
housing planning data 94
IX


42
lesser-developed countries, the utility of the model in
developed areas is questioned. In such areas, new modes of
transportation, declines in cost of transportation, and the
advent of refrigeration have lessened the effect of
transportation on siting of agricultural production.
Markets have expanded from the single central market to
regional, national, or international markets. Production
techniques favor large-scale agricultural enterprises.
Finally, and probably most important, land used for urban
purposes has become far more valuable than land used for
agriculture. Thus, the competition, especially in rapidly
developing areas, is no longer between different
agricultural uses, but between agricultural and urban uses
(Sinclair 1967).
Alonso's Theory of Urban Land Market
The foundations of the formal spatial analysis
of agricultural rent and location are found in the
work of J. von Thiinen, who said, without going into
detail, that the urban land market operated under
the same principles.
Alonso 1983:1
Based on von Thiinen' s ideas of economic rent and
land use, Alonso developed a model of urban land use. He
began with a set of assumptions similar to those of von
Thiinen. The physical environment of the urban area is
homogenous so that no area has any particular physical
advantage. There is only one central business district in


Zon
1
2
3
4
6
7
8
45
46
47
58
64
65
66
67
79
80
81
104
106
107
108
109
110
121
122
159
161
162
163
164
165
180
181
5
9
142
Multi-Family
Housing/
Square Mile
Persons
per Resident
Household Employment
0.68
1.89
194
2.60
2.76
221
1.46
2.59
276
4.00
2.49
246
0.00
3.54
54
0.81
3.47
127
0.96
3.49
232
0.00
2.32
35
0.00
1.00
O
19.29
2.89
741
3.75
5.01
66
0.38
2.81
263
0.53
2.80
599
0.42
2.65
111
0.38
2.84
90
0.46
3.02
234
0.72
3.09
226
2.74
2.62
103
0.00
2.52
41
1.59
2.04
18
0.00
2.17
5
2.99
3.35
100
0.00
2.51
54
26.14
3.16
1251
3.64
3.38
702
495.83
2.48
979
7.50
2.57
673
1.20
3.04
829
31.43
2.94
825
10.58
3.37
1703
0.00
3.16
852
43.14
3.06
297
20.00
3.04
950
8.87
2.71
428
0.77
2.16
74
0.00
2.50
1


56
compatible. Since data are collected based on the various
census definitions, it is difficult to make cross-cultural
comparison of the data. Even within the United States, the
census definitions and data are often not adequate,
especially for studies at the local level where finer
distinctions are required. Without adequate definitions of
urban and rural, a definition of the rural-urban fringe is
difficult, although several have been advanced.
Various models and analyses have contributed to the
understanding of the characteristics of urban, rural, or
fringe areas. None of the models, however, address the
problems of urban and rural differentiation.
Empirical studies of the rural-urban fringe
concentrate on loss of farmlands and encroachment of urban
land uses. While these changes seem to have little effect
on land use at a national level, they receive considerable
attention at the local level.
As urban land uses and population move into the
countryside in rapidly developing areas, change becomes more
evident. Depending on the point of view of the observer,
the changes may appear positive or negative. They may also
seem subtle or dramatic. In other words, the amount and
direction of change depends oftentimes on one's perception
and on whether or not one will benefit or lose as a result
of the change.


155
Traffic
Income/
Zone
Square Mile
98
£28,347.06
99
£160,633.33
100
£37,069.23
101
£107,088.89
102
£28,546.25
103
£15,024.34
105
£17,566.92
111
£10,668.47
112
£24,167.35
113
£53,827.27
114
£45,546.15
115
£28,195.24
116
£35,094.44
117
£39,481.25
118
£45,121.43
119
£50,059.09
120
£52,442.86
123
£122,366.67
125
£25,686.76
126
£54,584.38
127
£22,982.89
128
£30,115.52
129
£106.254.55
130
£166,971.43
131
£83,485.71
132
£46,752.00
133
£61,515.79
134
£55,657.14
135
£55,657.14
136
£6,686.76
138
£66,867.65
139
£29,147.44
140
£26,241.43
141
£91,845.00
142
£16,400.89
143
£41,250.00
144
£26,400.00


170
Morehouse, T. A.
1969 The 1962 Highway Act: A Study in Artful
Interpretation. Journal of the American Institute of
Planners 35(3):160-163.
Myers, R. R., and J. A. Beegle
1947 Delineation and Analysis of the Rural-Urban Fringe.
Applied Anthropology 6:14-22.
Park, R. E., E. W. Burgess, and R. D. McKenzie
1925 The City. Chicago: University of Chicago Press.
Patterson, H. L.
1968 Ontario's Disappearing Agricultural Land.
Agricultural Institute Review 23:7-10.
Pritchett, C. P.
1985 The Emerging Southeast Urban Regions. Urban Land
44(10):32-33.
Raup, P. M.
1975 Urban Threats to Rural Lands: Background and
Beginnings. Journal of the American Institute of
Planners 41(6) :371-378.
Richards, S. L.
1981 The Urban-Rural Fringe: Development at Whose
Expense? Paper Presented at the Florida Society of
Geographers. St. Augustine, Florida.
Sheppard, E. S.
1979 Regression Analysis and Geographic Models: Comment
Number 2. The Canadian Geographer 23(1):75-78.
Smith, P. J., and L. D. McCann
1981 Residential Land-Use Change in Inner Edmonton.
Annals of the Association of American Geographers
71:536-551.
Snyder, J.
1984 Cities in the Suburbs. The Orlando Sentinel.
Florida Magazine (June 25):1, 12-13.
Spielberg, F., and S. Andrle
1982 The Implications of Demographic Changes on
Transportation Policy. Journal of the American Planning
Association 48(3):301-308.


29
must also be within the boundaries of a "shi," "machi"
(town), or "mura" (village) (Wander 1975, Yamaguchi 1984).
The Dutch system divides municipalities into urban,
urbanized rural, and rural using a variety of
characteristics. Urban municipalities are those with
overall population densities of 300 persons per sguare
kilometer. These areas must contain at least one nucleus in
which 70 percent of the area's population (a minimum of
2,000 individuals) lives. This settlement must also have a
population density of 2,000 per square kilometer and at
least 90 percent of the male population must be
nonagriculturally employed. In urbanized rural areas, these
characteristics are considered. The most important is that
less than 20 percent of the male population is employed in
agriculture. Also, the major settled area has a population
less than 20,000. The third characteristic employed is
commuter patterns. Rural municipalities are those with more
than 20 percent of the male population employed in the
agricultural sector. These areas have less than 5,000
inhabitants in the major settlement and less than 300
persons per square kilometer overall density (Wander 1975,
Borchert 1984).
While only a few, selected examples of the criteria
used in different countries to determine urban or rural
status of areas have been described, it is apparent that


Table 9
Retail Employment and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
14 1
34
34
R2
.016
. 061
. 001
. 057
. 088
. 096
Intercept
(Constant)
63
185
61
208
53
63
Slope
-0.18
-1.26
-0.06
-1.42
-0.32
-0.43
F-value
2.85
11.29
0.14
8.50
3.08
3.40
Range
339
2,125
339
2,125
303
312
Average (Mean)
50
98
57
115
25
26
Value of
Intersection

-3,
.07 miles3 14.
. 65 miles
-3.07 miles3
14.65 miles
aThe resultant distance is outside of Seminole County.
108


80
compare two major data sets. These sets are called the
combined data in the analysis.
The first set, planning data, is the one in general
use in the county. It consists simply of total counts for
each traffic zone.
The second data set, density data, was calculated by
the author. Because the area of each traffic zone had not
been previously determined, density figures for traffic zone
variables have not been available to local governments.
These data, however, would be useful for planning purposes
because they better reflect the distribution of population
and population characteristics than do the planning data.
Each of the major, or combined, data sets is
subdivided into incorporated and unincorporated data sets.
Thus, a total of six data sets is used in the analysis.
Presentation of Findings
The results of the analysis are presented as a
series of table and graphs. Relationships between each
variable and distance are described in two ways:
1. Tabular--A table lists analysis results of
planning and density data within
incorporated, unincorporated, and combined
traffic zones, and


129
also be made by using cluster and discriminant analyses.
These techniques were used to distinguish urban from rural
and fringe areas with a degree of success by Fesenmaier et
al. in a 1979 study of London, Ontario, Canada.
Another consideration for further study would be to
expand the study area to include Orange and Osceola Counties
which, with Seminole County, make up the Tri-County MSA.
Such a study could use Orlando as the urban node. The
investigation might, however, abandon the idea of an urban
node and focus instead on transportation or utility
corridors.
In addition to examining the high-growth Tri-County
area, future studies should compare this area to other high-
growth areas and to low-growth and no-growth areas in the
state. Such studies could only advance the knowledge of
determination of urban, rural, and rural-urban fringe areas.
Meanwhile, it is essential to bear in mind that
Seminole County, the focus of the present study, is not
unique. There are many high-growth areas which have similar
characteristics and, therefore, a similar problem of
discerning a fringe area where urban expansion exists or is
likely to occur. Since the fringe area is difficult to
define quantitatively, more often than not, it has been
described by inference rather than empirical data. The
answer to the questions of whether it exists and where it


36
4. The related factor of high rents or high
land costs which can be an attractive or
repelling force
Criticisms of the classical models
The classical models have been the subjects of much
criticism. Both the theoretical underpinnings of the models
and the models themselves have come under fire.
Urban ecology, the theory which is the basis for the
concentric ring, sector, and multiple-nuclei models,
describes a process of invasion-succession land-use change
in which the mechanism is economic competition (Light 1983).
Critics suggest that there is too much emphasis on
mechanistic causal forces (Ley 1983). Unlike competition in
the animal world, human actions are subject to laws,
institutions, and conventions (Cadwallader 1985). The
theory also fails to account for sentiment and social values
which may be important in the determination of land use
(Murphy 1966, Ley 1983, Light 1983).
Other criticisms are directed at the models. It is
charged that they are too simplistic and lack universality
(Ley 1983). They exaggerate rigid land-use boundaries which
cannot be proven empirically (Murphy 1966, Ley 1983). Also,
the homogeneity of the various zones and sectors has been
questioned (Ley 1983). "But the very fact that controversy



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PAGE 188

81,9(56,7< 2) )/25,'$


94
SEMINOLE COUNTY
Dstonci Id Nodi (taifa of mill)
0 X
Incorporated Unincorporated Incorporated Unincorporated
Figure 12. Regression lines for incorporated and
unincorporated multi-family housing planning
data


125
differentiating urban, rural, and fringe areas. It also
suggested that the distance from an arbitrary urban node is
a good predictor of urban and rural characteristics,
especially when density data are used.
The regression analyses demonstrated considerable
difference between the results obtained by using absolute or
planning data values and those acquired through evaluation
of density data. Thus, the data used in local decision
making, which do not compensate for differences in traffic
zone size, may be subject to misinterpretation. For
example, a developer, using planning data results, may
choose to develop a project at 11.84 miles from the node,
expecting the project to be at the fringe of the rural and
urban areas and, therefore, less expensive to develop. The
density data results show, however, that the fringe is
located at 15.59 miles. As a result, the developer would
locate in an area where the property values are higher.
The regression analyses of the density data showed a
stronger correlation between the population variables and
distance from the node than did the planning data. These
analyses show the existence of urban and rural areas and
support a distance-decay function of the variables within
the density data sets. Because of the gradients within the
data sets, they also suggest the existence of a rural-urban


119
Nevertheless, the results of the analysis of the
planning data show striking similarities between the urban
and rural parts of the county. The population average per
traffic zone is 1,017 for incorporated areas and 1,038 for
unincorporated (see Table 3). There are an average of 291
single-family homes in incorporated areas and 336 in
unincorporated (see Table 4). In incorporated areas there
are 2.53 persons per household and in unincorporated 2.84
(see Table 6). Resident employment is 403 for incorporated
and 397 for unincorporated (see Table 7). Income in
incorporated areas averaged $19,819, while in unincorporated
areas it was $22,726 (see Table 10).
Based on these results, which are commonly used in
the daily planning decisions in the Seminole County area,
the area exhibits a remarkable homogeneity. When the data
are adjusted, however, by standardizing traffic zone size
the homogeneity wanes. Population density for incorporated
TZs is more than double that of the unincorporated (see
Table 3). The average density of single-family homes drops
from 411 in incorporated traffic zone to 231 in
unincorporated. Attendant and retail employment are more
than four times greater in incorporated areas than in
unincorporated (see Tables 8 and 9) and resident employment
is almost three times greater (see Table 7). Incorporated


110
SEMINOLE COUNTY
Incorporated Unincorporated Incorporated Unincorporated
Figure 20. Regression lines for incorporated and
unincorporated retail employment density data


130
exists, especially in Central Florida, will only be answered
when data which specifically address land use are collected
and analyzed.


35
and real-estate agents may influence the direction of high-
rent growth (Palm 1981).
Multiple-nuclei model
The concept of the multiple-nuclei forms of the city
evolved from studies by R. D. McKenzie (1939), author of The
Metropolitan Community. It was elaborated by Harris and
Ullman in 1945. In this model, a separate function for each
nucleus from one metropolitan area to another is specified.
The relationship of urban ares is derived from a clear
distinction between the central business district and other
identifiable areas (Palm 1981, Jordan and Rowntree 1982,
Light 1983) .
Harris and Ullman identified four factors which they
believed caused the emergence of separate nuclei in urban
land use:
1. The interdependence of certain types of
activities and their need to be located in
close proximity
2. A natural clustering tendency among certain
types of activities
3. A repetition of certain types of activities.
and


81
2. GraphicalTwo graphs in the form of
scattergrams are presented for each
variable. The first is based on planning
data, while the second is based on density
data.
PopulationDistance Relationships
The statistical findings in Table 3 describe the
relationships between population and distance to the urban
node for each of the six traffic zone data sets. Several of
these are of particular interest.
The R2 values suggest little systematic association
between traffic zone population and distance from the node
in any data set. It is clear, however, that by adjusting
the planning data for traffic zone sizethat is, converting
p
the planning data to density data--higher values for R are
achieved.
The slope of the regression line is negative, as
expected, indicating that the greater the distance from the
node, the smaller the population. This relationships exists
for all six data sets, but it is more pronounced in the
three density data sets (see Table 3 and Figures 7 and 8).
The ranges shown in the planning data results
represent the differences between the highest and lowest
absolute traffic zone populations, while the ranges within


116
Based on the 95-percent confidence level of the
F-test, a model of the population characteristics of the
individual variables would exhibit in most instances a
distance-decay gradient as suggested by Alonso (1971, 1983)
and Pryor (1971), and as expected in this study. It also
suggests that different variables show the existence of a
fringe area at varying distance from the urban node.


66
1. Census tracts are generally too large to use
for detailed data analysis, especially in
the unincorporated areas (see Figure 5), and
2. The Census is based on a decennial count and
detailed information becomes available only
several years after each enumeration. The
TZ data, by contrast, is completed and
reviewed every five years and has a 20-year
planning horizon (Price 1987)
While traffic zones are smaller units than census
tracts and some of the TZ data are derived from census
materials, aggregations of TZs do not correspond necessarily
with census tracts (see Figures 4 and 5). This is because
of a difference in philosophy between the U.S. Census Bureau
and the Federal and State Departments of Transportation.
Census tracts, blocks, and enumeration districts do not
split neighborhoods and have a primary function of grouping
like areas. On the other hand, transportation data are
based primarily on street networks. The splitting of
neighborhoods is a common feature of traffic zones in
Seminole County (Price 1987).
Another common feature of the TZs in Seminole County
is that they are not based on density, even though the
Federal Highway Administration Study (1977) defining traffic
zones suggests that density be considered (see Table 2). In


102
SEMINOLE COUNTY
Distonci to Nodi (tonltis of mito)
0 o x v
Incorporated Unincorporated
Incorporated
Unincorpora ted
Figure 16. Regression lines for incorporated and
unincorporated resident employment density data


SEMINOLE COUNTY
0X9
Incorporated Unincorporated
Incorporated
Unincorporated
gure 18. Regression lines for incorporated and
unincorporated attendant employment density data


14
Figure 2.
Counties included in the Orlando Metropolitan
Statistical Area and the Orlando Urban Area
Metropolitan Planning Organization


84
SEMINOLE COUNTY
Dtonci lo Modi (tafo of mili)
O X
I
Incorporated Unincorporated Incorporated Unincorporated
Figure 8. Regression lines for incorporated and
unincorporated population density data


25
immediately available source of urban and rural information.
Therefore, whether or not they are based on adequate
definitions, these data will continue to be used for much of
the recent research in the United States.
International Definitions
If comprehensive definitions of urban and rural for
the United States have proven elusive, such definitions at
an international level have been impossible. Numerous
problems have been encountered which negate an international
consensus of criteria for urban and rural. In most cases,
comparable data are simply not available. Many countries
lack the skills necessary to collect detailed information,
while others do not deem detailed census data a national
priority either for economic or cultural reasons. Also,
where the data are available, there is often inconsistency
of nomenclature and of geographic bounding of urban areas
between countries. The result is a "bewildering variety of
definitions of 'urban' and 'rural'" (United Nations
Secretariat 1975:18).
By describing just one of the problems, that of data
comparability, it becomes easy to understand why the United
Nations has allowed that standard international definitions
of urban and rural are not, and may not be, possible (Lang
1986). The problem of comparable data is illustrated in two


68
fact, according to regional, county, and city planners, no
calculations of area in various traffic zones in Seminole
County have ever been made (Delk 1987, personal interview;
Gilbrook 1987, personal interview; Grovdahl 1987, personal
interview; Heaton 1987, personal interview; Marder 1987,
personal interview; Nagle 1987, personal interview; Price
1987, personal interview; Ross 1987, personal interview;
Thompson 1987, personal interview; Weaver 1987, personal
interview; Wells 1987, personal interview).
There will be one exception in the future. The
planner in Winter Springs, one of the seven cities in the
county, intends to use Census data and density figures in
the city's Comprehensive Plan Update. The Winter Springs
Planning Department, which in 1987 is just beginning to
receive detailed 1980 Census data, plans to use block data
cross-referenced with Seminole County Traffic Zone data. It
also intends to calculate densities for population, housing,
and employment all to be used in future planning (Koch
1987 ) .
Use of the Traffic Zone
in the Present Study
The traffic zone was chosen as the areal unit in
this study because it is the unit used most often by
planning agencies in Seminole County. In addition, it is
the unit on which the socioeconomic variables generated by


8
5. Outlying noncontiguous areas where the
required dwelling unit density located
within 1.5 miles of the primary contiguous
urbanized portion, as measured by the
shortest connecting highway, as well as by
other outlying areas within 0.5 mile of said
noncontiguous areas "which meet the minimum
residential density rule" (U.S. Bureau of
the Census 1952:xiv).
The Extended City
In 1970, another concept, that of the "extended
city," was recognized. An extended city is a city whose
incorporation boundary has been expanded to include
substantial territory which is rural in character. Only the
urban parts of an extended city are considered the central
city if such a designation applies (U.S. Bureau of the
Census 1972, 1982).
As has been shown, recent Census definitions of
urban, which include the urban fringe, have become more
complex and more specific than previous definitions. While
there is a continued reliance on corporate boundaries and
minimum population, other factors, such as population
density and dwelling-unit density, are now considered,
especially in the definition of the urban fringe.


49
The data show the "best predictor" of loss of farmlands,
based on statistical analysis, was the frequency of part-
time farmers. The fact that large-scale farms were not
being managed and operated by full-time farmers appeared, in
this area, to be most indicative of the decline of the rural
farming business. Crewson and Reed (1982:359) conclude that
"[t]he percentage of part-time farmers is increasing
steadily because off-farm income is vital to the maintenance
of the economic viability of farming today." Thus, the loss
of farmland in this particular study area is attributed
ultimately to an economic factor.
Certainly economic factors were important in Hart's
study of rural Tand-use change in the southeastern United
States (Hart 1980). In describing the demise of a major
cash cropcotton--Hart outlined the evolution of once-
great agricultural holdings in the Piedmont counties of
Georgia and South Carolina. A pronounced change in land use
occurred between 1939 and 1974. During that period, nearly
4-1/2 million acres of productive farmland and 1-1/3 million
acres of cleared land were sold by farmers to nonfarmers
(Hart>1980:492). One reason for the transfers of ownership,
particularly those which involved subdivision for
development, was demonstrated in the answers Hart received
when he asked about the value of land in Carroll County,
Georgia. He was told that "old, worn-out cotton land was


28
By contrast, some countries require official
bounding for urban designation. Argentina, for example,
considers an area urban if its population is 2,000 or
greater and it has official boundaries. All other areas,
regardless of population concentration, are rural (Wander
1975). India classifies legally recognized cities and towns
with populations of 5,000 or more as urban if they also have
a population density of 1,000 per square mile and three-
quarters of those employed work in other than the
agricultural sector of the economy (Bose 1975, Wander 1975,
Jordan and Rowntree 1982).
Still other countries define urban areas "in terms
of minor civil divisions . which have fixed boundaries
and some local government status" (Wander 1975). Until the
1960 Census, only "shi," cities with populations of 30,000
or more, were recognized as urban in Japan. The rest of the
country was considered rural, or "gun." However, as in
Extended Cities in the U.S. Census, "shi" often contained
extensive areas which might better be classified as rural so
the Japanese Bureau of Statistics devised the concept of
Densely Inhabited District (DID). A DID is defined as any
area of contiguous enumeration districts with a population
of 5,000 or more and a density of at least 4,000 persons per
square kilometer. The grouping of enumeration districts


95
SEMINOLE COUNTY
Distonc* to Nod* (twttis of mil*)
0 0 X V
Incorporated Unincorporated
Incorporated
Unincorporated
Figure 13. Regression lines for incorporated and
unincorporated multi-family housing density data


I certify that I have read this study and that in my
opinion it conforms to acceptable standards of scholarly
presentation and is fully adequate, in scope and quality, as
a dissertation for the degree of Doctor of Philosophy.
Earl Starnes
Professor of Urban and
Regional Planning
This dissertation was submitted to the Graduate Faculty of
the Department of Geography in the College of Liberal Arts
and Sciences and to the Graduate School and was accepted as
partial fulfillment of the requirements for the degree of
Doctor of Philosophy.
December 1987
Dean, Graduate School


121
the 95-percent confidence interval (see Table 12). Twelve
of the fourteen cases which did not prove significant were
based on the absolute traffic zone counts of the planning
data. Only two density data regression analyses,
unincorporated multi-family housing and unincorporated
retail employment, had F-values which were not significant
at the 95-percent confidence level. Thus, 92 percent of the
density data regression analyses, compared to only
50 percent of the planning data analyses, show significant
relationships between the variables and distance.
Within each major data set, the regression lines for
the incorporated and unincorporated data of each variable
were overlain. The value of the intersections of these two
lines represents the distance from the urban node at which
the data of the variable become more rural than urban in
character. These values, more than any of the other
results, show the marked differences between the planning
and density data (see Table 13).
A comparison of the value of the planning data
intersection with that of the density data intersection for
individual variables suggests that those variables which are
most urban have the smallest difference between the two
values. Thus, the differences between the two intersections
for multifamily housing, population, and resident employment
are less than 4.2 miles, while the differences between the


UNIVERSITY OF FLORIDA
3 1262 08557 0207


31
In 1946, Rodehauer defined the rural-urban fringe as
"that area in which the land is utilized in an urban manner,
while at the same time certain attributes of the rural area
are present" (Rodehauer 1946:50). This general description
continues to be quoted in the literature (Fesenmaier et al.
1979).
Russwurm's study (cited in Fesenmaier et al. 1979)
differentiated a rural-urban fringe based on density of
population and the presence or absence of farming. He
specified that 50 percent or more of the fringe population
should be nonfarming individuals and that in the large
Canadian urban areas with populations of 100,000 or more,
the fringe should be more than 10 miles wide.
During the same year, 1971, Pryor suggested the
following detailed definition:
The rural-urban fringe is the zone of transition in
land use, social and demographic characteristics, lying
between (a) the continuously built-up urban and suburban
areas of the central city, and (b) the rural hinterland,
characterized by the almost complete absence of nonfarm
dwellings, occupations and land use, and of urban and
rural social orientation; an incomplete range and
penetration of urban utility services; uncoordinated
zoning or planning regulations; areal extension beyond
although contiguous with the political boundary of the
central city; and an actual and potential increase in
population density, with the current density above that
of surrounding rural districts but lower than the
central city. These characteristics may differ both
zonally and sectorally, and will be modified through
time. (Pryor 1971:62)


16
increase in the urban population (U.S. Bureau of the Census
1982). The percentage of rural residence decrease is second
only to Pinellas County, while the percentage of urban
residence increase is the third greatest in the state.
With 603.2 persons per square mile, Seminole County
was the sixth most densely settled county in Florida in
1980. It also experienced the seventh greatest percentage
of population increase114.8 percent, between 1970 and 1980
when the population rose from 83,692 to 179,752 (see
Table 1) .
Despite the county's seemingly dense population and
high percentage of population increase, the population is
not evenly distributed. There are some sections of the
county which appear clearly urban, others which seem rural,
and still others which may not fit in either category. Yet,
the Census has separated the population, and thus the land
area, into rural and urban contingents based solely on
incorporation lines, population size, and/or population
density. These may not be the most important and diagnostic
criteria for such classifications. While the "city wall"
incorporation limits may differentiate urban from rural for
carrying out governmental policy, other definitions of urban
and rural must now be considered. A functional definition,
particularly in high-growth areas such as Central Florida,
is required. Areas well beyond incorporation limits often


57
Attempts to measure change at the local level are
often stymied by lack of definition, data, and technique.
Census definitions are vague. Census data based on those
definitions are not available in the format necessary for
detailed local planning. For example, while detailed data
in census block form are available in urbanized areas, only
census tract data, which encompass a much larger areal unit
of measurement, exist for nonurban areas. Thus, if
comparisons are to be made using census data, only the
larger census tract material can be used. Technique depends
on time, money, data, and knowledge available to the
investigation. Local planning efforts often suffer as the
result of these limitations.
Planning staffs in rapidly growing Seminole County
have attempted to overcome data discrepancies by using
Regional Planning Council (RPC) data which are divided into
traffic zone units instead of census tracts or blocks. The
present study of urban, rural, and rural-urban fringe in
Seminole County will also use RPC traffic zone data, both in
original form and with modifications.


38
information about what actually existed in the city rather
than preconceived notions derived from earlier descriptive
models.
Criticisms of social area analysis
Much of the criticism of social area analysis hinges
on its theoretical background. The theory espoused by
Shevky and Bell suggests that, since society produces the
city, any understanding of the social forms of the city must
be "within the context of the changing character of the
larger containing society" (Shevky and Bell 1955:3). The
three constructs represent broad characterizations of that
society (Ley 1983).
The theory does little to explain differences and
similarities between residential areas (Cadwallader 1985).
Nor, does it address the understanding of the "process of
residential or social patterning of a city" (Cutter
1985:21). It also does not justify the use of the three
particular constructs (Palm 1981, Cadwallader 1985).
The methodology is described as unsophisticated and
the selection of variables which are used for the constructs
has been questioned. It is also suggested that the
variables do not test the empirical validity of the
constructs (Palm 1981, Cadwallader 1985).


148
Traffic
Resident
Employment/
Attendant
Attendant
Employment/
Zone
Square Mile
Employment
Square Mile Income
10
177.94
56
41.18
S20.779.00
11
121.34
56
34.15
S20.779.00
12
69.55
125
56.82
S20,779.00
13
209.82
440
392.86
S20.779.00
14
201.14
20
22.73
S20.779.00
15
137.76
410
418.37
S20.779.00
16
132.29
693
721.88
S20.779.00
17
167.86
455
325.00
S19,397.00
18
150.00
25
29.76
S19,397.00
19
288.64
65
147.73
S19,397.00
20
190.00
69
40.59
S19,397.00
21
11.97
1505
1059.86
S19,397.00
22
9.41
0
0.00
S19.397.00
23
196.04
137
67.82
S19,397.00
24
317.54
839
735.96
S15.271.00
25
747.73
181
411.36
S15.271.00
26
900.00
247
425.86
S14.538.00
27
777.55
343
350.00
S9.469.00
28
848.21
276
492.86
S19.356.00
29
696.15
130
125.00
S19,356.00
30
81.10
60
36.59
S16.777.00
31
12.26
122
115.09
S16.777.00
32
67.54
474
415.79
S16.777.00
33
192.94
570
335.29
S16.777.00
34 .
30.80
48
19.20
S16.777.00
35
11.18
221
130.00
S6.481.00
36
786.76
325
477.94
S6.481.00
37
1244.83
280
482.76
S6,481.00
38
963.64
257
1168.18
SIO.500.00
39
1105.56
61
169.44
SI0,500.00
40
912.50
726
1815.00
S14.716.00
41
79.50
522
261.00
S14.716.00
43
3.91
1252
978.13
S14.716.00
44
410.68
987
479.13
S16.897.00
48
876.43
41
29.29
S14.517.00
49
1162.00
151
302.00
S17.453.00
50
125.00
336
120.00
S17.453.00


APPENDIX
SOCIOECONOMIC DATA1980


(Thou.ondi)
91
SEMINOLE COUNTY
Dtsionci Id Modi (finita of mili)
0X7
Incorporated Unincorporated Incorporated
Unincorporated
Figure 11. Regression lines for incorporated and
unincorporated single-family housing density
data


sincere appreciation goes to Sofia Kohli for editing and
word processing this dissertation.
I wish most of all to express profound gratitude to
my wife, Jeanne Fi1lman-Richards, who always listened,
supported, and put up with the things necessary to complete
this work.
IV


10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
43
44
48
49
50
133
Distance From
Node
Area/
Populat
(Tenths of Mile)
Square Miles
(1980
42-0
1.36
635
50.0
1.64
520
62.0
2.20
401
70.0
1.12
615
69.0
0.88
463
76.0
0.98
351
80.0
0.96
464
94.0
1.40
562
85.0
0.84
302
86.0
0.44
401
77.0
1.70
777
75.0
1.42
40
88.0
2.02
45
93.0
2.02
951
104.0
1.14
900
109.0
0.44
818
115.0
0.58
1342
113.0
0.98
2063
99.0
0.56
1308
105.0
1.04
1992
98.0
1.64
329
105.0
1.06
33
113.0
1.14
189
117.0
1.70
812
127.0
2.50
190
130.0
1.70
56
123.0
0.68
1597
117.5
0.58
2154
123.0
0.22
522
124.5
0.36
959
125.5
0.40
809
124.5
2.00
353
134.5
1.28
io
137.5
2.06
2011
126.5
1.40
3280
120.0
0.50
1321
112.8
2.80
797


CHAPTER III
METHODOLOGY
The review of literature in Chapter II shows that
current definitions of urban, rural, and rural-urban fringe
are inadequate and many of the models and analyses upon
which current research is based do not address the
fundamental issue of distinguishing characteristics of rural
and urban. Yet economic, political, and administrative
decisions often depend on whether areas are "defined" as
rural or urban.
At present, decisions, particularly in high-growth
areas such'as Seminole County, are often made on the basis
of a regional data set which may or may not reflect
characteristics of rural and urban. This study examines,
through various statistical analyses, the utility of one
such data set in differentiating urban and rural populations
and areas .
The data set selected for study is generated by the
East Central Florida Regional Planning Council (1984).
Instead of the more widely used census tract, the geographic
base for the data set is the traffic zone, a unit which was
originally set up for transportation planning.
58


63
Since county participation was required if federal and state
transportation funds were to be allocated, directions were
given for creating TZs for both "developed land . [and]
the undeveloped land that the urban area will encompass in
the next 20 to 30 years" (U.S. Federal Highway
Administration 1977:2-2).
As early as 1963, the East Central Florida Regional
Planning Council staff converted all census tract data into
traffic zones. The conversion of data was based on
allocation of Census data to smaller areas and while traffic
zones could be made up of block data, more often it
corresponded with road networks and not neighborhoods.
These data were based on collective county/city policy, but
did not change the state population figures. Thus,
socioeconomic data from the 1960 Census were converted into
TZs, which became the standard geographic base. These data,
initially, applied only to the Urban Transportation Planning
Process (UTPS) (Heaton 1987).
Use of Traffic Zones in
Seminole County
While traffic zones were developed initially for
federal and state transportation planning, they have been
adapted for use in comprehensive planning in Seminole County
(see Table 2 and Figure 4). They are used instead of census
tracts as a geographic base because


1
2
3
4
6
7
8
45
46
47
58
64
65
66
67
79
80
81
104
106
107
108
109
110
121
122
159
161
162
163
164
165
180
181
5
9
137
Density Single
Population/ Family
Area
Housing
41.61
252
292.19
198
146.25
264
312.50
243
29.74
39
65.65
89
283.65
167
19.08
41
0.49
1
1459.29
680
420.00
64
40.69
221
40.89
500
18.69
95
8.70
70
132.80
190
201.44
179
186.30
100
191.38
44
37.30
21
14.44
6
179.85
68
133.00
53
3467.05
943
778.18
499
4985.42
728
1146.88
701
388.66
738
1617.86
727
2250.96
1368
1301.11
742
800.00
223
3028.75
782
878.23
391
47.45
83
4.81
2
Single Family
Multi-
Housing/
Family
Square Mile
Housing
21.36
8
103.13
5
55.00
7
121.50
8
8.41
0
18.09
4
80.29
2
8.23
0
0.49
O
485.71
27
80.00
3
14.09
6
14.05
19
6.62
6
2.68
io
43.58
2
64.39
2
68.49
4
75.86
0
16.67
2
6.67
0
50.75
4
53.00
O
1071.59
23
226.82
8
1516.67
238
438.13
12
126.80
7
519.29
44
657.69
22
412.22
0
218.63
44
977.50
16
315.32
11
21.17
3
1.92
O


71
For each of the traffic zones a centroid has been
estimated, which is used to calculate the distance to a
common point located at State Road 436 and Interstate 4 in
the major urban center of Altamonte Springs. This area was
chosen as the urban node because it is the economic and
transportation focal point for Seminole County and is
adjacent to Orange County and in close proximity to the City
of Orlando (see Figure 6).
Of the 181 traffic zones in Seminole County, 175
zones were used in this research. Six zones were deleted
because population data were recorded as zero and they would
have produced questionable analysis results.2
Definitions of the Variables
The variables used in the present study include
(1) population, (2) single-family housing, (3) multi-family
housing, (4) resident employment, (5) attendant employment,
(6) retail employment, (7) median family income, and
(8) persons per household. The data for the first
seven of these variables were obtained from the
o
Of the traffic zones which were omitted, three82,
85, and 160--were agricultural or vacant land in 1980. The
other three42, 124, and 137--were totally industrial
retail or commercial retail areas. These traffic zones are
small and scattered throughout Seminole County.


12
comprehensive plans which outline growth and development
guidelines, transportation documents that give direction to
federal, state, and local roadway plans, grants for housing,
capital improvements, property acquisition, and local
governmental policy.
Purpose of Research
Efforts to locate precisely and predict urban,
rural, and fringe areas are often hindered because the
process and characteristics of urbanization in rapidly
developing rural areas are poorly understood. The purpose,
then, of the present research is to analyze urbanization in
a rapidly developing rural area, to improve the
understanding of the characteristics associated with rapid
urbanization, and to contribute to a better definition of
the rural-urban fringe.
Study Area
The geographic focus of this study, Seminole County,
is located in Central Florida adjacent to Orange, Lake, and
Volusia Counties (see Figure 1). It is included, along with
Orange and Osceola Counties, in the Orlando Metropolitan
Statistical Area (MSA) and the Orlando Urban Area
Metropolitan Planning Organization (OUAMPO) (see Figure 2).
Seminole County was selected as the study area
because it is exhibiting several signs of rapid


165
Yamaguchi, T.
1984 The Japanese National Settlement Systems. In
Urbanization and Settlement Systems: International
Perspectives. L. S. Bourne, R. Sinclair, and K.
Dziewonski, eds. Pp. 261-279. New York: Oxford
University Press.
Yeates, M.
1987 The Extent of Urban Development in the Windsor-
Quebec City Axis. The Canadian Geographer 3JL ( 1 ): 64-69 .
Zeimetz, K. A., E. Dillon, E. E. Hardy, and R. C. Otte
1976 Dynamics of Land Use in Fast Growth Areas.
Economic Research Service. United States Department of
Agriculture. Agricultural Economic Report No. 325.


5
States were included if they contained one village with a
population of 2,500 or several villages whose combined
population was greater than 50 percent of the total
population of the township. In other states, townships, or
other political subdivisions, were included if they had a
population of 10,000 and a density greater than 1,000
persons per square mile (U.S. Bureau of the Census 1913,
1923, 1933, 1942). Thus, the 1910, 1920, 1930, and 1940
Census definitions of urban were based almost entirely on a
combination of incorporation lines and a minimum population
standard. There was only peripheral recognition of some
areas which were equally populous or densely settled, but
remained unincorporated.
By 1950, growing concern with a more precise
separation of urban from rural fostered major additions to
the basic Census definition of urban. For the first time,
the term "urban territory" was used and the concepts of
"places," "urbanized areas," and "urban fringes" were
included. These terms have to be described in detail
because they continue through the 1980 Census, with only
minor revisions, to be the basis for most urban, rural, and
urban-rural fringe determinations in the United States.
The 1950 Census defines the urban territory as
incorporated places with populations of 2,500 or more, the
urban fringe around cities with 50,000 or more inhabitants.


103
or retail, there is nothing to give clear evidence of rural
or urban.
Attendant Employment--Distance Relationships
There is only an extremely weak relationship between
attendant employment and distance form the urban node. The
p
R value for planning incorporated data, .000 indicating no
relationship, is raised only slightly to .101 by adjusting
the data for density. Similarly, the R2 values for the
unincorporated traffic zones are only .066 for planning data
and .131 for density data (see Table 8).
The slope of the regression lines for each of the
six data sets is negative. The regression lines for
incorporated and unincorporated planning data diverge with
increasing distance from the urban node (see Table 8 and
Figure 17). Regression lines for the same data, adjusted
for density, however, intersect at 14.62 miles from the
urban node (see Table 8 and Figure 18). Thus, adjusting for
density does differentiate urban and rural using this
characteristic even though the R2 values are quite low.
Retail Employment--Distance Relationships
Retail employment is a subset of attendant
employment and shows characteristics similar to those of
attendant employment. The R2 values which range from .001
to .096 indicate a weak relationship between retail


RURAL-URBAN FRINGECONTINUUM OR DICHOTOMY?
A STUDY OF THE HIGH-GROWTH AREA,
SEMINOLE COUNTY, FLORIDA
By
STORM L. RICHARDS
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
1987


112
lines would eventually cross somewhere outside of the study
area, that is, outside of Seminole County (see Table 10 and
Figure 21). The regression lines for incorporated and
unincorporated data which have been adjusted for density,
however, cross within the county at 12.60 miles from the
urban node (see Table 10 and Figure 22).
Conclusions
Each regression has been subjected to an F-test to
determine if distance from the node (x) can be used to
j -: : the value of the socioeconomic variables (y). The
results of these tests (see Tables 3-10) show that the model
was useful for predicting y in 34 out of 48 cases. For
example, population did decrease in a predictable fashion
with distance from the urban node.
While the F-test analyzes the relationship between
distance and a specific socioeconomic variable, the Z-score,
or the comparison between means, determines the
comparability of the separate populations within a variable.
This test was employed in the present study for the density
data populations of each variable. The comparisons showed
that the unincorporated and incorporated populations in each
case are different at the 99 percent confidence level (see
Table 11).


50
worth about $150 to $200 an acre for forestry. Farmers were
paying $600 to $700 an acre for such lands. Realtors . .
[said] that the price of five-acre lots in the northeastern
half of the countythe side toward Atlantabegin at around
$7,000 . ." (Hart 1980:525).
A national study of farmland loss conducted by the
U.S. Department of Agriculture (Zeimetz et al. 1976) found
that, in general, factors other than urbanization accounted
for the majority of cropland loss. In particular, marginal
croplands were converted to pasture and other agricultural
lands were idled as new technology made farming of those
areas uneconomical (Zeimetz et al. 1976:ii).
Plaut (1976) states that many researchers agree that
the direct conversion of agricultural land to urban uses
does not have a significant impact on amount of land devoted
to farming at a national level. Despite this commonly held
belief, it is well to keep in mind Hart's observation (1980)
that land which is fallow may be returned to production at
some time in the future, but that subdivision and
development of rural lands results in irreversible change.
There are indications that such change is occurring in the
rural-urban fringe of high-growth areas.


146
Multi-Family
Persons
'raf f ic
Housing/
per
Resid
Zone
Square Mile
Household
Employ
145
80.00
2.10
268
146
21.67
2.44
203
147
82.00
2.26
361
148
84.09
2.57
409
149
82.14
3.02
1078
150
7.69
2.60
29
151
0.00
2.55
84
152
15.79
3.00
253
153
23.21
3.04
412
154
9.52
3.34
920
155
237.84
2.74
968
156
4.76
3.00
32
157
0.00
3.03
494
158
0.00
3.07
631
166
25.56
3.26
758
167
88.00
2.97
516
168
189.77
3.27
1341
169
487.50
2.76
483
170
142.62
2.76
576
171
240.00
2.25
285
172
434.78
3.01
1062
173
2761.76
1.66
605
174
545.45
2.64
469
175
0.00
3.36
835
176
0.00
3.18
266
177
240.00
2.86
83
178
1.18
3.04
92
179
494.05
2.79
485


55
relatively high incomes. In fact, the median family income,
$20,873, was the highest in the state in 1980 (Kemp 1985).
Most of the new construction is in smaller
developments located generally in the southern part of the
county. Two larger "urban villages," however, are in the
first phases of growth. Earlier this year, 1987, South
Seminole Corporation paid $12 million for a 783-acre tract
of long-idle rural land in south central Seminole County.
The area, Alafaya, will contain 3,835 homes and 65 acres of
office and retail space (Snyder 1984).
The second urban village, Heathrow, adjacent to
Interstate-4 in the northwest quadrant of the county, covers
1,248 rural acres. In addition to 4,000 houses, the
development will have a shopping center and several hundred
thousand square feet of office space (Snyder 1984). This
development has already attracted the national headquarters
of the American Automobile Association and others are
expected to follow.
Conclusion
There exists at present no satisfactory definition
of either rural or urban. In the United States, the
definitions set out by the Bureau of the Census are most
frequently used, but other countries define rural and urban
by their own standards so that definitions are rarely


Table 4
Single-Family Housing and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
. 026
.111
. 009
. 079
. 150
. 209
Intercept
(Constant)
370
599
331
605
554
502
Slope
-1.02
-3.24
-0.60
-3.00
-2.55
-3.16
F-value
4.64
21.76
1.26
11.96
5.66
8.46
Range
1,368
1,737
1 100
1,737
1,367
1,516
Average (Mean)
300
376
291
411
336
231
Value of
Intersection

11 .
44 miles -
64.38 miles3 11
.44 miles
-64.38 miles3
aThe resultant
distance is
outside of
Seminole
County.


Figure 9.
Major transportation arteries in Seminole County


/
Figure 5. Seminole County census tracts


159
Cutter, S. L.
1985 Rating Places: A Geographer's View on Quality of
Life. Resource Publications in Geography. Washington,
DC: Association of American Geographers.
Dennis, R., and H. Clout
1980 A Social Geography of England and Wales. Oxford:
Pergamon Press.
Dunleavy, P.
1982 The Scope of Urban Studies in Social Science. In
The Urban Perspective. Pp. 1-71. Milton Keynes: The
Open University.
East Central Florida Regional Planning Council
1984 The Orange-Seminole-Osceola Statistical Dataz 1980
2005. Orlando: East Florida Regional Planning Council
Everitt, J.
1984 Influences on Land Use Change in the Urban Fringe:
The Case of Surrey, British Columbia. Geographical
Perspectives 53 (Spring):114.
Fesenmaier, D. R., M. F. Goodchild, and S. Morrison
1979 The Spatial Structure of the Rural-Urban Fringe:
A Multivariate Approach. The Canadian Geographer
23(3) : 255-265.
Furuseth, 0. J., and J. T. Pierce
1982 A Comparative Analysis of Farmland Preservation
Programmes in North America. The Canadian Geographer
26(3):191-206.
Goldstein, S., and D. Sly, eds.
1975 Basic Data Needed for the Study _of Urbanization.
Dohain, Belgium: Ordina Editions.
Harris, C. D., and E. L. Uilman
1945 The Nature of Cities. Annals of the American
Academy of Political and Social Science 24 2 : 7-17.
Hart, J. F.
1980 Land Use Change in a Piedmont. Annals of the
Association of American Geographers 70(4 j:492-527.
Healy, R. G.
1985 Lots or Crops: The Land Supply Dilemma. Urban
Land 44(2):34-35.


72
Orange-Seminole-Osceola Statistical Data, 1980-20053 (East
Central Florida Regional Planning Council 1984). Persons
per household was calculated by the author because it is
commonly used for planning purposes.
The variables are defined by the East Central
Florida Regional Planning Council (1984:vi-x) as
1. Population is defined as the total number of
civilian and military individuals whose
v t
principal residence is in a particular
traffic zone. Excluded from these figures
are seasonal and transient residents.
Population allocations to traffic zones are
based primarily on 1980 U.S. Census data and
the total figures are allocated by Regional
Planning Council, County and City
governmental staff. '
*
2. Single-family housing is defined as the
total number of completed single-family
dwellings and mobile homes, whether they are
occupied or vacant. Not included in the
Two variables listed in the document, hotel/motel
units and school enrollment, grades 1-12, were not used in
this research. Hotel/motel units was excluded because only
20 TZs had more than one unit. While 39 TZs had values for
school enrollment, this variable would only indicate where
schools are since student population is assigned to the
location of the school and not the home.


11
status simply because they are beyond areas with certain
population density limits.
For large-scale, generalized research, the Census
criteria may be adequate. Local research and planning,
especially in rapidly developing areas, however, requires
more precise definitions of urban, rural, and rural-urban
fringe. Unfortunately, such definitions do not exist.
Problem Statement
and Purpose of Present Research
In much of the United States, development is
spilling beyond the incorporation boundaries of cities into
what were regarded as rural areas. The consequences of
rapid urbanization on the countryside are dramatic and, in
some cases, seem almost instantaneous. A recent Wall Street
Journal article (March 26, 1987) described the phenomenon in
the following terms:
From Plano, Texas, to Middlesex County, New
Jersey, from Aurora, Colorado, to Gwinnett County,
Georgia--places once considered rural and idyllic
and far from the central-city blues--the scenario is
the same. Offices and shopping centers shoot up,
subdivisions follow, and it gets harder to tell
urban from suburban from rural. Mini-cities seem to
be everywhere. (Morris 1987:1)
In high-growth areas across the country, urban
researchers, planners, and governmental decision-makers face
the problem of distinguishing urban, rural, and rural-urban
fringe areas. Such information is essential for


83
SEMINOLE COUNTY
Obten ci to Kodi (tinttij of mito)
0 0X7
Incorporated Unincorporated Incorporated Unincorporated
Figure 7. Regression lines for incorporated and
unincorporated population size planning data


126
fringe which is a continuum between rural and urban areas of
the county.
Future Studies of
the Rural-Urban Fringe
Seminole County was selected as the study area
because the county, which historically has had a strong
agricultural, rural economy, has changed dramatically
because of industrial, commercial, and residential growth.
Seminole County, however, is only a portion of the
high-growth area in Central Florida. Orange and Osceola
Counties are also experiencing rapid development. Since,
according to the Regional Planning Council, these counties
do not use density data either, a more extensive study of
the entire area using both planning and density data should
be undertaken.
One purpose of this study was to review critically
the planning data used locally for decision making. In the
future, the planning agencies may find that adding other
variables which more directly represent land use would aid
in differentiating urban, rural, and fringe areas. Such
variables include average daily traffic counts, property
conversion ratios or the number of times property has sold
within a specified time period, percentage of developable
land, and urban service areas.


90
SEMINOLE COUNTY
Distonci te Hod* (tenths of mfto)
0 0 X V
Incorporated Unincorporated Incorporated Unincorporated
Figure 10. Regression lines for incorporated and
unincorporated single-family housing planning
data


13
Figure 1. Seminole and adjacent counties


158
Brotchie, J., P. Newton, P. Hall, and P. Nijkamp
198 5 The Future of Urban Form: The Impact of New
Technology. New York: Nichols Publishing Company.
Brown, H. J., R. S. Phillips, and N. A. Roberts
1981 Land Markets at the Urban Fringe: New Insights for
Policy Makers. Journal of the American Planning
Association 47(2):131-144.
Brown, H. J., and N. A. Roberts
1978 Landowners at the Urban Fringe. Discussion Paper
D78-10. Cambridge: Harvard University. Department of
City and Regional Planning.
Bryant, C. R.
1976 Farm-Generated Determinants of Land Use Changes in
the Rural-Urban Fringe in Canada, 1971-1975. 01tawa:
Environment Canada, Lands Directorate.
1981 Agriculture in an Urbanizing Environment: A Case
Study from the Paris Region, 1968-1976. The Canadian
Geographer 26(1):27-45.
Bryant, C. R., and L. H. Russwurm
1979 The Impact of Non-Farm Development on Agriculture:
A Synthesis. Plan Canada 19:122-139.
Bryant, C. R., L. H. Russwurm, and S-Y. Wong
1981 Census Farmland Change in Canadian Urban Fields,
1941-1976. Ontario Geography 18:7-23.
Burgess, E. W.
1925 The Growth of the City. In The City. R. E. Park,
E. W. Burgess, and R. D. MacKenzie, eds. Pp. 47-62.
Chicago: University of Chicago Press.
Cadwallader, M. T.
19 85 Analytical Urban Geography: Spatial Patterns and
Theories. Englewood Cliffs, NJ: Prentice-Hal1, Inc.
Champion, A. G.
1983 Land Use and Competition. In Progress in Rural
Geography. M. Pacione, ed. Pp. 21-45. Totowa, NJ:
Barnes & Noble Books.
Crewson, D. M., and G. Reeds
1982 Loss of Farmlands in South-Central Ontario from
1951-1971. The Canadian Geographer 26(4 ) : 355-359.


18
exhibit characteristics similar to those in the city, while
areas which appear rural according to a functional
definition and governmental policy may be viewed quite
differently by developers, who base their perspective on
profitability. The present research, therefore, utilizes
alternative types of data which may lead to a clearer
distinction between, and ultimately understanding of, urban,
rural, and rural-urban fringe areas in rapidly developing
sections of the country.
Intent of the Research
The intent, then, of the present research is first
to characterize the various areas of Seminole County,
Florida, using a standard socioeconomic data set derived
from a variety of sources (East Central Florida Regional
Planning Council 1984:v) and which is divided into "traffic
zones" (TZs). Such information is used by regional, county,
and municipal governments as well as planning agencies in
Central Florida. The data include population
characteristics, housing types, employment, income, and
education. (See page 71 in Chapter III.)
Secondly, through the manipulation of the standard
data set, it is possible for areas in Seminole County to be
more clearly defined and designated as rural, urban, or
rural-urban fringe. At present, for planning purposes,


o
Figure 6.
The incorporated cities and urban node of Seminole County


120
income, however, at $17,009 is less than half that of
unincorporated TZ average of $45,370.
Thus, the use of density data instead of planning
data brings about a very different picture of the county.
In fact, the Z-scores of the density data show two distinct
populations, one within incorporated areas and the other in
unincorporated areas, for each of the socioeconomic
variables represented in the density data set. This is
probably the result of the differences in mean distance from
the urban node.
p
The coefficients of determination, R appear to be
low; the values for the density data are, however,
consistently higher than those of the planning data, with,
one exception. Incorporated density data for income had a
p
lower R value than that of incorporated planning data
income (see Table 10).
In all cases, the regression slope of the variables
was negative (see Figures 7, 8, and 10-22). This suggests
that the variables are subject to distance-decay, that is,
the farther the distance of the traffic zone from the urban
node, the less the diagnostic value of the variable.
To determine the "utility" of the model for
predicting socioeconomic values based on distance from the
urban node, F-tests were employed.. These statistics show
that, of the 48 regression analyses, 34 are significant at


Table 1
Seminole County Population, 1930-1980
Year
Population
Percentage
1930 1940 1950 1960 1970 1980
18,735 22,304 26,883 54,947 83,692 179,752
Change/Decade <> 19.0 <--> 20.5 <--> 104.4 <> 52.3 <> 114.8 <>
Total Percentage Change
<
> (50 years) <
> 859.4


BIOGRAPHICAL SKETCH
Storm L. Richards was born at Patuxent River Naval
Air Station, Maryland, in 1950. He obtained his B.A. with
honors in anthropology in 1973 at the University of Florida.
During his undergraduate program, Mr. Richards participated
in a National Geographics-sponsored cultural anthropological
and archaeological project in North Central Vera Cruz,
Mexico.
In 1978, he completed his M.A. in geography at the
University of Florida. During the same year, he began his
studies for a Ph.D. in geography with emphasis on urban and
regional planning. During the course of his studies, he has
also pursued a planning career in both the public and
private sectors. He was employed by the Suwannee River
Water Management District. He was also Principal Planner
for the City of Ocala, Florida; Land Development Co
ordinator for the Navajo Office of Land Development, Window
Rock, Arizona; Senior Planner, Seminole County, Florida; and
Deputy Director for the Seminole County Expressway
Authority. He is employed currently as an environmental
planner and permits coordinator by Greiner, Inc., Orlando,
Florida.
172


113
SEMNOLE COUNTY

I
Incorporated
Oistonci to Modi (tenths of mito)
0 X
Unincorporated Incorporated
V
I
Unincorporated
Figure 21. Regression lines for incorporated and
unincorporated income dollars planning data


Table 8
Attendant Employment and Distance from Node
Combined TZ
Incorporated TZ
Unincorporated TZ
Measurement
Planning
Data
Density
Data
Planning
Data
Density
Data
Planning
Data
Density
Data
n
175
175
141
141
34
34
R2
. 005
. 103
. 000
. 101
. 066
. 131
Intercept
(Constant)
278
704
279
799
178
195
Slope
-0.48
-4.61
-0.06
-5.28
-0.67
-1.15
F-value
0.87
20.19
. 000
15.78
2.26
4.83
Range
1,505
4,391
1,505
4,391
617
610
Average (Mean)
245
386
275
4 55
120
97
Value of
Intersection

-16.
56 miles3
14.62 miles
-16.56 miles3
14.62 miles
aThe resultant
distance is
outside of
Seminole
County.
104


51
Encroachment of urban land uses
onto the rural-urban fringe
While direct conversion of rural lands to urban
purposes is considered of little consequence to the national
agricultural production of the United States, such
conversion along with other effects of urbanization may
produce considerable change in land use within the rural-
urban fringe of rapidly developing urban areas (Plaut 1976).
In fact, urbanization is often considered the dominant
process by which change occurs within the rural-urban fringe
(Plaut 1976, Champion 1983, Everitt 1984).
In 1976, Plaut explored the idea that "urbanization
[has] a substantial impact on the loss of farmland on the
rural-urban fringe" (1976:27). Using regression analysis,
he analyzed the changes in land use in Standard Metropolitan
Statistical Areas in the United States. The variables
included in the analysis were number of housing units built
in the county between 1960 and 1970, class of soil
productivity, age of the farmer, and productivity of
farmlands. Based on this analysis, he determined that there
were strong relationships between land-use change and
urbanization in the rural-urban fringe areas of the Midwest
and Northeast (Plaut 1976).
Another author (Pierce 1981) investigated the rate
of conversion of rural land to urban uses within the


Figure 4.
Seminole County traffic zones


10
because virtually all of that research is based on Census
data.
Several problems with the Census definitions and
data are apparent. Even the 1980 Census acknowledges that
the absolute lower limit for urban designation has caused
consternation among those who inhabit smaller places.
"Within small counties, measurements of urban and rural
populations over time may be significantly affected by the
increase or decrease of a place's population across the
2,500 population threshold, e.g., the increase of 1 person
to a place of 2,499 results in an increase of 2,500 to the
county's urban population" (U.S. Bureau of the Census
1982:51). By the same token, the place itself wavers back
and forth between a rural and an urban designation depending
on the 2,500^ individual.
Other problems are encountered in the urban fringe
criteria for urban areas. Boundaries for the urban fringe
are based on population density and contiguity or proximity
to areas with certain population densities. For example,
industrial and office parks are included in the fringe only
if they are within densely settled areas. Since land use,
even if it would seem typically urban, is not considered, it
is possible to conceive a situation, especially in a rapidly
developing area, where large segments of land devoted to
office, research, or industrial parks are relegated to rural


107
employment and distance from the node (see Table 9). As
with the attendant employment data, the raw data regression
lines diverge as distance from the urban node increases (see
Table 9 and Figure 19). The density regression lines
intersect, however, at 14.65 miles from the urban
node--three-hundredths of a mile farther than the
intersection of the attendant density regression lines (see
Table 9 and Figure 20J.1
IncomeDistance Relationships
Of the eight variables used in the present study,
income shows the strongest relationship to distance from the
O
urban node. The R values range from .286 for incorporated
traffic zone density data to .441 for unincorporated traffic
zone density data (see Table 10).
The incorporated and unincorporated raw data
regression lines converge with distance from the urban node,
but do not cross within Seminole County. Presumably, these
^In an attempt to create more diagnostic and useful
variables, the relationships between the various employment
figures and population per traffic zone were explored.
Retail employment divided by population resulted in
percentages that ranged from 0 percent to 2,000 percent and
R2,s of .02 for incorporated TZs and .01 for unincorporated
TZs. Attendant employment figures varied even more.
Percentages ranged from 0 percent to approximately 15,000
percent and the R2,s were .01 for unincorporated and .04 for
incorporated TZs. Resident employment described TZs where
employment compared to population was from 0 percent to 300
percent and both R2,s were .0.


152
Traffic
Income/
Zone
Square Mile
1
$2,078.14
2
$12,771.88
3
$5,108.75
4
$12,261.00
6
$5,284.91
7
$4,984.15
8
$11,789.42
45
$1,642.57
46
$3,970.87
47
$5,842.86
58
$21,442.50
64
$1,172.39
65
S516.67
66
SI,281.94
67
$675.81
79
$4,785.55
80
$7,505.40
81
$20,711.64
104
$39,374.14
106
$18,124.60
107
$25,374.44
108
$17,674.63
109
$23,684.00
110
S26,913.64
121
$10,011.82
122
$45,887.50
159
S22.974.38
161
$6,315.98
162
$20,475.71
163
$13,781.73
164
$15,925.56
165
S28,103.92
180
$26,747.50
181
S17,256.45
5
$6,255.61
9
$19,979.81


32
After elaborating on his definition of the fringe
area, Pryor states that the characteristics he describes are
not based on empirical evidence. He then calls for further
investigation by other researchers.
Urban Form and Land Use:
Models and Analyses
. . geographers have been chiefly associated with
the description and analysis of urban form. What
theory there is of urban form in geography, however,
is largely derived from other fields. One is urban
sociology, especially the human ecology school of
Chicago (Park, Burgess, and others). Another is
land economics. . .
--Agnew, Mercer, and Sopher 1984:12
In their pursuit of generalizations and laws which
explain and predict urban form and urban and rural land use,
geographers have used a number of models and analyses.
Certain of these have had considerable impact on geographic
thought and continue to be discussed and criticized in the
literature. They include the classical models of urban
form: concentric zone, sector, and multiple nuclei; social
area analysis and factorial ecology; and von Thnen's
agricultural land-use theory and Alonso's land-rent theory.
While none of these studies has dealt directly with the
problem of urban and rural definitions, each has contributed
to a better understanding of the characteristics of urban or
rural areas.


151
Resident
Attendant
Traffic
Employment/
Attendant
Employment/
Zone
Square Mile
Employment
Square Mile Income
145
382.86
782
1117.14
S13.200.00
146
338.33
176
293.33
S22,535.00
147
722.00
470
940.00
S22.535.00
148
929.55
390
886.36
S17.381.00
149
1283.33
290
345.24
S17.381.00
150
27.88
190
182.69
S17.381.00
151
420.00
134
670.00
S25.745.00
152
332.89
249
327.63
S25,745.00
153
735.71
289
516.07
S25,745.00
154
1095.24
60
71.43
S25.745.00
155
1308.11
323
436.49
S25,745.00
156
38.10
405
482.14
S30,828.00
157
504.08
70
71.43
S30,825.00
158
751.19
70
83.33
S30.828.00
166
842.22
417
463.33
S28.666.00
167
1032.00
170
340.00
S25.244.00
168
1523.86
132
150.00
S25.244.00
169
754.69
242
378.13
S25,244.00
170
472.13
450
368.85
S25.244.00
171
570.00
1247
2494.00
S25.244.00
172
2308.70
244
530.43
S20.701.00
173
1779.41
411
1208.82
S20.701.00
174
2131.82
18
81.82
S20.701.00
175
852.04
18
18.37
S20.701.00
176
532.00
560
1120.00
S20.701.00
177
276.67
605
2016.67
S21,398.00
178
54.12
15
8.82
S21,398.00
179
577.38
95
113.10
S21,398.00


22
considerable and specialized body of literature.
Nevertheless, because the boundaries between urban and rural
are often ambiguous and contrived, areas of research within
the separate subfields occasionally overlap. This is
particularly true in the case of rural-urban fringe studies.
The literature reviewed for the present study is
drawn mainly from urban and rural geography; however,
sources from other, closely related disciplines are also
discussed. Sociology, anthropology, and planning each have
urban and rural contingents in which problems of definition
similar to those encountered within geography must be
confronted. The literature review, then, is set out,
regardless of discipline, within the broad themes of urban
and rural.
Urban and Rural Definitions
One technical aspect that causes some concern is
the actual delimitation of geographic areas that can
be regarded as urban. Such delimitation is
necessary, particularly in studies focusing on . .
rural-urban land conversion.
Yeates 1987:64
Because there is no consensus among researchers on
the exact definition of urban, it is difficult to pinpoint
areas, particularly peripheral areas, which are, or may
become, urban. For some urban investigators, this
difficulty in defining specific areas as urban has become a
moot question. In fact, it has been suggested "that the


ra
Zon
98
99
100
101
102
103
105
111
112
113
114
115
116
117
118
119
120
123
125
126
127
128
129
130
131
132
133
134
135
136
138
139
140
141
142
143
144
135
Distance From
Node
(Tenths of Mile) Sq
35.0
31.0
35.5
38.0
44.5
45.5
52.5
61.0
56.0
47.0
50.0
58.5
54.0
51.0
47.5
40.0
34.0
27.0
21.5
23.0
20.0
16.0
12.0
6.0
7.0
11.0
16.0
14.0
3.0
2.0
4.5
12.5
18.5
13.5
22.0
25.0
30.0
Area/
Populat
are Miles
(1980
0.68
622
0.12
449
0.52
1530
0.18
529
0.80
2860
1.52
2314
1.30
1474
2.22
1005
0.98
683
0.44
1765
0.52
240
0.84
3092
0.54
2299
O
05
2019
0.42
1570
0.44
1072
0.42
2131
0.18
856
0.68
480
0.32
953
0.76
1498
0.58
1584
0.22
600
0.14
291
0.28
1207
0.50
1204
0.38
1976
0.42
1041
0.42
1910
3.40
239
0.34
119
0.78
2151
0.70
2205
0.20
615
1.12
1711
0.32
914
0.50
229


ACKNOWLEDGMENTS
My gratitude must first be expressed to the members
of my supervisory committee. I am indebted particularly to
my chairman. Dr. David Niddrie, who has been supportive of
my work for many years. Most important has been his
personal concern for my academic and professional careers.
Dr. Edward Malecki, who has served as cochairman, provided
me with the direction in making the necessary revisions of
this study. For this, and for his seemingly endless
patience, I thank him. Additionally, I would like to
express my gratitude to Dr. Louis Paganini, who taught me
the value of field geography, which has been important in my
professional career. I would also like to thank Dr. Earl
Starnes for his participation in review of my dissertation.
Finally, I should like to thank Dr. William Maples, whom I
have known and respected since I first came to the
University of Florida, for his direction, his support, and,
above all, his honesty.
I wish also to express my gratitude to the
individuals who have worked with and shared my concerns in
completion of this dissertation, including Dr. Kathy Ross,
Dr. Monte Blair, Dr. John Braaksma, and Dick Haury. My
iii


47
Figure 3
RURAL-URBAN FRINGE
Percentage Distance Urban to Rural
0 25 50 75 100
x Boundary of Totally Urban
y Boundary of Totally Rural
Adapted from Pryor 1971
Model describing land use in the rural-urban
fringe


173
Mr. Richards is married to Jeanne Fillman-Richards,
who is also pursuing her doctorate in geography, and they
have a daughter, Emerson Storm Fillman Richards.