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How Does Urban Form Impact the Potential for Children to Walk and Bicycle to School

Permanent Link: http://ufdc.ufl.edu/UFE0024661/00001

Material Information

Title: How Does Urban Form Impact the Potential for Children to Walk and Bicycle to School A Case Study of Orange and Seminole Counties in Central Florida
Physical Description: 1 online resource (93 p.)
Language: english
Creator: Schmucker, Jeffrey
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: design, health, obesity, walkability
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Childhood obesity in the United States has become a national epidemic. One of the reasons that researchers have suggested that this may be occurring is due to a decrease in the amount of physical activity that children are participating in. One solution aimed at increasing physical activity among children, is by providing enhanced opportunities for children to walk and bicycle to school. This study examines how urban form impacts the potential for children to walk and bicycle to school, by examining several characteristics of the built environment around elementary schools within Orange and Seminole Counties in Central Florida. The two primary characteristics used in this investigation are street connectivity and residential density. Within street connectivity, three indicators are used to measure the potential for walkability to school. These indicators include street density, intersection density, and Pedestrian Route Directness (PRD), which is a ratio of the network walking distance to the straight-line distance between two points. Residential density characteristics also use three indicators for measuring potential walkability. These include gross residential density, net residential density, and Effective Walking Area (EWA), which calculates the percentage of residential parcels that are found along a street network. These indicators are compared against four influential development periods which correspond to growth management and school coordination legislation in the State of Florida. These include historic schools built before 1950, pre-growth management schools built between 1950 and 1985, pre-school coordination schools built between 1986 and 1995, and post-school coordination schools built after 1995. The general findings from this study suggest that historic schools built before 1950 and those schools sited after 1995 in Orange County reveal the highest potential for walkability. The general findings in Seminole County reveal the greatest potential for walkability occurring around schools built during the pre-growth management period between 1950 and 1985. By examining the Counties across the four development time periods, there does seem to be a correlation between the patterns of development in Orange County, while the development trends in Seminole County seem to be less apparent, following no coordinated patterns. Developments that are more compact, consisting of more traditional grid-like street patterns and higher residential densities, appear to support greater potential for walking and bicycling. Because the intention of this study was to investigate how urban form impacts walkability, analysis within the four influential time periods was critical, especially in examining how policy factors may be affecting the development of Florida s built environment. Providing a better understanding of how our built environments affect our health is imperative as we plan communities for generations to come.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jeffrey Schmucker.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2009.
Local: Adviser: Steiner, Ruth L.
Local: Co-adviser: Bejleri, Ilir.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024661:00001

Permanent Link: http://ufdc.ufl.edu/UFE0024661/00001

Material Information

Title: How Does Urban Form Impact the Potential for Children to Walk and Bicycle to School A Case Study of Orange and Seminole Counties in Central Florida
Physical Description: 1 online resource (93 p.)
Language: english
Creator: Schmucker, Jeffrey
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2009

Subjects

Subjects / Keywords: design, health, obesity, walkability
Urban and Regional Planning -- Dissertations, Academic -- UF
Genre: Urban and Regional Planning thesis, M.A.U.R.P.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: Childhood obesity in the United States has become a national epidemic. One of the reasons that researchers have suggested that this may be occurring is due to a decrease in the amount of physical activity that children are participating in. One solution aimed at increasing physical activity among children, is by providing enhanced opportunities for children to walk and bicycle to school. This study examines how urban form impacts the potential for children to walk and bicycle to school, by examining several characteristics of the built environment around elementary schools within Orange and Seminole Counties in Central Florida. The two primary characteristics used in this investigation are street connectivity and residential density. Within street connectivity, three indicators are used to measure the potential for walkability to school. These indicators include street density, intersection density, and Pedestrian Route Directness (PRD), which is a ratio of the network walking distance to the straight-line distance between two points. Residential density characteristics also use three indicators for measuring potential walkability. These include gross residential density, net residential density, and Effective Walking Area (EWA), which calculates the percentage of residential parcels that are found along a street network. These indicators are compared against four influential development periods which correspond to growth management and school coordination legislation in the State of Florida. These include historic schools built before 1950, pre-growth management schools built between 1950 and 1985, pre-school coordination schools built between 1986 and 1995, and post-school coordination schools built after 1995. The general findings from this study suggest that historic schools built before 1950 and those schools sited after 1995 in Orange County reveal the highest potential for walkability. The general findings in Seminole County reveal the greatest potential for walkability occurring around schools built during the pre-growth management period between 1950 and 1985. By examining the Counties across the four development time periods, there does seem to be a correlation between the patterns of development in Orange County, while the development trends in Seminole County seem to be less apparent, following no coordinated patterns. Developments that are more compact, consisting of more traditional grid-like street patterns and higher residential densities, appear to support greater potential for walking and bicycling. Because the intention of this study was to investigate how urban form impacts walkability, analysis within the four influential time periods was critical, especially in examining how policy factors may be affecting the development of Florida s built environment. Providing a better understanding of how our built environments affect our health is imperative as we plan communities for generations to come.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Jeffrey Schmucker.
Thesis: Thesis (M.A.U.R.P.)--University of Florida, 2009.
Local: Adviser: Steiner, Ruth L.
Local: Co-adviser: Bejleri, Ilir.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-08-31

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2009
System ID: UFE0024661:00001


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HOW DOE S URBAN FORM IM PACT THE POTENTIAL FOR CHILDREN TO WALK AND BICYCLE TO SCHOOL: A CASE STUDY OF ORANGE AND SEMINOLE COUNTIES IN CENTRAL FLORIDA By JEFFREY M. SCHMUCKER A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS IN URB AN AND REGIONAL PLANNING UNIVERSITY OF FLORIDA 2009 1

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2009 Jeffrey M. Schmucker 2

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To m y Family and Friends 3

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ACKNOWL EDGMENTS First and foremost, I would like to thank my fa mily and friends. Most importantly, I want to acknowledge my parents for all of their love and support, encouragement, and especially for teaching me that Its Great to be a Florida Gator. Thanks for always being there. I would also like to thank my beautiful fianc Raini for all of her love, support, a nd incredible sense of patience and understanding. She has stood by me ever y inch of the way duri ng this adventure. No doubt there were some rough mo ments, but we prevailed, baby! I would also like to mention my sister Caitlin. She is an inspiration to me, even though she doesnt realize it. To her, I want to say, Work hard, think big, and wonderful things will come your way. I would like to thank my Chair, Dr. Ruth Steiner. Having been in a peculiar predicament at the beginning of the thesis endeavor, Ruth took me under her wing and pushed me in the right direction. I want to thank her for extracting the best out of me and helping me gain a better understanding of the bigger picture. I would also like to thank my Co-Chair Dr. Ilir Bejleri, who provided me valuable instruction, wisdom, a nd guidance throughout this entire process. Additionally, I would like to thank Allison Fischm an and Russell Provost. I would never have been able to complete this without you. I appr eciate all of the time and effort the two of you spent in helping me prepare and analyze the data for this project. Finally, I would like to thank all of the people from the Department of Urba n and Regional Planning (f aculty, staff, students, and colleagues) that supported me along the way. You have truly made my experience here enjoyable and unforgettable. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................7 LIST OF FIGURES .........................................................................................................................8 ABSTRACT .....................................................................................................................................9 CHAPTER 1 INTRODUCTION................................................................................................................. .11 2 LITERATURE REVIEW.......................................................................................................16 Childhood Obesity and Physical Inactivity ............................................................................16 Automobile-Dominated Land Development ..........................................................................18 Florida Growth Management a nd Coordinated School Planning ...........................................21 Issues with the Siting of Public School Facilities ...................................................................23 School Enrollment Capacity ............................................................................................24 School Site Location and Site Size ..................................................................................25 Urban Form Characteristics and Walkability .........................................................................26 Complexities in Determining Mode of Travel ................................................................28 Measuring Potential Walkability .....................................................................................29 Street Connectivity ..........................................................................................................31 Residential Density ..........................................................................................................35 Summary .................................................................................................................................36 3 METHODOLOGY FOR MAPPING AND ANALYZING POTENTIAL WALKABILITY ....................................................................................................................41 Establishing the Analysis Zones .............................................................................................41 Calculating Potential Walkabil ity: Indicators for Analysis ....................................................42 Street Connectivity Indicators .........................................................................................43 Indicator #1: Street Density .............................................................................................43 Indicator #2: Intersection Density ...................................................................................43 Indicator #3: Pedestrian Route Directness ......................................................................44 Residential Density Indicators .........................................................................................44 Indicators #4: Gross Residential Density ........................................................................45 Indicator #5: Net Residential Density .............................................................................45 Indicator #6: Effective Walking Area .............................................................................45 Summary .................................................................................................................................46 4 CASE STUDY FINDINGS AND RESULTS........................................................................48 5

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Context of Study Region ........................................................................................................48 Orange County Case Study .....................................................................................................49 Indicator #1: Street Density .............................................................................................49 Indicator #2: Intersection Density ...................................................................................50 Indicator #3: Pedestrian Route Directness ......................................................................50 Indicator #4: Gross Residential Density ..........................................................................51 Indicator #5: Net Residential Density .............................................................................51 Indicator #6: Effective Walking Area .............................................................................52 Seminole County Case Study .................................................................................................52 Indicator #1: Street Density .............................................................................................53 Indicator #2: Intersection Density ...................................................................................53 Indicator #3: Pedestrian Route Directness ......................................................................54 Indicator #4: Gross Residential Density ..........................................................................54 Indicator #5: Net Residential Density .............................................................................55 Indicator #6: Effective Walking Area .............................................................................55 Summary .................................................................................................................................56 5 DISCUSSIONS AND CONCLUSI ONS................................................................................72 Discussions and Conclusions ..................................................................................................72 Bridging Community Development and Public Health ..........................................................75 Limitations of this Study ........................................................................................................80 Opportunities for Future Research ..........................................................................................82 LIST OF REFERENCES ...............................................................................................................88 BIOGRAPHICAL SKETCH .........................................................................................................93 6

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LIST OF TABLES Table page 2-1 Costs of Inactivity (billi on $), in the United States, 1995 .................................................38 2-2 Criteria for Establishi ng School Attendance Zones ...........................................................39 2-3 Common Street Connectivity Measures ............................................................................40 7

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LIST OF FI GURES Figure page 3-1 Creation of Analysis Zones ................................................................................................47 4-1 Overview of Study Area ....................................................................................................58 4-3 Graphical Illustration of St reet Density in Orange County ...............................................59 4-4 Graphical Illustration of Inte rsection Density in O range County ......................................60 4-5 Graphical Illustration of Pedestrian R oute Dire ctness in Orange County .........................61 4-6 Graphical Illustration of Gross Re sidential Density in Orange County ............................62 4-7 Graphical Illustration of Net Re sidential Density in Orange County ................................63 4-8 Graphical Illustration of Effective Walking Area in Orange County ................................64 4-9 Map of Seminole County School Attendance Zones and Schools ....................................65 4-10 Graphical Illustration of St reet Density in Sem inole County ............................................66 4-11 Graphical Illustration of Inte rsection Density in S eminole County ...................................67 4-12 Graphical Illustration of Pedestrian R oute Dire ctness in Seminole County ......................68 4-13 Graphical Illustration of Gross Re sidential Density in Sem inole County .........................69 4-14 Graphical Illustration of Net Re sidential Density in Sem inole County .............................70 4-15 Graphical Illustration of Effective Walking Area in Sem inole County .............................71 5-1 Connectivity Indicators of Sa mple Schools in Orange County .........................................85 5-2 Effective Walking Area of Sample Elem entary School in Seminole County ...................86 5-3 Connectivity Indicators of Sa mple Schools in Seminole County ......................................87 8

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Abstract of Thesis Presen ted to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Arts in Urban and Regional Planning HOW DOES URBAN FORM IM PACT THE POTENTIAL FOR CHILDREN TO WALK AND BICYCLE TO SCHOOL: A CASE STUDY OF ORANGE AND SEMINOLE COUNTIES IN CENTRAL FLORIDA By Jeffrey M. Schmucker August 2009 Chair: Name: Ruth L. Steiner Cochair: Ilir Bejleri Major: Urban and Regional Planning Childhood obesity in the United States has become a national epidemic. One of the reasons that researchers have s uggested that this may be occurri ng is due to a decrease in the amount of physical activity that children are participating in. One solution aimed at increasing physical activity among children, is by providing enhanced opportunities for children to walk and bicycle to school. This study examines how urban form impacts the potential for children to walk and bicycle to school, by examining several char acteristics of the built environment around elementary schools within Orange and Seminole C ounties in Central Florida. The two primary characteristics used in this investigation are stre et connectivity and reside ntial density. Within street connectivity, three indicato rs are used to measure the potential for walkability to school. These indicators include street density, intersection density, and Pedestri an Route Directness (PRD), which is a ratio of the network walking distance to the straight-line distance between two points. Residential density characteristics also use three indicators for measuring potential walkability. These include gross residential density, net residential density, and Effective Walking Area (EWA), which calculates the percenta ge of residential parcels that are found along 9

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10 a street network. These indicators are compared against four influential development periods which correspond to growth management and school coordination legisla tion in the State of Florida. These include histor ic schools built before 1950, pre-growth management schools built between 1950 and 1985, pre-schoo l coordination schools built between 1986 and 1995, and postschool coordination schools built after 1995. The general findings from this study suggest that historic schools built before 1950 and those schools sited after 1995 in Orange County reveal the highest potential for walkability. The general findings in Seminole County reveal the greatest potential for walkability occurring around schools built during the pre-growth management period between 1950 and 1985. By examining the Counties across the four developm ent time periods, there does seem to be a correlation between the patterns of developmen t in Orange County, while the development trends in Seminole County seem to be less apparent, following no coordinated patterns. Developments that are more compact, consisting of more traditional grid-like street patterns and higher residential de nsities, appear to support great er potential for walking and bicycling. Because the intention of this st udy was to investigate how urban form impacts walkability, analysis within the four influential time periods was critical, especially in examining how policy factors may be affecting the developm ent of Floridas built environment. Providing a better understanding of how our built environments affect our health is imperative as we plan communities for generations to come.

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CHAP TER 1 INTRODUCTION The connection between physical activity and health is as old as ci vilization. Hippocrates (460 BC 377 BC) once stated, Walking is mans best medicine. As our populations and cultures have grown and evolved, so too have our wa ys of life; we tend to eat more and walk less (Kahn, 2008). Paralleling this trend for the past tw enty-five years is a notab le increase in obesity rates among adult individuals (Centers for Dis ease Control and Prevention, 2007). Just as astonishing is the percentage of children and adolescents who are overweight or obese (Ogden, Carroll, & Flegal, 2008). One particular factor as sociated to the increase in rising obesity rates can be associated to physical in activity, which is particularly deleterious for the health of children and adolescents. Many children do not engage in enough physical activity to meet the recommendations required to maintain a hea lthy weight that suppor ts healthy lifestyles (Dellinger & Staunton, 2002). Alternatively, children are spending more time indoors, participating in less-physically active alternatives, such as watching television and playing videogames (Robinson, 1999). One solution to c onsider in addressing this issue is the encouragement of physical activity by providing sa fe and accessible opportunities for children to walk and bicycle to school. Though providing such an option may not entirely address physical activity concerns, the notion at least serves as a stepping-stone to promote further opportunities. It is not feasible to either predict or estimate the probability of children that might engage in physical activity, largely due to a diverse range of variables (e.g., dietary behaviors, safety concerns (real and perceived), personal choices). This ma kes the understanding of childhood obesity and its relationship to urban form extr emely difficult to measur e. However, further research is important and necessary in the con tinued effort to reveal the connections between health and the built environment. 11

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The issue of childhood obesity has becom e a majo r health concern for the U.S. and abroad (Wang & Lobstein, 2006). Although rates have stabilized between the periods of 2003 2006, we must not allow ourselves to become compl acent on the issue (Centers for Disease Control and Prevention, 2006). If obesity rates have reached a plateau, the plateau is still incredibly high. Previous data collected by the National Heal th and Nutrition Examination Survey (NHANES) for the time periods between 1976-1980 and 2003-2004, show the prevalence of overweight increasing: For children aged 2-5 years, prev alence increased from 5.0% to 13.9%; for those aged 6-11 years, prevalence increased from 6.5% to 18.8%; and for those aged 12-19 years, prevalence increased from 5.0% to 17.4% (Centers for Disease Control and Prevention, 2006). The current trend of overweight and obesity levels among childre n and adolescents has nearly tripled since 1980. In aaddition, another 15% of children and 14.9% of adolescents are considered "at risk" for becoming overwei ght, based on BMI (body mass index) measures (Centers for Disease Control and Prevention, 200 6). Overweight and obesity concerns are particularly risky for children as they may experience immediat e health consequences with a greater risk for weight-relat ed health problems in adulthood (Serdula, 1993), including cardiovascular disease, diabetes (Fagot-Campagna, Pettitt, Engelgau, Burrows, Geiss, Valdez, Beckles, Saaddine, Gregg, Williamson, & Nara yan, 2000), psychosocial illnesses (Strauss, Rodzilsky, Burack, & Colin, 2001; Dietz, 1998), a nd a host of other chronic disorders. Physical inactivity among other va rying factors is associated with the increase in childhood overweight and obesity. Current ly the U.S. Department of Health and Human Services recommends that American adults accumulate at least 30 minutes of mo derate physical activity most days of the week, while children should part icipate in at least 60 minutes. Even greater amounts of physical activity may be necessary for th e prevention of weight gain, for weight loss, 12

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or for sustaining weight loss. One soluti on to combat physical inactivity am ong younger populations is to increase the number of children who walk or bicycle to and from school. In 2003, the U.S. EPA (Environmental Protection Agency) reported a decline in the number of students who walked or bicycled to school from 48 percent in 1969 to 15 percent in 2001 (Steiner, Crider, & Betancourt, 2006). This trend was also projected in a Home-to-School Transportation study conducted by the Florida Department of Transportation ( FDOT ) in 1992, stating that only one out of six children in Florida walk or bicycle to school while the rest a re transported by bus or private motor vehicle (Sta rnes, Stein, Crider, Audi rac, & Pither, 1992). Fewer children engaging in active transportation methods as a mode of travel to school leads to an influx of motor vehicle traffic around school site s. The result of this occurrence often creates severe congestion increasing the incidence for pedestrian-vehicul ar accidents creating additional health risks. Unfortunately, this transportation m ode shift is causative of many ambiguous planning and development decisions made over the last half-a-century. In the U.S., public school enrollment reached a record high of 49 million in 2004; That number is projected to reach 53 million by 2016 (ICMA, 2008). With public school enrollment on the rise, it is becoming increasingly impor tant for decision make rs to address issues associated with the siting of public school facil ities, including but not li mited to a variety of factors that influence a childs mode of travel to school. This issue is especially important in the State of Florida, where populations are expect ed to double to 36 million by the year 2060 (1000 friends of Florida). More peopl e will presumably mean more children equaling a greater need for strategic planning and deci sion making regarding land use de velopment and school siting. The State of Florida currently re quires coordination between local pl anning agencies and district school boards mandating concurrency and the establ ishment of a public school facilities element 13

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in every local com prehensive plan. This requ irement was implemented to ensure consistency between land use development and school siting deci sions. The intent of this cooperative effort is to support the safety, health, and welfare of the general public and prev ent further unnecessary urban disinvestment and sprawl as Fl oridas population continues to grow. This study intends to contribute further investigation in to how physical (in)activity corresponds to childhood overweight and obesity issues, by explor ing how urban form impacts the potential for children to walk and bicycle to school. Similar research has led to this study and has fostered its process of evaluation, us ing a like methodology. This study examines two counties across four temporal development period s in the Central Florid a region using several indicators to measure the impact that urban form presents on school walkability1. Two main characteristics of urban form are explored in this study: Street Connectivity and Residential Density Street Connectivity is analyzed using three indicators: (1) Street Density, (2) Intersection Density, and (3) Pedestrian Route Directness (PRD) (Bejleri, Steiner, Provost, Fischman, & Arafat, 2008). Reside ntial Density is also analyzed using three indicators. The first two are strict measures of residential density including (1) Gross Residential Density and (2) Net Residential Density (Bejleri, et al., 2008). The third measure (3) Effective Walking Area (EWA), will be used to make assumptions on po tential walkability based on the percentage of residential parcels that are found along the street network. The ini tial analysis is then examined, comparing each set of findings across four temporal development periods which correspond to preand post-Growth Management laws and coordi nated school planning le gislation in the State of Florida. Through these findings, the author in tends to provide insight into how urban form has impacted the potential for children to walk and bicycle to school. Exploring these findings 1 Walkability (including walkable) will be used throughout the paper referring to active-mobility (walking, bicycling, etc.) within the built environment 14

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15 within the context of the different developmen t periods provides further insight into how the built environment has impacted walkability. The central Florida region is th e fastest growing region in the State of Florida. According to a recent report presented by Flor idians for a Sustainable Populat ion (in conjunction to findings from Florida 2060: A Population Distribution Scenario), the central Florida region will experience explosive growth with continuous ur ban development from Ocala to Sebring, and St. Petersburg to Daytona Beach. The study project s that the I-75 and I-4 corridors will be fully developed by 2060 (Floridians for a Sustainable Population, 2006). Resting squarely within this area are Orange and Seminole counties. Due to the projected growth and development of this region, it is important to provide research insight to help alle viate the stresses that will presumably exist into the future. The authors concentration on these two counties was chosen due to the availability of GIS data and the a dditional resources and information provided from previous studies within the ar ea specifying the need for furthe r research and investigation. This document contains five chapters. Th e first chapter is an introductory section justifying the value of this res earch. The second chapter provid es a review of the literature pertaining to issues of childhood obesity and physical inactivity. Connecti ons between health and the built environment are discussed, specifica lly examining the various impacts that urban form presents on walkability. The third chapter highlights the methodology that is used in this study. The fourth chapter presents in detail the research findings. Finally, chapter five presents discussions and conclusions based on the findings. This section will also include suggestions for valuable future research.

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CHAP TER 2 LITERATURE REVIEW This chapter illustrates the connections be tween physical activity and childhood obesity through a review of the literature pertaining to urban form and walkability. This section will primarily focus on issues associated with school s iting and the factors that affect a childs ability to walk and bicycle to school. The literature will begin with a review of the issues surrounding childhood obesity and the connection to physical in activity and the built environment. Next, a brief historical look into transformations of U.S. land development patterns will be discussed, specifically examining regulatory functions manda ted by Florida legislation that are used in guiding land use and school-site development deci sions. Then a section briefly outlining some of the major issues associated with the siting of public school facilities is discussed. Finally, a section describing the characteri stics of urban form is discus sed, including the relationship between the built environment and walkability, particularly concer ning school walkability. This section will provide a foundation and context for th e arguments stated in this research study. Childhood Obesity and Physical Inactivity Childhood obesity rates have reached such astoni shingly high levels in the United States that the condition is now considered an epidem ic (Centers for Disease Control and Prevention, 2006). The rise in childhood obesity has been attr ibuted to complex interactions across a number of relevant social, environmental, and policy contexts that have collectively created an adverse environment for maintaining a healthy weight. Factors associated w ith weight gain and childhood obesity include energy input (food intake ), energy output (amount of work), and genetic predisposition. Although dietary behaviors and genetic make-up play vital roles in regulating obesity levels, the res earch presented in this study ta kes an approach that focuses primarily on factors affecting phys ical activity and inactivity (expe nditure of energy) within the 16

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built enviro nment, particularly the various physical and institutional impe diments that exhibit a childs ability to walk or bicycle to school. Scientific evidence has shown that physical activity plays a critical role in supporting weight loss based on the first law of thermodynamics1. Unfortunately, many children do not participate in the recommended amount of physical activity needed to maintain a healthy weight that supports healthy lifestyles (Dellinger & Staunton, 2002). In many cases, children are deprived of the opportunities to engage in physi cal activity due to a gr owing separation between residential dwellings and commercial, civic, a nd institutional services (e.g., school facilities), inadequate provision of community places for chil dren to commune (e.g., parks, ball-fields, and other (natural) recreational destin ations), and the lack of necessa ry infrastructural elements like sidewalks, bicycle lanes, and other pedestrian pathways that support recreational and travel opportunities (Day, 2009). Many of these issues are directly related to failures in policies, planning, and design. Unfortunately, there can be many negative implications related to th ese policy decisions, including preventable disorders su ch as obesity, which is a know n risk factor for many chronic disorders (e.g., diabetes, coronary heart diseas e) (Weight Control Information Network, 2009). These conditions contribute to th e billowing stress on our health care system and have added to the enormous increase in health care costs (Weight Control Information Network, 2009). One study, conducted in 1995, reported that the direct monetary costs re lated to physical inactivity a contributor to the obesity epidemic may be as high as $24.3 billion annually (see Table 2-1) 1 The first law of thermodynamics genera lly states that a thermodynamic syst em can store or hold energy and that this internal energy is conserved. Heat is a process by which energy is added to a system from a high-temperature source, or lost to a low-temperature sink. In addition, energy may be lost by the system when it does mechanical work on its surroundings, or conversely, it may gain energy as a result of work done on it by its surroundings. The first law states that this energy is conserved: The change in the internal energy is equal to the amount added by heating minus the amount lost by doing work on the environment. 17

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(Colditz, 1999). The estim ated hospital costs al one in treating children for obesity-associated conditions rose from $35 million in 1979-1981 to $127 million in 1997-1999, in 2001 dollars (Wang & Dietz, 1999). To deliver adequate and practical solutions that will aid in remedying these conditions, policy makers must recogni ze some of the causative factors that are contributing to these instances. Introducing more opportunities to be physically active is one solution in helping relieve a portion of the outrageous health car e costs that are associated with preventive disease control and the overweight and obesity epidemic. There are many ways to encourage and increase levels of physical activity. Several ways to promote childre n to participate in phy sical activity is through parental encouragement and cooperative participation, development of positive attitudes about exercise, modeling healthy behaviors, and encour aging healthy eating habits. Encouragement of physical activity can also be strengthened th rough physical education programs in schools and within the community through an assortment of community organizations. Additional methods for encouraging physical activity can also be achieved through a variety of physical planning strategies, design implementations and a host of regulatory factors which are the focus of the research presented in this paper. Automobile-Dominated Land Development A viable and effective way to provide younger populations the opportunity to engage in increased levels of physical activity is to provide safe and accessi ble means for children to travel to and from school by walking and bicycling. Unfortunately, many communities in the U.S. have deserted the ideal of creating environments that are friendly for the pedestrian and healthy for the populations that inhabit th em. To better conceptualize thes e implications, it is important to understand the evolution of development trends that have historically inhibited community walkability and propelled us into an age of automobile-dominated living. 18

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Cities h ave been recognized as places for people to come together, to enjoy the benefits of company, commerce, and mutual defense for th ousands of years (Frumkin, Frank, & Jackson, 2004). By the 1950s, the American Dream was thriving in post-World War II suburban land development, spurred on by middle class American society fleeing the atrocities of the inner city in the so-called pursu it of happiness (specifically the ow nership of land) (Calthorpe, 1993). This era instituted a new America, in which both the city and the suburb were now locked in a mutually negating evolution toward the loss of community, human-scale environments, and the beauty of natural surroundings. Ultimately, these patterns of development and growth created on one side, congestion, pollution, and isolation, and on the other, urban disinvestment (inner city retraction) and economic hardship. Some of the negative conditions resulting from this movement include environmental stresses, intrac table traffic congestion, lack of affordable housing, irreplaceable open space and gathering pl aces, lifestyles which burden working families and isolate undervalued populations, and declines in public health and ov erall quality of life issues (Calthorpe, 1993). Functional, inhabitable communities are products of great planning, good policy, and forwards thinking of design and the appropria te use of space. Reviewing historic U.S. development trends reveals communities consisting of narrow tree-lined streets, with sidewalks, where people walked and rode their bikes. To wns were simple; in many instances, shopkeepers lived above their businesses and residents knew one another. Although reverting back to the simplicity of yesteryear is daring ly unrealistic, the notion of recreating the small town livability does not have to be entirely disregarded. In fact, the small towns of the mid-1900s, as we remember them, consisted of the most valuable elements that supported healthy livable places, including community-oriented design s, with civic and institutional f acilities at the core of the 19

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neighborhoo d, places for people to co mmune and engage in public activities, and most of all, a sense of belonging, captured by a st rong sense of place (Lynch, 1960). Today, the automobile has reconstructed our daily lives and has reshaped the ways in which we live and function in the modern world (Frumkin, Frank, & Jackson, 2004; Calthorpe, 1993). The focus on small town development, with pedestrian friendly thr ough-fares is rare in some instances it is completely non-existent. Mode rn development patterns th at strictly facilitate automobile accommodation and lack human-scale environments have left us with communities where the segregated lifestyle of individuality with long commutes between home, work (school) and play prevail. This disinvestment in comm unity building destroys the cohesion that people and their environments (both na tural and built) need in sust aining health, wellness, and a satisfactory quality of life. Making sound decisions about developing health y places for people to live, work, and play begins with good community planning (Lucy 1994), es pecially when it comes to the health and well being of children in the community. At the core of such decision making is a host of rules and regulations that are aimed at addressing these issues. In pa rticular, the topics of growth management and land use regulation; two extrem ely important mechanisms that assist in fostering sensible development for both current a nd future populations. To better understand the connection between land development patterns and the locations of schools within the community, it is important to understand the regulatory framework by which development decisions are frequently made. While the challenges described above are fair ly common across the United States, not all States deal with such ch allenges the same way. Some States, like Florida, have chosen to adopt a top-down planning approach to govern and manage their growth. This paper will focus on the 20

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planning and development structure that Flo rida constitutes in order to put into context the case studies for this research. Florida Growth Management and Coordinated School Planning In 1972 the Florida legislature passed the Flor ida State Comprehensive Planning Act. This act was designed to provide long-range guidance for the orderly social, economic, and physical growth of the state, setting forth goals, objec tives, and policies (1972 Florida Laws, Chapter 72295). Also part of the 1972 Fl orida legislation, was the devel opment of the Environmental Land Management Study (ELMS) Committee, which dr afted the Local Government Comprehensive Planning Act of 1975. This act was intended to c ontrol land use and guide development. The act specified two major mandates. The first was a requirement for local governments to adopt comprehensive plans. The second requirement mandated that all development plans conform to the adopted comprehensive plan. Unfortunately, the act would eventually fail due to unclear expectations and a failure in implementing it e ffectively. Then in 1985 the Local Government Comprehensive Planning and Land Development Act (a.k.a. GMA) (Chapter 163, Part II, Florida Statutes) was created. This act was simila r to the 1975 act, in that it required all of Floridas counties and municipali ties to adopt local government comprehensive plans to properly guide future growth and development. Ho wever, when the act was amended in 1986, the requirement that all local governments ensure t hat public facilities and services needed to support development shall be available and concurre nt with the impact of development (Powell, 1993) was added. The term concurrency is often used to describe this provision. Understanding concurrency and its intent is an impor tant aspect in bridging the relevance of land use development and the impact it presents in th e siting of public school facilities. Concurrency, as explained by Boggs and Apgar is a land use re gulation which controls the timing of property development and population growth. It s purpose is to ensure that ce rtain types of public facilities 21

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and services needed to serve new reside nts are constructed and made available contemporaneously with the impact of new development (1991, p.1). Neither the 1985 document nor the amended document in 1986 described what public facilities needed to be included within this co ncurrency requirement. In 1993 a detailed list of public facilities and services was introduced, in cluding sanitary sewer, solid waste, drainage, potable water, parks and recreat ion, and transportation facilities (including mass transit), was added to the GMA. These facilities and services were the only ones subject to the concurrency requirement (FSA 163.3180 (1)(a)). Additional facilitie s and services could not be made to meet concurrency unless appropria te studies revealed such a n eed with approval by the Florida legislature. Missing from this list was a requirement recognizing public school facili ties. During this same period (1993), Florida legislation, (specifically ELMS III, established by Governor Lawton Chiles) proposed bringing about more coordinated efforts between local governments and district school boards. The primary objectiv e of the proposal recommended that formal inter-local agreements between local government and district school boards be implemented to ensure consistency between plans for public school facilities and new land development (Powell, 1999). It wasnt until 1995, in response to overcro wding issues in Floridas public schools, that Florida Educational Facilities Legislation mandate d the requirement of th e aforementioned interlocal agreements proposal ( 1013.33(2) F.S. and either 163.3177(6)(h)4 F.S. or 163.31777 F.S.). These inter-local agreem ents were critical to land development decisions as public schools encouraged residential growth and vice-a-versa residential gr owth required a need for updated (or new) schools. In 2002, further legislation was passed requiring the States school boards and local governments to review school siting with a comprehensive approach. It was the 22

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responsibility of the school board to review and take into co nsideration local com prehensive plans before making any sc hool facility decisions. Schools are expected to meet specific criteria concerning enrollment capacity, size and location of new and existing schools, and the in frastructure needed to promote safe and accessible transportations options to and from pub lic school facilities. In 2005, an amendment to the GMA recognized the need for public school faci lities to meet concurrency requirements. However, this requirement does not apply to th ose districts with reported slow growth and adequate enrollment capacity (Florida Depa rtment of Community Affairs, 2008). The concurrency requirement does however require local governments to be consistent with the plans of the local school board by including a Public Schools Facility Element in their comprehensive plans. This portion of the comprehensive plan includes objectives and policies which illustrate the development needs of public school facil ities including, infras tructural provisions, collocation of new schools with other public fac ility needs, locations of new schools near residential areas, and the use of school faciliti es as emergency shelters [9J-5.025, FAC]. Issues with the Siting of Public School Facilities There are many issues associated with school siting. This study will briefly discuss a couple of the major components, including enrollment capacity and school site location and site size. Although there are stringen t regulations regarding concurre ncy and policies requiring intergovernmental agreements used to coordinate and ensure consistency in development the implementation process can sometimes get complicat ed and be ill-effective. As part of the school boards responsibilities, th ere are explicit powers and duties that must be met to ensure that each district provides adequate and func tional public school facil ities that are governed effectively ( 1001.41 F.S. & 1001.42 F.S.) However, in developing communities where children can walk and bicycle to school, coordinated efforts must be met. If we do not change 23

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the location of schools to ensure that more students liv e within walking and bicycling distance, we will eith er pay increasing amounts to bus or dr ive our children to school or continually be retrofitting neighborhoods to ensure th at children are able to walk and bicycle to school (Steiner, Bejleri, Wheelock, Boles, Cahill, & Perez, 2008). School Enrollment Capacity Since the 1950s, average school size (measur ed by enrollment capacity) has gown while school facilities have become increasingly larger in size and distant from the neighborhoods they serve. Florida public school enrollment in 2007, for elementary school-aged students was approximately 765,200 (American Fact Finder, 2 008). This number represents just a 1.03 percent increase based on the approximated 757,300 students enrolled in 2006 (American Fact Finder, 2008). Although the incr ease seems minimal, thats approximately an additional 7900 students across the entire State. Furthermore, the National Ce nter for Education Statistics reported that from 1930 to 2001, public school enrollment in the U.S. nearly doubled, from 26 to 48 million students (across all grade levels), yet the number of public school buildings decreased 60 percent in the same period, from 247,000 to 93,000 (ICMA, 2008). This st atistic indicates a shift from an average of 105 students to nearly 516 students per school building. As the average size of a school has grown, so to have the di stances between schools a nd the neighborhoods they serve. This trend not only relate s to growth in average enrollment size, but is also causative of the policies and practices that encourage large site locations and discourage expansion and renovation of existing school sites. Part of controlling enrollment capacity in school s is directly related to decisions made by the Superintendant and the district school boa rds establishment of School Attendance Zones (SAZ). School attendance zones are the geographical boundaries that institute which 24

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communities (area) a s chool will serv e. SAZs are established based on a series of factors, of which enrollment capacity plays a critical role (see Table 2-2). SAZs are also developed with th e purpose of integrating a dive rsity of students into school facilities. However, balancing th e structure of a student body is qui te difficult, due to residential development patterns which often produce neig hborhoods that are demographically and socioeconomically unbalanced. The result is a set of attendance boundaries that vary considerably in shape and size (Steiner, et al., 2008 ). The location of a school site relative to the neighborhood it is intended to serve may be quite distant. This poses an inherent tran sportation issue concerning the mode choice of children getting from home to school. While recognizing this problem and understanding its implications, the scope of this research study does not specifically address the issue of establishing SAZ boundaries. School Site Location and Site Size The escalation in school site size also play s a critical role in determining school walkability. Over the past three decades, the acre age required for school sites has grown so large that it has become a challenge for local govern ments and school boards to even consider walkability as a critical factor in site location. Overly larg e school sites, have by necessity, become typical throughout many communities and are usually located on the periphery or outer regions of a community and sometimes complete ly outside of the neighborhoods the school is intended to serve. In many instances, this is re sultant of costs and avai lability of land within existing urban areas. With scarce budgetary resources under a weak ened economy (current 2009), government dollars are being spent to cover th e most crucial needs, particularly wages for teachers positions, and the cost of text books, am ong other needs. Citing school walkability as a priority is typically an afterthought. It should also be noted that in many communities, school siting decisions are also based upon educational specifications and community expectations such 25

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as the need for athletic fields and courts, pa rking, and storm water management requirements, which subsequently drive the need for excessively large school sites (Maryland Department of Planning, 2008). In some instan ces, new school sites have shifte d to the periphery due to low enrollment capacity within existing urban areas. Due to the increased distances between many schools and the neighborhoods they serve, walking and bicycling is simply not feasible and the school bus is typically acknowledge d as the solution to the problem In the State of Florida, district bussing is not provided within a two m ile radius around school sites, unless hazardous walking conditions exist preventing safe and accessi ble access for children to walk or bicycle to school (e.g., road construction). Under these ci rcumstances, courtesy bussing is provided for those students until such probl ems hindering access from home to school are remedied. In many cases, parents drive thei r children to school desp ite factors related to distance (Campbell & Wang, 2008), increasing the amount of traffic in and around school sites. There are many tradeoffs between overly large school sites and sm aller sites built with more community-oriented approaches. While th e upfront cost of land may be less at the periphery of a community, the long -term costs appear to be much higher. Costs of sprawl in terms of land consumption and water and air pollu tion are some of the more recognizable factors (Maryland Department of Planning, 2008) while other literature is beginning to hypothesize about the negative long-term consequences asso ciated with community degradation and public health (Frumkin, Frank, & Jackson, 2004). Urban Form Characteri stics and Walkability Addressing the physical characteristics of the built environment is an essential component in coordinating school sites that facilitate more walkable conditions. One of the many tools used to assess physical environments and the peopl e who travel within them is travel demand (Cervero & Kockelman, 1997). Travel demand (or travel demand management) refers to the 26

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m anagement of traffic conditions, including traffic flow, traffic c ongestion, and the provision of travel options needed to meet specific dema nds (U.S. Department of Transportation, 2009). Managing traffic demand today is about providing travelers, re gardless of whether they drive alone, with travel choices, such as work location, route, time, and mode (U.S. Department of Transportation, 2009). Subsequently land develo pment issues must be addressed to support these options. This requires strategic planni ng efforts that recognize the connection between transportation planning and land use development. In general, planning and development technique s can influence active mobility. In a study examining travel demand, Cervero and Kockelman introduce three dimensions of the built environment (a.k.a. the 3Ds), which include: (1) de nsity of land uses (the agglomeration of spaces within a particular area), (2) diversity of land uses (the aggregate mix of spaces within a particular area), and (3) design (the physical layout and compositional elements of the urban structure). Additionally, there is literature that also suggests two other components; distance & destinations, which relate to the length and ti me between places) (Cer vero & Kockelman, 1997). This development archetype is particularly importa nt in providing the oppor tunity for children to walk and bicycle to school, assuming school faciliti es as a specific land use. At a macro-level, density (the number of residen tial dwelling units per ac re), distance (total length of connected road segments), and destination (in this case, a school site) are the discernible factors in examining the general (potential) walkability between home and school. At the micro-level (design implications), additional features mu st be provided like sidewalks (with adequate widths), street trees that pr ovide shading, safe crossing opportunities (medians and pedestrian refuge areas), buffering or separa tion of pedestrian and vehicula r traffic, and the addressing of 27

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safety issues (Frank, Engelke, & Schm id, 2003; Knack, 2008). However, even with the provision of the appropriate infrastructure to support walkability, active travel is not inevitable. Complexities in Determining Mode of Travel So, what influences a persons decision to either walk, bicycle or driv e to a destination? This is a complex question. In addition to fact ors related to urban form, research shows that individual behaviors (multivariate factors of pers onal choice) and other determinants also play a role. This makes measuring actual walkabilit y an extremely difficult task. One factor in determining an individuals mode choice is vehicle accessibility. Undervalued populations2 may not have equal access or be legally allowed to op erate a motor vehicle, th us shifting mode choice to non-personal automobile options. Another factor that influences a persons mode of transport is micro-economic problems relating to benefits weighed against costs (Boarnet & Crane 2001). This theory is further supported by Randall Crane, a professor at the University of California at Los Angeles: The cost of a trip consists of those things that add hassles to ones day or burden ones pocketbook: the amount of time it takes to travel, the amount of traffic that might be encountered along the journey, and how much m oney the trip might require. The choice to drive, take transit, walk, or bicycle is ther efore viewed as a function of ones preferences for a particular mode plus the costs of the different modes relative to one another (Frank, Engelke, & Schmid, 2003, p. 108). This is particularly relevant in the mode choice of young children w hose parents typically assume the responsibility of deciding how a child gets to and from school. Moreover, safety and physical or social environments may also play cr itical roles in contributing to the proportion of children who travel to school by motorized ve hicle (Cooper, Page, Foster, & Qahwaji, 2003; Dellinger & Staunton, 2002). Still, the most common reason for not walking has been directly 2 Undervalued populations refers to those individuals that are underserved or unable to reap all the benefits that society provides due to income constraints, personal disability, infrastructure provision, and/or policy implications. 28

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attributed to distance (Goldsm ith, 1992; Aultm an-Hall, Roorda, & Baetz, 1997). Given its quantitative nature, distance is a reasonable m easure of the impedance between the origin and destination for walking (Aultman-Hall, Roorda, & Baetz, 1997, pp.11). Taking into consideration these few examples of mode choice, its easy to see some of the difficulties involved in measuring actual le vels of walkability. Measuring Potential Walkability Some research on walkability (both nationally and internationally) has cited one-quarter mile (or 400 meters) as an acceptable distance an i ndividual might be expected to walk to any given destination (Atash 1994). However, in the State of Florida (where this research study takes place), a two-mile radius (pedestrian shed) has been established around school sites, defining the boundary by which parents are responsi ble for getting their children to school. As noted a moment ago, the acceptable distance a person might be expected to walk is approximately one-quarter mile. This suggests that the two-mile radius es tablished in the State of Florida is a highly unrealistic distance to exp ect a child to walk or bicycle to school. To investigate the potential walkability of children who walk or bicycle to school, the author will focus on the factors of urban form residing within more reasonabl e walking distances, specifically one-half and one-mile radii. As mentioned previously, meas uring walkability is a difficu lt task. However, there are many characteristics of built environments that can provide measurable outcomes in examining the potential walkability of a place. To better understand how walkability can be measured, it is important to review several of the defining characteristics that support pedestrian walkability. The author will utilize two publi cations to define these charact eristics, which will provide the foundation for this research study. The first study was originally presented to the Joint Congress 29

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of ACSP-AESOP3, entitled Measuring Network Connectivity for Bicycling and Walking. This paper illustrates a general set of urban form characteristics useful in assessing potential walkability patterns: 1. Block Length, 2. Block Size, 3. Block Density, 4. Street Patterns 5. Street Density, 6. Intersection Density 7. Connected Node Ratio 8. Link Node Ratio 9. Pedestrian Route Directness 10. Effective Walking Area (Dill, 2004) It should be noted that while each of these ch aracteristics provides a distinctive value for quantitatively evaluating walkability there is a wide level of variability that can be interpreted from case to case. When specifically examini ng the walkability of a place, its important to choose the appropriate characterist ics that support what is being investigated. Analysis may require the use of two or more characteristics to support or negate one finding from another. For instance, block density may be a good proxy for street connectivity. However, it may not necessarily indicate good walkab ility. Although the census block density of two completely different regions is the same, further research may reveal that one portrays less walkability due to the physical design of the block. For this r eason, using multiple indicators is important in examining the walkability of places. The second selection of liter ature, developed by Dover, Kohl & Partners and Chael, Cooper & Associates in conjunction with the City of Raleigh, Nort h Carolina, presents a list of characteristics more specifically aimed at assessing the walkability of neighborhood schools: 3 ACSP is the Association of Collegiate Schools of Plan ning; AESOP is the Association of European Schools of Planning. 30

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1. Stree t Connectivity 2. Completeness of Sidewalk Network 3. Availability of Public Transportation 4. Number of Dwelling Units within Walking and Bicycling Distance 5. Mixture of Uses in Immediate Vicinity 6. Street Trees 7. Posted Speed Limits 8. Curb Radii at Intersections 9. Vehicle Lanes and Lane Widths 10. Defined or Guarded Crosswalks 11. Pedestrian Refuge/Median Strips 12. Street Lighting 13. Natural Surveillance (City of Raleigh, N.C., 2008) This research will focus primarily on examining the characteristics of Street Connectivity and Residential Density utilizing the supportive literature from both of the above listed documents. The researcher has established an explicit set of indicators to measure both characteristics of urban form in determining potential walkability. The following literature will justify the use of these two publications as a guideline in conducting this study while validating the significance of the chosen indicators for measuremen t of potential walkability. Street Connectivity Because streets accommodate most forms of travel and facilitate connectivity, their importance serves as a central focus in measuri ng travel patterns and behaviors (Frumkin, Frank, & Jackson, 2004). Traditionally, in the United Stat es, street patterns were laid in gridiron patterns. These road networks divided land into manageable urban bloc ks accessible by people who traveled mainly by foot, hor se & buggy, and in later years, powered automobiles. Such networks reduced the distance between origin a nd destination, providing many intersections, and therefore many possible routes of travel (Frumkin, Frank, & Jackson, 2004). By the mid 1900s, urban planners deserted the idea l gridiron pattern for a more hi ghly sought after pattern which typified the development of mi ddle class suburbia. This included a street hierarchy system which separated automobile through-fares from developed areas (spe cifically residential 31

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neighborhoods), creating a whole ne w style of street patterns. By the early 1990s another street pattern began to surface consis ting o f loops and lollipops4, subsequently turning straight-line distances into journeys of consid erable length. The intent of the hierarchy street system and the circuitous nature of looping roadways was strategically aimed at reducing the number of automobile thoroughfares, making [r esidential] streets sa fer for the pedestrian. Unfortunately, the street hierarchy system has had very advers e affects resulting in reduced connectivity, the promotion of urban sprawl, an increase in vehi cle miles traveled, and a host of other public nuisances and health related issues (Frumkin, Frank, & Jackson, 2004). In recent times, development strategies like the New Urbanism5 (neo-traditional design), transit-oriented design (TOD)6, and the ideology of Smart Growth7 have attempted to address issues of suburban sprawl and loss of community by returning to traditional development styles. These development models call for more compact uses of land, unite d by traditional grid-lik e street patterns and higher residential and population densities. These archetypes are intended to reconnect people and place, providing greater connectivity betwee n origin and destination through multi-modal transportations options which facilitate efficien t travel modes for a diversity of individuals, including pedestrians. 4 Loops and lollipops refer to large circuitous and winding streets and dead-end / cul-de-sac street development patterns. 5 The New Urbanism is a planning movement in support of the abandonment of auto-centric development and Euclidean zoning. It suggests a return to more traditional, pedestrian-oriented development patterns and a mix of uses and housing types. See CNU (Congress for th e New Urbanism) website for further description and information. More information available at: http://www.cnu.org/ 6 TOD is a development initiative that involves the creation of compact, walkable communities centered around high quality train systems. This makes it possible to live a higher quality life without complete dependence on a car for mobility and survival. More information available at: http://www.transitorienteddevelopment.org/tod.html ) 7 Smart Growth refers to development decisions that affect many of the things that affect people's everyday lives their homes, their health, the schools their children attend, the taxes they pay, their daily commute, the natural environment around them, economic growth in their co mmunity, and opportunities to achieve their dreams and goals. What, where, and how communities build will affect their residents' lives for generations to come. More information available at: http://www.epa.gov/livability/about_sg.htm ) 32

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The Design Guidelines for Pedestrian-Fri endly Neighborhood Schools booklet published by the City of Raleigh, North Carolina explains Street Connectivity as a well-connected network of local streets, supporting trans it by providing direct routes and a high degree of connections for pedestrians between origins/des tin ations (City of Raleigh, N.C., 2008). Because traffic can be dispersed over a large network of streets, local streets in a well -connected network tend to carry lower volumes of vehicular traffic(City of Raleigh, N.C., p. 3). This makes active forms of travel along such roadways safer in terms of d ecreasing the incidence for automobile-pedestrian interference. Additionally, well connected networks of local st reets potentially maximize the number of residential dwellings that could be located within wa lking distance of a school site location (City of Raleigh, N.C., 2008). Pedestrian Route Directness (PRD) is often c ited as a measurable indicator for evaluating the connectedness of places. PRD is the ratio of route distance to straig ht-line distance for two selected points (Dill, 2004, p.5). The lowest value for PRD is 1.00, whereas the network distance is equal to the strai ght-line distance. Cited in Di lls work (2004), the INDEX Plan Builder developed by Criterion Planners Engineer s, recommends PRD values of 1.2-1.5 as an acceptable level of connectivity, whereas values ranging between 1.6-1.8 characterize less direct routes. A study conducted by Lawrence Frank & Co., in King County, Washington, found that compact development utilizing connected street networks with pedestrian facilities could help improve air quality and the health of people in a community (Frank, Sallis, Saelens, Bachman, & Washbrook, 2005). The study also found that reside nts in the most interconnected areas of King County traveled 26 percent fewer vehicle miles pe r day, while residents in the most walkable areas tended to be less overweight or obese (Frank, et al., 2005). Communities exhibiting more 33

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com pact development patterns show a greater in cidence of individuals engaging in physical activity. Investment in well conn ected street networks, a mix of land uses, and an orientation towards more multi-modal transportation options can be beneficial to the public welfare of a community (Frank, et al., 2005). Another study, evaluating the e ffects of urban form and distance on travel mode to school among middle school students in Oregon, found that urban form does play a role in determining a childs decision to participate in active forms of school travel (Schlossberg, Greene, Phillips, Johnson, & Parker, 2006). Schlossberg and coll eagues (2006) utilize se veral of the same common indicators of street connect ivity that this study uses in conducting its analysis, including street density, intersection density and pedestrian rout e directness (See Tabl e 2-3). While sixteen percent of the students surveyed listed walking or bicycling as their pr imary means of travel from home to school (1 to <1.5 miles), more th an double (forty-two percent) listed walking or bicycling as their primary means of travel from school to home (1 to <1.5 miles). The increase in students engaging in active travel from sc hool was found to be connected to parents who drove their children to school, but were not avai lable to pick their ch ildren up after school (Schlossberg, et al., 2006). Althoug h there were some limitations in this study (primarily small sample sizes), the findings reveal that students ar e willing to walk at di stances greater than the accepted standard of one-quarter mile. These fi ndings support the need for further research investigating the impact of urba n form at greater distances around school sites. Additionally, this study found that while holding distance and other urban form measures constant, intersection density was a strong indicator wh ich influenced overall walkabili ty (Schlossberg, et al., 2006). In support of the findings from this study, Frank and colleagues (2005) suggest that areas with densities equal to or greater than 30 intersecti ons per square kilometer (approximately equal to 34

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78 intersections per square m ile) have been a ssociated with greater overall connectivity and increased levels of physical activity. Residential Density The term Density (referring to urban development density) is a controversial term and not surprisingly, a hot topic issue among most pl anning practitioners as well as citizens in many communities (Forsyth, 2003). The debate of ove r density has resulted in many arguments both for and against the issue. In many instances dens ity is seen as the opposition to natural, healthy environments, postulating that its effects consti tute crowded, ugly, dirty places (Forsyth, 2003). However, higher urban density is essential in sh ifting mode choice from automobile travel to active forms of travel for utilitarian pur poses, especially for school walkability. Many studies have been published relating walk ability and increased levels of physical activity to various characteristic s of urban form including, reside ntial density, mix of land uses, street connectivity, and aesthetic s & safety (Saelens, Sallis, Black, & Chen, 2003). However, little research has been conducted specifically examining the impact of residential density on a childs ability to walk and bicycle to school. Although not specifically regarding schools in its calculation, one study utilizing data collected by the SMARTRAQ household travel survey in the Atlanta, Georgia region found that number of cars (within household), nearby recrea tional space, and residential density were most strongly related to wa lking among younger populations (Fran k, Kerr, Chapman, & Sallis, 2007). Similarly in another study, analysis also utilizing SMARTRAQ data revealed that land-use mix and intersection density were also positively rela ted with time spent participating in moderate levels of physical activity (Frank, Schmid, Sallis, Chapman, & Saelens, 2005). Another study conducted in six cities in the Netherlands while adjusting for age (children age 6-11), sex, BMI, and level of education, fou nd that physical activity was significantly (p < 35

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.05) associated with residential density, am ong ot her relationships with green space, and activefriendliness of the neighbor hood (de Vries, Bakker, van Mechelen, & Hopman-Rock, 2007). Although there is little resear ch specifically examining residential density and school walkability, related studies show that there are connections be tween residential density and general walkability, including increase d levels of physical activity. In this research study, the aut hor will examine the impact of residential density on school walkability. A key issue to consider when usi ng density as a measurable characteristic of walkability is the differences in calculating density types. Depending on the type of research one might be conducting, it is important to differentia te the classification of density calculations being used, as results can sometimes be conf using or misinterpreted (Forsyth, 2003). For instance when calculating either Gross or Net residential density, its no t enough to state the one is calculating Net resi dential density. This is due to a difference in mathematical equating. Net density refers to densities where the base la nd area calculation focuses only on the parcel or, if covering larger areas, excludes certain uses (e.g.: commercial and retail uses). Gross densities do not have such exclusions (calculations incl ude all land uses) (Forsy th, 2003). Research suggests that schools be located in neighborhoods with a minimum net residential density of 5 dwelling units per acre (City of Raleigh, N.C., 2008). However, other research has shown that more walkable areas have a net residential densit y equal to or greater than 6 dwelling units per residential acre while less walkable areas expe rienced less than 4 dwelling units per residential acre (Frank, et al., 2005). This study will examine both Gross Residential Density and Net Residential Density as potential factors influencing a childs ability to walk or bicycle to school. Summary There are many factors contri buting to the current childhood obesity epidemic. One of those factors is the amount of phys ical activity that chil dren engage in. Studies have shown that 36

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the percentage of children walki ng and bicycling to school has declined over the past 30 years (Steiner, Crider, & Betancourt, 2006), while obesity rates have near ly tripled since 1980 (Centers for Disease Control and Prevention, 2006). Incr easing the num ber of children who walk and bicycle to school can potentially reduce the prevalence of childhood obesity rates. One solution in addressing the obesity epidemic is through ex amination of the built environment. This will help researchers and practitioners alike to better understand how urban form impacts the potential for individuals to walk and bicycle with in their communities. The next chapter of this study provides a detailed description of the me thodology that will be used in conducting the research case studies. 37

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Table 2-1. C osts of Inactivity (bi llion $), in the United States, 1995 Condition Relative Risk PAR% Direct Costs Type 2 Diabetes 1.5 12% 6.4 CHD 2 22% 8.9 Hypertension 1.5 12% 2.3 Gall Bladder Disease 2 22% 1.9 Cancer Breast 1.2 5% 0.38 Colon 2 22% 2 Osteoporotic Fractures 2 18% 2.4 Total 24.3 Billion Source: Colditz, G.A. (1999). Medicine & Sc ience in Sports & Exercise, Vol. 31(11) 38

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Table 2-2. C riteria for Establishing School Attendance Zones Priority Determinants 1 School Capacity 2 Convenience of access to schools 3 Safe and efficient student transportation and travel 4 Effective and appropriate instructional programs 5 Socioeconomic diversity in school enrollments 6 Financial and administrative efficiency Source: Florida Statutes 1001.41(2), F.S.; 1001.42(4); 751.01-.05, F.S. 39

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40 Table 2-3. Common Street Connectivity Measures Measure Description Ideal Values Block Length Blocks are the land area carved out by the street network. It is presumed that shorter the block, the greater amount of connectivity 300 to 600 feet (Dill, 2004) Block Size Measured by the length and the width, blocks that are smaller in total size presumably infer better connectivity Fort Collins, Colorado requires block sizes to be between 7 and 12 acres (Steiner, et al., 2006) Street Density The total linear miles (or kilometers) of streets per unit of area (usually in square miles or kilometers) Not Identified Intersection Density The number of intersections per unit of area (usually in square miles or kilometers). It is presumed that higher density equates to higher connectivity Over 78 intersections per square mile (Frank, et al., 2005) Connected Node Ratio The number of street intersections divided by the number of intersections plus cul-de-sacs Values of 0.7 or higher are favored (Dill, 2004) Link Node Ratio The number of links (road sections between intersections) divided by the number of nodes (intersections) Higher than 1.4 (Dill, 2004) Pedestrian Route Directness (PRD) The ratio of network distance to straight-line distance for two selected points. Numbers closer to one may represent better connectivity Values between 1.2 and 1.5 have been recommended as acceptable standards (Dill, 2004)

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CHAP TER 3 METHODOLOGY FOR MAPPING AND ANALYZING POTENTIAL WALKABILITY This chapter provides a detailed description of the reasoning for this work and the methodology that is used to analy ze and evaluate the case studies concerning this research. The focus of this project is to pr ovide further examination of how urban form impacts the potential for children to walk and bicycle to school. Th e methodology used in this study is largely based upon like methods being used in concurrent resear ch ongoing at the University of Florida funded in part by the Robert Wood Johnson Foundation1 (Steiner, et al., 2008; Bejleri, et al., 2008). The analysis area for this particular project invo lves elementary schools in Orange and Seminole Counties, located in and around the Orlando area in the centr al region of Florida. Establishing the Analysis Zones As mentioned in Chapter Two, the State of Florida has established a two mile buffer around school sites, which identifies the area th at district-school bussing is not provided, unless extenuating circumstances are present. Recogni zing the impracticality for students to walk or bicycle a distance of two miles to school, this study examines potential walkability within two smaller analysis zones: (1) Half-mile and (2) One-mile distances. These are assumed to be reasonable distances a child coul d be expected to walk or bi cycle to school based on findings from previous studies (Schlossberg, et al., 2006). This study uses ArcGIS software to generate halfand one-mile straig ht-line buffers around each school site in both of the case study regions. These buffer zones are referred to throughout this study as the Pedestrian Shed. Another zone has also been created by calculating the distan ce along the network path of streets around each school site. This zone is re ferred throughout the study as the Pedestrian Network Shed or 1 Robert Wood Johnson Foundation is an independent philanthropy devoted to improving health policy and practice. More information available at: http://www.rwjf.org/ 41

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sim ply the Network Shed. This zone represents a more realistic path a child might be expected to walk from home to school. However, due to the location of school si tes within established SAZs, the analysis zones sometimes extend beyo nd the boundary of the SAZ. In these unique circumstances, adjustments to the analysis zones are made to reflect the area that is contained within the SAZ boundary. Figure 3-1 provides an illustration of how these pedestrian (network) sheds are created around each school. As a means of investigating the affects of urban form on walkability, each school is examined within the parameters of the established analysis z ones, while controlling for school age based on development patterns that follo w a linear timeline of growth management and school coordination legislation in the State of Florida. The four development periods used to make comparisons are as follows: (1) Histori cal Schools (constructed before 1950); (2) PreGrowth Management Schools (construct ed between 1950 and 1985); (3) Pre-School Coordination Schools (constructed between 1986 and 1995); and (4) Post-School Coordination Schools (constructed after 1995). By comparing findings across these influential periods, the researcher intends to evaluate how physical development and policy actions have shaped urban environments and walkability around the case study school sites over time. Calculating Potential Walkabili ty: Indicators for Analysis This study utilizes two primary characteristic s of urban form to an alyze these conditions: (1) Street Connectivity and (2) Residential Densit y. These two characteristi cs were chosen based on the literature supporting their ability to prov ide a quantitative means of measuring potential walkability. The following sub-sections describe in further detail how each one of the above mentioned characteristics will be examined to analyze and evaluate walkability. 42

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Street Con nectivity Indicators To measure street connectivity three walkability indicators are used: (1) Street Density (the total number of linear miles of st reet per square mile); (2) Inte rsection Density (the total number of intersections per square mile); and (3) Pedest rian Route Directness (the ratio of the network distance to the Euclidean (straightline) distance between two points). Indicator #1: Street Density Street Density is used as an indicator to provide a quantit ative measure of the number of available pathways (available miles of streets) a child might be able to travel between home and school. This study will utilize th e street network as the surrogate pathway for measuring these connections. These pathways are identified by a calculation measuring the distance along the centerline of each street. A greater street density within the proximity of a school site presumably means that there is greater connectiv ity thus increasing the potential for a child to walk or bicycle to school. Street density is a calculation derived from dividing the total number of street miles by the total area (square miles) within a specified range In this case, the established analysis zones will be used as parameters in this study. Indicator #2: Intersection Density Intersection density is correlated to street patter ns in that intersections rely on the presence of street networks. Intersecti on density is also used to prov ide information of connectivity by illustrating nodes of intersection (junction between streets and roadways). Like street density, a higher degree of intersection dens ity presumably indicates higher levels of connectivity, thus providing environments that support a greater pote ntial for walkability. Intersection density is calculated by dividing the total number of intersections by the total area (square miles) within a specified range. Again this calculation will be conducted using the halfand one-mile analysis zones as boundaries. 43

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Indicator # 3: Pedestrian Route Directness PRD in the simplest of terms is a value repr esenting the directness of travel between two points. More specifically, it is a ratio between the straight-line distance of two points divided by the network distance between those same two points (an origin and a destination). In this study, PRD is measured using schools as destination po ints and using individual residential dwelling units as origin points. PRD is then tallied for each analysis zone using the average network and straight-line distances between residential dwelling units to the correspondi ng school they are zoned. Although a formative indicator of connec tivity, PRD is not always representative of walkable environments (Dill, 2004). Residential Density Indicators Residential density is also measured, using th ree indicators: (1) Gross Residential Density (total number of dwelling units per gross acre); (2) Net Residential Density (total number of dwelling units per residential parcel acre); and (3) Effectiv e Walking Area (the ratio of residential parcels within a [s pecified] network distance to th e number of residential parcels within the [same specified] radius distance of a destination). Residential density information used for this study was provided from data prepar ed in previous research (Steiner, et al., 2008; Bejleri, et al., 2008). Both Gross and Net residential densities ar e calculated by assigning dwelling unit counts to residential parcels within each school attendance zone. This information was created using land use codes acquired by th e Department of Revenue, dwelling unit counts for multifamily parcels using da ta from the 2006 American Community Survey, and additional information provided by the Bureau of Economic and Business Research, and county apartment complex records (Steiner, et al., 2008; Bejleri, et al., 2008). 44

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Indicators #4: Gross R esidential Density Gross residential density provides a value re presenting the total num ber of dwelling units per gross acre. Gross acreage in cludes all land use desi gnations (e.g.: reside ntial, commercial, industrial, etc.) in its ca lculation of residential density. Gross residential density will be used to compare the gross densities of re sidential dwellings between each analysis zone and the entire County over the four time periods. Indicator #5: Net Residential Density Net residential density provides a value repres enting the total number of dwelling units per residential parcel acre. The resi dential parcel acre is the acre age containing only residential land uses, excluding such land uses as mentioned in th e calculation of gross re sidential densities (e.g.: commercial). Net residential density will be comp ared to acceptable standards of net residential density to determine levels of walkability with in the established halfand one-mile analysis zones. These density findings will also be comp ared to the net densitie s for the entire County during the four time periods. Indicator #6: Effective Walking Area In addition to analyzing gross and net resident ial densities (total number of dwelling units per area), the researcher will also use EWA to investigate residential parcel ratios within proximity to school sites along connected street ne tworks. EWA is a ratio calculated by dividing the total number of residential parcels within a [specified] network distance to the total number of residential parcels within the [same specified] radius distance of a de stination (in this study, the destination is the school site). EWA valu es range between 0 and 1.00. Values closer to 1.00 represent greater percentages of residential parcels within the c onnected road network within a specified distance. Greater values presumably indicate higher levels of potential walkability. EWA will be examined along the halfand one-mile networks around each school site. 45

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Summary The m ethodology described in this chapter will help quantify patterns of urban form that impact the potential walkability of children tr aveling between home and school. Although there are many factors that can influence walkability, it should be noted that the indicators chosen for this study have proven to be effective in pr oviding reasonable determinations of potential walkability. It is assumed, based on the litera ture concerning developm ent patterns and the regulatory factors for the State of Florida, that street connectivity and residential densities will be best around the school sites built before 1950. Chapte r four of this study presents the findings resultant of these methods providing a m eans for evaluation and further discussion. 46

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47 Figure 3-1. Creation of Analysis Zones (Pedestrian Sheds) (Steiner, et al., 1008)

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CHAP TER 4 CASE STUDY FINDINGS AND RESULTS In this Chapter, findings from each cas e study are presented based upon the methodology that was described in Chapter Three. This Chapter is divided into four sect ions. The first section provides an overview of the case st udy areas to put into context the findings from this chapter. The second section presents findings from the Or ange County case study wh ile the third presents those from Seminole County. These two sections will include a synopsis of the findings related to each of the six walkability indicators describe d in the previous chapte r. The last section provides a summary and comparison of the fi ndings from both case study areas. Context of Study Region The two counties chosen for case study rese arch represent two distinct geographical regions of central Florida (see Fi gure 4-1). The first case stu dy examines Orange County, which is traditionally more urban in nature, encompassing an area of approximately nine-hundred square miles. Seminole County on the other hand is about a third of the si ze in total land area and consists of approximately th ree-hundred square miles. Both Counties have seen steadily growing populations since 1950, which in turn has spurred an incred ible amount of land development in and around this area of the State. In response to these growth rates, a number of new public school facilities have been constructed. The greatest influx of new school construction for both Counties occurred during the pre-growth management period in the State of Florida between 1950 and 1985. This growth accounted for 43 percent of the total schools built in Orange County and 59 percent of the total schools built in Seminole County. Prior to 1950, eight schools were constructed in Orange Count y, while only one was built in Seminole. Development before 1950 was certainly at a minimum in both Counties during this time, especially in Seminole County. Based on 200708 estimates, the total number of enrolled 48

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elem entary students in Orange and Seminole Counties is 82,501 and 21,756, respectively. These numbers are expected to incr ease in the coming years as the total population increases throughout the central Florida region. Acknowle dging these growth proj ections, it will be increasingly important to understand and address the impacts of the built environment as we plan for the future. Orange County Case Study The Orange County case study an alyzed 120 elementary schools, representing all of the elementary public school facilities within Orange County (see Figure 4-2). Six indicators of walkability were analyzed across four temporal development periods to provide the following findings. The first three indicators present find ings related to street connectivity while the second set of three indicators present findings associated with residential density. Indicator #1: Street Density An influential indicator used in determining the potential walkability of a place, is the density of streets. In Orange County, the highest total average for st reet density across all analysis zones was found around schools built prio r to 1950, with the highest of those values found within the half and one-mile pedestrian ne twork sheds. The actual highest average value of street densities is found w ithin the half-mile network shed during the pre-school coordination time period between 1986 and 1995. This is due to an outlier school embodying a street density of 51.1. During this same period, de nsities within the one-mile pedestrian network shed revealed a slight decrease, while both the half and one-mile pedestrian shed s saw considerable declines. For the schools built after 1995, street density co ntinued to decrease acros s all analysis zones with the exception of the one-mile pedestrian network shed which revealed a minimal increase. Figure 4-3 provides a graphical illu stration of these findings. 49

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Indicator # 2: Intersection Density Intersection densities are also measured to determine connectedness for walkability. Intersection density findings revealed the same general patterns as street density. Consistent with street density, the highest total average across all analysis z ones is found around schools built prior to 1950, with the highest of those values found within the half and one-mile pedestrian network sheds. After 1950, intersection density declined during the following two time periods, though the average within the half-mile pedestri an network shed increased between 1986 and 1995. Again this is due to the outlier school, w hose indicator value was 432.9. Paralleling street density values for schools built after 1995, intersection density de creased across all analysis zones with the exception of the one-mile pedest rian network shed which revealed a slight increase. Although the indicator va lues revealed a declining tre nd across all four time periods, the average density values for all analysis zones exceeded the acceptable standard (78 intersections per square mile) during each of the four time periods, except within the one-mile pedestrian shed around schools built after 1995. Fi gure 4-4 provides a graphical illustration of these findings. Indicator #3: Pedestrian Route Directness Similar to street and intersection density indica tors, PRD ratios revealed the lowest values for schools built before 1950, supporting the notion th at schools built during this period were located within more connected networks. Values during this time period averaged 1.6, which is slightly above the accepted standard (1.2 1.5) considered to be representative of good connectivity. As the overall trend for street and intersection density declined during the following two time periods, PRD ratios increased accordingly. However, around schools built after 1995, as street and intersection densities continued to decrease PRD ratios revealed decreasing values. Again the lowest values (still above the acceptable range) were found along 50

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the street networks for both the half and one-m ile pedestrian sheds. Interestingly, the PRD ratio for the one-mile pedestrian network shed revealed lower values (presuma bly better connectivity) than those shown within the half -mile network shed for all time periods, with exception of those schools built after 1995. This pattern is a reflection of more direct street routes o ccurring within the one-mile network area. Figure 4-5 provides a graphical illustration of these findings. Indicator #4: Gross Residential Density In Orange County, the average gross reside ntial density for the entire county is 1.9 dwelling units per gross acre. This number is based on total parcel acres within the entire county. Not surprisingly, schools built before 1950 revealed the highest levels of gross residential density across all analys is zones, with the highest levels occurring within the half and one-mile pedestrian network sheds. Gross residential densities revealed a decline in density during the two time periods following 1950, with signs of regeneration occurring around schools built after 1995. An interesting patt ern to note is the trend of gross residential densities within the half and one-mile pedestrian network sheds across the four time periods. Prior to 1950, the greatest gross residential density was found within the half mile network shed. During the following two periods, gross residential densities were greater within the one-mile network shed, with a resurgence of density within the half-mile network shed after 1995. Figure 4-6 provides a graphical illustration of these findings. Indicator #5: Net Residential Density Net residential density is also calculated, representing the number of dwelling units per residential parcel acre. The current average net residential density for Orange County is 4.5 dwelling units. The findings for net residential density are similar to the trends found with gross residential density, as the grea test densities are found to occur around schools built before 1950, with declining values during the following two time periods and rebounding occurring around 51

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schools built after 1995. Again, findi ngs reveal that the greatest net residential densities occur within the half and one-m ile pedestrian network sheds across all time periods. Furthermore, net residential density values within the connected netw orks exceed that of the average for the entire County. These findings show that greater ne t residential densitie s are occurring within connected networks around school s supporting even greater potenti al for children to walk and bicycle to school. Figure 4-7 provides a graphical illustration of these findings. Indicator #6: Effective Walking Area EWA is measured to determine the potential for walkability based on the percentage of zoned residential parcels that ex ist along the street network aro und school sites. Similar findings show consistency with the development patterns of residential density indicators, in that the highest values are seen around the schools built before 1950. For these schools, EWA findings show that just more than fifty percent of resident ial parcels within a half-mile of school sites are found along the half-mile street network. An add itional eighteen percent of residential parcels are found along the street network when calculati ng outward a distance of one-mile. Consistent with patterns of gross and net residential densi ties, EWA values began to decline during the pregrowth management and pre-school coordination time periods. Although residential densities show some resurgence following the pre-schoo l coordination time period, EWA values remain fairly static with little m ovement around schools built after 1995. Figure 4-8 provides a graphical illustration of these findings. Seminole County Case Study In the Seminole County case study, 28 of a total 37 elementary schools were analyzed. All thirty-seven schools considered fo r analysis were public school f acilities. However, the nine schools not included in this study are part of cluster attendance zones in which multiple schools exist within a single attendance zone (see Figure 4-9). For th e twenty-eight schools analyzed, 52

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findings will be presented based on the m ethodology set out in Chapter Three. Again, the first three indicators present findings related to st reet connectivity while the second set of three indicators present findings associated with residential density. Indicator #1: Street Density Street densities in Seminole County revealed vastly different trends than did findings from Orange County. Before 1950, development in Seminole County was minimal with the construction of only one school in the entire County. Street densities in Seminole County reflected the lowest averages around this school s ite, with considerable growth occurring during the pre-growth management period. Following 1985, street densities within the half and onemile pedestrian network sheds continued to increa se, while densities within the half and one-mile pedestrian sheds showed a decline. After 1995 during the post-school coordination period (1986 to 1995) street densities began to declin e across all analysis zones. Figure 4-10 provides a graphical illustration of these findings. Indicator #2: Intersection Density Intersection density followed the same general pa tterns as street density with relatively low values occurring around the single school site bui lt before 1950. Like street density, average intersection density values increased within all analysis zones duri ng the following two time periods, except for a considerable decline among the average values within the one-mile pedestrian shed between 1986 and 1995. During the same period that values fell within the onemile pedestrian shed, the average indicator values within the half-mile pedestrian network shed increased sharply. The overall trend shows that intersection densities have been increasing since 1950. However, consistent with street density tr ends, intersection density also showed a decline across all analysis zones around schools built after 1995. Although there are some fluctuations in the overall findings, its impor tant to note that densities w ithin the half-mile and one-mile 53

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pedestrian n etwork sheds exceeded the acceptable standard (78 intersecti ons per square mile) during all time periods, except within the one-mile pedestrian network shed prior to 1950. Figure 4-11 provides a graphical illust ration of these findings. Indicator #3: Pedestrian Route Directness PRD ratios revealed somewhat consistent valu es related to both street and intersection densities. However, PRD was lowest for the school site built prio r to 1950, even though indicators of street connectivity re vealed relatively low values of st reet and intersec tion densities. Although the PRD ratio during this period averaged 1.4 (for all analysis zones), good street connectivity is apparent only w ithin the half-mile network she d. When extending the analysis area out to the one-mile network, PRD ratios rema in constant, likely due to long stretches of roadway. This type of scenario proves why using a single indicator fo r measurement can convey misleading findings. Furthermore, as street conne ctivity presumably increased based upon street and intersections densities, PRD va lues also increased, revealing less direct travel patterns. After 1985, PRD ratios decreased within the half and one-m ile pedestrian network sheds, while values increased within the half and one-mile pedestrian sheds, revealing some consistency with street density patterns. Other than dropping to a value of 1.9 within th e one-mile network shed during the pre-school coordination time period, PRD values were found to be well above the accepted standard for good connectivity with in all analysis z ones across all time periods. Figure 4-12 provides a graphical illustrati on of these findings. Indicator #4: Gross Residential Density In Seminole County, gross residential density currently consists of about 1.6 dwelling units per gross acre. Again, this number does not exclude any land uses in its calculation. The gross residential density for the school site built before 1950 showed the lowest values for all analysis zones. The highest value during th is time period is still less than one dwelling unit per gross acre 54

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(0.73 within the half-m ile pedestri an network shed). Gross reside ntial densities increased across all analysis zones for schools built between 1950 and 1985. Numb ers then began to decline during the following period, with ex ception of the one-mile pedestrian network shed which saw a slight increase (nothing of statistical value). After 1995, gross residential densities declined for all analysis zones, with the highest values occurring within th e half and one-mile pedestrian network sheds. Figure 4-13 provides a graphical illustration of these findings. Indicator #5: Net Residential Density Net residential density for Seminole County wa s conducted only within the analysis zones around each school site and not at the County leve l, due to unforeseen circumstances regarding data availability. However, the information gath ered from the analysis zones have provided valuable insight. Consistent w ith the findings of gross resident ial density, net densities were lowest around the school site built before 1950. During the pre-growth management period from 1950 and 1986, net residential densit ies increased sharply, especi ally within the half-mile pedestrian network shed. Average densities durin g this period peaked at 4.7 units. Following this period, slight increases were found within the half-mile pedestrian shed and the one-mile network shed, while there were reductions within the one-mile pedestrian shed and half-mile network shed. Net residential density then de creased within all anal ysis zones around schools built after 1995, with the greatest densities, again found along the stre et networks in both the half and one-mile pedestrian network sheds. Figure 4-14 provides a graphical illustration of these findings. Indicator #6: Effective Walking Area After calculating the EWA for Seminole County, findings revealed that seventy-two percent of residential parcels f ound within a half-mile of the school site built before 1950 were sited along the street network. Th e percentage of residential pa rcels along the one-mile street 55

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network was only fifty-six percent, revealing that a gr eater number of zone d residential parcels were situated within th e half-m ile range of the school site. Although findings from both gross and net residential densities showed consider able increases in density for the time period between 1950 and 1986, EWA began to decrease, es pecially the average number of parcels found within the half-mile networ k area. Findings reveal that schools built dur ing this period and through to 1995, showed continual declines. Fo r the school locations that were sited after 1995, EWA remained constant within the half-mile network, but continued to decline within the one-mile network area. Figure 4-15 provides a graphical illustrati on of these findings. Summary In both case studies, the majority of findi ngs revealed that there were symbiotic relationships between each of the measurable indi cators. In Orange Count y, it was apparent that street connectivity and residen tial density were the greatest around the schools built before 1950. During the following two time periods, values d eclined, with some resurgence of residential density around the schools built after 1995. Unlike Orange County, Seminole County revealed the lowest values for both street connectivity and residential density aroun d the school site built before 1950. Additionally, indicato r values increased during the pre-growth management period, with fluctuating values during the pre-school coordination period. Seminole revealed some similarities to the findings in Orange County, in that street co nnectivity indica tors revealed decreasing values for schools sited after 1995. Ho wever, the most remarkable finding from both Counties was the average values for intersec tion densities within the halfand one-mile pedestrian network sheds. In both Counties, values exceeded the acceptable standard (except within the pedestrian network shed in Orange County), which is indicative of good connectivity. The most notable difference between the two Coun ties was the continual decline of residential 56

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density values in Sem inole County, while values in Orange Count y revealed some resurgence after 1995. Although the two Counties returned different results, the in dicator values have proven to be effective. This is apparent from the paralleling relationships between both the street connectivity and residential density indicators within each of the studies. However, in some instances, findings revealed contradictory behavior, making it difficult to provide any explanation. For instance diffe ring patterns between increasing va lues within the network shed and decreasing values within the pedestrian shed (concerning a single indi cator such as street density). The item to note, howev er, is that better connectivit y is occurring along the street network. It is also important to understand that this study has ex amined data at the aggregate level and that the findings have been evaluated holistically across the four time periods and not at a micro level investigating the exact reasonings for all shifts. The next chapter provides a discussion of th e findings detailed here. With a better understanding of how urban form has evolved over the past half-a-centu ry, the researcher will begin to relate how the findings from this st udy correspond to trends in physical activity and rising childhood obesity rates. The following ch apter also presents conclusions and provides recommendations for future research regarding this and related topics. 57

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58 2007 Population Land Area (Square Miles) Persons per Square Mile Number of Elementary Schools in Study Number of Enrolled Elementary Students (20072008) Orange County 1,066,113 907.51,174.8012082,501 Seminole County 409,509 308.21,328.702821,756 Figure 4-1. Overview of Study Area

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Street Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 18.83 14.91 13.06 12.58 Half-mile Pedestrian Network Shed (adjusted) 20.93 19.98 22.68 22.14 One-mile Pedestrian Shed (adjusted) 15.80 13.64 11.98 11.66 One-mile Pedestrian Network Shed (adjusted) 19.41 18.50 18.35 18.98 Total Average 18.74 16.76 16.52 16.34 Street Density (Orange County)0.00 5.00 10.00 15.00 20.00 25.00 Before 19501950 19851986 1995After 1995Linear Miles per Square Mile Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-3. Graphical Illustration of Street Density in Orange County 59

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Intersection Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 149.13 106.03 82.93 81.91 Half-mile Pedestrian Network Shed (adjusted) 177.43 156.21 173.83 145.26 One-mile Pedestrian Shed (adjusted) 121.59 98.08 80.20 76.34 One-mile Pedestrian Network Shed (adjusted) 152.45 137.00 124.57 134.69 Total Average 150.15 124.33 115.38 109.55 Intersection Density (Orange County)0.00 20.00 40.00 60.00 80.00 100.00 120.00 140.00 160.00 180.00 200.00 Before 19501950 19851986 1995After 1995Intersections per Square Mile Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-4. Graphical Illu stration of Intersection De nsity in Orange County 60

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Pedestrian R oute Directness Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 1.68 2.23 2.91 2.47 Half-mile Pedestrian Network Shed (adjusted) 1.57 1.80 2.15 1.92 One-mile Pedestrian Shed (adjusted) 1.56 1.91 2.46 2.17 One-mile Pedestrian Network Shed (adjusted) 1.51 1.78 1.94 1.93 Total Average 1.58 1.93 2.36 2.12 Pedestrian Route Directness (Orange County)0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Before 19501950 19851986 1995After 1995Network / Euclidean Distance Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-5. Graphical Illust ration of Pedestrian Route Directness in Orange County 61

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Gross Residential Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 3.87 2.56 1.70 1.89 Half-mile Pedestrian Network Shed (adjusted) 4.26 2.73 1.87 2.55 One-mile Pedestrian Shed (adjusted) 3.40 2.26 1.49 1.69 One-mile Pedestrian Network Shed (adjusted) 3.90 2.81 2.14 2.43 Total Average 3.86 2.59 1.80 2.14 Gross Residential Density (Orange County)0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 Before 19501950 19851986 1995After 1995Dwelling Units per Gross Acre Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-6. Graphical Illust ration of Gross Residential Density in Orange County 62

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Net Residential Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 8.40 5.35 3.51 3.81 Half-mile Pedestrian Network Shed (adjusted) 8.99 6.24 3.91 5.32 One-mile Pedestrian Shed (adjusted) 8.65 5.21 3.26 3.76 One-mile Pedestrian Network Shed (adjusted) 8.75 5.96 3.96 4.61 Total Average 8.70 5.69 3.66 4.38 Net Residential Density (Orange County)0.00 1.00 2.00 3.00 4.00 5.00 6.00 7.00 8.00 9.00 10.00 Before 19501950 19851986 1995After 1995Dwelling Units per Residential Parcel Acre Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-7. Graphical Illust ration of Net Residential Density in Orange County 63

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Effective Walking Area Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Network Shed (adjusted) 0.53 0.34 0.22 0.24 One-mile Pedestrian Network Shed (adjusted) 0.71 0.57 0.40 0.40 Effective Walking Area (Orange County)0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Before 19501950 19851986 1995After 1995Ratio of Residential Parcels (Network) / Residential Parcels (Eclidean) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-8. Graphical Illust ration of Effective Walking Area in Orange County 64

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Figure 4-9. Map of Seminole County Sc hool Attendance Zones and Schools 65

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Street Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 9.31 15.53 13.18 10.74 Half-mile Pedestrian Network Shed (adjusted) 17.96 19.45 25.10 22.30 One-mile Pedestrian Shed (adjusted) 5.56 14.01 11.18 10.43 One-mile Pedestrian Network Shed (adjusted) 13.50 18.09 20.64 19.70 Total Average 11.58 16.77 17.53 15.79 Street Density (Seminole County)0.00 5.00 10.00 15.00 20.00 25.00 30.00 Before 19501950 19851986 1995After 1995Linear Miles per Square Mile Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-10. Graphical Illustration of Street Density in Seminole County 66

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Intersection Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 31.84 61.88 69.38 46.76 Half-mile Pedestrian Network Shed (adjusted) 114.62 133.92 203.03 91.07 One-mile Pedestrian Shed (adjusted) 21.33 94.39 64.09 47.60 One-mile Pedestrian Network Shed (adjusted) 62.65 127.42 138.52 94.13 Total Average 57.61 104.40 118.75 69.89 Intersection Density (Seminole County)0.00 50.00 100.00 150.00 200.00 250.00 Before 19501950 19851986 1995After 1995Intersections per Square Mile Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-11. Graphical I llustration of Intersection Density in Seminole County 67

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Pedestrian R oute Directness Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 1.45 2.46 3.26 3.19 Half-mile Pedestrian Network Shed (adjusted) 1.41 2.31 2.01 2.49 One-mile Pedestrian Shed (adjusted) 1.45 2.02 2.52 2.49 One-mile Pedestrian Network Shed (adjusted) 1.44 2.07 1.92 2.26 Total Average 1.44 2.22 2.43 2.61 Pedestrian Route Directness (Seminole County)0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 Before 19501950 19851986 1995After 1995Network / Euclidean Distance Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-12. Graphical Illust ration of Pedestrian Route Directness in Seminole County 68

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Gross Residential Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 0.36 2.25 1.88 0.97 Half-mile Pedestrian Network Shed (adjusted) 0.73 2.19 2.00 1.24 One-mile Pedestrian Shed (adjusted) 0.18 2.13 1.50 1.09 One-mile Pedestrian Network Shed (adjusted) 0.35 2.25 2.38 1.56 Total Average 0.40 2.21 1.94 1.21 Gross Residential Density (Seminole County)0.00 0.50 1.00 1.50 2.00 2.50 3.00 Before 19501950 19851986 1995After 1995Dwelling Units per Gross Acr e Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-13. Graphical Illu stration of Gross Residentia l Density in Seminole County 69

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Net Residential Density Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Shed (adjusted) 0.78 4.29 4.38 2.79 Half-mile Pedestrian Network Shed (adjusted) 1.82 4.72 4.51 3.16 One-mile Pedestrian Shed (adjusted) 0.41 4.05 3.68 2.60 One-mile Pedestrian Network Shed (adjusted) 0.89 4.36 4.44 3.61 Total Average 0.98 4.36 4.25 3.04 Net Residential Density (Seminole County)0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00 4.50 5.00 Before 19501950 19851986 1995After 1995Dwelling Units per Residential Parcel Acre Half-mile Pedestrian Shed (adjusted) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-14. Graphical Illu stration of Net Residential Density in Seminole County 70

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71 Effective Walking Area Before 1950 1950 1985 1986 1995 After 1995 Half-mile Pedestrian Network Shed (adjusted) 0.72 0.27 0.19 0.19 One-mile Pedestrian Network Shed (adjusted) 0.56 0.43 0.36 0.26 Effective Walking Area (Seminole County)0.00 0.10 0.20 0.30 0.40 0.50 0.60 0.70 0.80 Before 19501950 19851986 1995After 1995Ratio of Residential Parcels (Network) / Residential Parcels (Eclidean) Half-mile Pedestrian Network Shed (adjusted) One-mile Pedestrian Network Shed (adjusted) Figure 4-15. Graphical Illu stration of Effective Walk ing Area in Seminole County

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CHAP TER 5 DISCUSSIONS AND CONCLUSIONS The final chapter of this pape r will provide a discussion of how the research conducted in this study supports the question of how urban form impacts the potential for children to walk and bicycle to school. These discussions will also address a subsequent research question somewhat of an undertone of this study that asks how does the built environment impact physical activity and childhood obesity? The intent of this study was to: Provide further insight of the impacts that the built environment poses on public health Make a valuable contribution towards the unde rstanding of urban form and how it impacts physical activity; Raise awareness about the relationship between the built environment and the ability for people to participate in active travel; Provide a useful resource for others to use in developing similar studies for future research Although this study focuses primarily on the abil ity of children to walk and bicycle to school, the same methodology could be used to determine the potential walkability of any population within the built environment. Discussions and Conclusions This study chose to use street connectivity and residential density tw o characteristics of urban form to investigate poten tial walkability around school site s. Based on the findings from this study and the supportive literat ure, it is assumed that there is a higher probability for walkability within the areas exhibiting more tradi tional styles of developm ent. These consist of more grid-like street networks and a structured grouping of residential densities. In the Orange County case study it was clear that street connect ivity was best around the historic schools built before 1950, considering all analysis zones. Mo re traditional developm ent patterns were found around these school sites particularly influenced by intersection density indicators. Additionally, 72

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above average intersection density values we re found along the street network for all tim e periods further indicating good c onnectivity around Orange County schools. These patterns also hold true for residential density trends, which show the highest density of residential parcels around school sites built before 1950. Respectiv e values decreased during the following two time periods, with a slight re surgence around the schools built after 1995. Not surprising, the effective walking area for school sites in Orange County showed that the greatest potential for walkability around schools built before 1950, based on the high percentage of residential parcels found along the street network. Figure 5-1 provides an illustration of schools (one for each time period), characterizing the more traditional development styles before 1950, the more suburban nature of development during the following two ti me periods, and the resurgence of residential density after 1995. Considering these findings, it s clear that the potentia l for walkability is highest around the historical schools which exhibit more trad itional development styles. Although patterns revealed decreased walkability based on declining street connectivity and residential densities between the pre-growth management and pre-school coordination time periods, it is encouragin g to see residential density patter ns increasing around the schools built after 1995. Furthermore, intersec tion densities, although decreasing on the whole, are still well above the acceptable standard for all but one of the analysis zones. Seminole County exhibited different trends than those seen in Orange County. Both street connectivity and residential density indicators revealed the weakest values during the period before 1950, though during this same time period EWA was exceptionally high. This is likely due to the minimal amount of residentially deve loped parcels around the sc hool site (low number of dwelling units compared to th e total number of existing residen tial parcels). The EWA ratio is based on the total number of zoned residential parcels and not the num ber of dwelling units 73

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within those parcels. Ultim ately, EWA can only provide a generalization of potential walkability based on the number of residential parcels that exist in a specific area. However, the positive thing to note (especially in the example noted ab ove) is that, although resi dential development is low, the majority of residential parcels are lo cated along the street network, thus exhibiting a greater potential for walkability. This is especially true if the area were to be developed more intensively in the future. Figure 5-2 provides a visual illustration of EWA to help explain. Following 1950, there was a boom in development w ith an increase of resi dential densities and street connectivity around a host of new schools across the entire County. However, following 1985 patterns became erratic, with increasing and d ecreasing values across all analysis zones. However, intersection density values within the pedestrian network sheds exceeded the acceptable standard, providing some semblance of good connectivity around schools in Seminole County. Figure 5-3 provides an illustration of a sample of schools across the different development periods, showing the general tren ds occurring in Seminole County. The low connectivity and residential density findings seen before 1950 may also be due to a small sample size reflective of there only being one school constructed before 1950. Furthermore, land development on the whole across Seminole County for the four time periods seemed to have been growing at a slower rate than neighboring Orange County. If provided the opportunity to examine Seminole County in the next decade, it would be interesting to see if resurgence of better connectivity and residen tial densities (more compact de velopment) are occurring. However, based on the current findings, it se ems that Seminole County although legally bound by the State to conform to regulatory measur es regarding growth management and school concurrency may still be developing by its own accord. 74

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Overall, Orange County is m ore in tune with the States legislative policies, even though continual declines are seen am ong street connectivity indicato rs. Conversely, Seminole County does not seem to be following any development tre nds respective of the States policy inactions. Although different patterns were f ound in the two case studies, the indicators within each study showed consistency between one another, valida ting the use of the chosen characteristics as respected means in measuring potential walkabi lity. The methodology used in this study proves to be a beneficial resource that could be used to evaluate other communities. As mentioned, specifically in Orange County, there seems to be a resurgence of residential density occurring around newer schools. This may in part be due to policies that oversee improvements in coordination between decision makers regardi ng school siting and neighborhood development. Additionally, market demand may also be enco uraging further production of neo-traditional developments, such as the Baldwin Park nei ghborhood. Development archetypes such as the new urbanism and the ideology of Smart Growth have been increasing in popularity nation-wide. With the State overseeing growth issues, and en couraging new development techniques arising, the State of Florida has the tools to develop mo re highly walkable and healthy communities. So how do traditional design, physical (in)activity and obesity relate? How can it provide solutions for developing safer, healthier communities? Bridging Community Develo pment and Public Health Healthy physical and psychosocial behaviors have been linked to our physical (built and natural) environments. One of many components is our dependence on social interactions within the community. Limiting existence to physical sustenance (access to places) minimizes human interactions. This can be extremely detrimenta l to the health of individuals and a community, Seymour Sarason (1974, viii), a leading writer in the field of commun ity psychology, has argued that the dilution or absence of the psychological sense of community is the most destructive 75

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dynam ic in the lives of people in our societ y (Lucy, 1994, p. 312). A lack of psychological connection in a community in many instances is due to the lack of physical cohesion of the community. Many of the communities we see across the U.S. today are disconnected and unidentifiable, leading to places that lack interest, and are dominated by automobile travel. However, compact community development types typical of higher density and connectivity can potentially increase the opportunitie s for people to engage in da ily interactions within the community, thus increasing social stability and healthy physical and psychological behaviors. As seen in this research study, the built environm ent plays a potential role in guiding decisions on whether to walk or bicycle for utilitarian tr avel purposes. However, there have been some inhibiting factors along the way which have reduced the possibilities for more compact development types. Since the inception of zoning laws in res ponse to growing industrial centers around the world, public health has proven to be a critical topic of concern. In the United Sates, the landmark case between the Village of Euclid and Ambler Realty 1 revealed just how closely land use (development) and public health are related. As a means in stymieing environmental and public nuisances (namely industria l intoxicants) near residential dwellings, the Supreme Court found in favor of separating land uses in what is now defined as Euclidean zoning2. This new zoning order and disconnection of land uses in many ways has contributed to what we identify 1 Village of Euclid vs. Ambler Realty was a United States Supreme Court case argued in 1926. It was the first significant case regarding the relatively new practice of zoning, serving to substantially bolster zoning ordinances in towns nationwide across the United States. More information available at: http://supreme.justia.com/us/272/365/case.html 2 Euclidean zoning is the separation or division of a muni cipality into districts, the regulation of buildings and structures in such districts in accordance with their construction and the nature and extent of their use, and the dedication of such districts to particular uses designed to serve the general welfare. More information available at: http://legal-dictionary.thefreedictionary.com/ 76

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all over the United States, as urban sprawl. Unfortunately, the repe rcussions have been destructive, both environm entally and in terms of population h ealth (Schilling & Linton, 2005). Addressing community livability and the hea lth of people by introducing more compact development can provide more highly livable environments potenti ally alleviating patterns of suburban sprawl, reconnecting social interact ions, and decreasing environmental hazards. Furthermore, developing in a more tradit ional manner, focusing on community-orientated approaches, can have a profound affect on the hea lth of individuals in a community, especially children. When addressing the issu e of walkability, it is not clear exactly all of the factors that influence a persons choice to be ac tive or not in their travel behaviors. There are some, but in many instances it is extremely difficult. Even if ur ban form suggests that a place is walkable; is it really? What are the factors facilitating or inhibiting behaviors in so-called walkable environments? Can walkability be encouraged by creating more compact developments? The bigger question may be; do people want to be physic ally active, specifically speaking in terms of their travel routines? The old ad age of if you build it, they will come, is really an uncertainty. Marlon Boarnet raises an interesting point: Persons might choose their environments in part based on their desired level of physical activity. It does not take much imagination to believe that an avid surfer would choose to live near the beach or that a ski enthusiast would move near the mountains. Generalizing to other, more common forms of physical activ ity, do persons who wish to walk choose residences in pedestrian-orien ted neighborhoods near parks? If so, the association between physical activity and urban form might repr esent a persons reside ntial location choice rather than an influence of the built environment on activity (2004, p. 3). What are the affects of (re)developing a nei ghborhood into a pedestrian -friendly place that encourages walking and bicycling if the residents of that community have a disinterest in living active lifestyles? These and many ot her questions are at the core of trying to better understand how the built environment a ffects population health. 77

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One of the key features in trad itional devel opments prior to 1950 was the institution of schools as focal points located at the center of the community. In many neighborhoods, schools were located in close proximity to parks, re creational areas and othe r community and civic assets. Neighborhood schools, planned with a co mmunity-oriented appro ach retain residents who use nearby schools for a variety of activities other than just education. Having a school at the core of the community provides a wealth of opportunities and services for both children and adults, such as parks and playgrounds, athletic facilities, health and wellness centers, libraries, and adult education opport unities. Schools also serve as places that host community events such as theater productions, local music and art festivals, community m eetings, and even local farmers markets. Furthermore, a school that provides a ho st of services within the community limits the need for constructing additional facilities requiring funding from tax dollars (Spengler, Young, & Linton, 2007). These and other factors make schools ideal places that contribute to a sense of a place providing the social interactions that ma ke communities healthy and enjoyable places to be. Moreover, to increase walkability of schools, its important for them to be located within a reasonable proximity to the neighborhoods they serv e. School coordination regarding issues of size of school, site location and building design are as important if not more important than the physical elements that support the physical act of traveling to school (e.g., sidewalks, bicycle lanes, etc). Understanding the conditions that contribu te to mode choice s of younger populations, particularly to school is impor tant. Although the number of ch ildren who walk and bicycle to school has decreased dramatically, studies show that children do engage in active travel opportunities to school (Fulton, Shisler, Yore, & Caspersen, 2003). In addition to physical design elements, there are many programs and orga nizations which contribute to increasing the 78

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safety and walkability of environm ents around schools. One of the most notable programs is the Safe Routes to School program (SRTS) 3 SRTS promotes walking and biking to school through education. It encourages greater enforcem ent of traffic laws, educating the public, and exploring ways to create safer streets for children trave ling to and from school. Another notable program is the Florida Traffic and Bicycle Safety Education Program (FTBSEP) 4 The FTBSEP program is jointly operated between the Departm ent of Tr ansportation and the University of Florida. The main goal of the organization is to administer a traffic and bi cycle safety education program through workshops and certificate programs for Fl orida elementary and middle schools, reducing the incidence of pedestrian-vehicular accidents. Understanding travel behaviors is just one part. Addressing the impacts of the built environment is another. Together, through cooperative efforts, increasing the likelihood of active travel is possible. It is also imperative that we continue to support physical educ ation in the classroom. Impac ting a childs physical health through education in school can potentially encourage phys ical activity in other instances of a childs life. Studies have shown that children who are more physically active early in life tend to be more physically active later in life (Telama, Yang, Viikari, Valimaki, Wanne, & Raitakari, 2005). However, the need to encourage physical activity extends beyond the classroom. As this and other studies suggest, our environmental surroundings play critical ro les, influencing the ways we live and operate in society. Unders tanding how to effectively design our built environments will be critical in supporting the he alth of populations for generations to come. This is especially true for the region of central Florida where this study ta kes place, as expected growth and development are predicted to skyrocket duri ng the next fifty years. 3 SRTS More information available at: http://www.saferoutestoschools.org/index.shtml 4 FTBSEP More information available at: http://www.hhp.ufl.edu/safety/index.html 79

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Limita tions of this Study Because this study was inherited as a contin uing research opportunity, the researcher utilized previously existing data sets to conduct this study. Some data sets were unavailable for use in further investigation. This however, was not detrimental in conducting the overall research analysis for this project. In addition to data availability, there were some additional limitations pertaining to time and monetary c onstraints, which permitting could have yielded more in depth analyses. Considering data availability, the methodology used two distinct measures to calculate potential walkability; street connectivity and residential de nsity. In examining street connectivity, the researcher used the centerline of streets as a proxy in measuring potential walkability. Due to the aggregat e nature of this study, the use of street networks in measuring connectivity provided a reasonable se t of findings relative to genera l patterns of urban form and their impacts. However, a more realistic determ ination for walkability could have been made by examining actual pedestrian networks, which would consider elements such as sidewalks, crosswalks, speed limits, informal paths, fences, walls, crossing guards, personal safety, and lanes of traffic (Bejleri, et al., 2008, p.12). One particular dataset that posed a limitation on this study was residential parcel data for the areas outside of the analysis z ones in Seminole County, specifically the net calculations. The purpose for calculating the resident ial densities for th e surrounding area of the County is to provide a comparison between what is occurring inside of the analysis area s to what is happening outside of them. Although net resi dential densities were calculated for the analysis zones, net residential density information for the rest of the County had not been generated. Needed information included parcel boundaries and recalcu lation of dwelling unit information. However, due to time constraints, generating the GIS datasets was not feasible. Remedying the residential 80

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parcel inform ation for the areas outside of the an alysis zones is important, as it examines how urban form is impacting schools within the areas where children can most likely be expected to walk and bicycle compared to the averages of what is occurring across the rest of the County. Because this study examined development trends across four influential time periods of Floridas growth generating assertions that policy inactions played a critical role in determining physical environments its importa nt to note that no research was conducted in examining changes in redevelopment or reconstruc tion particularly within the analysis zones. Although a school was built during a specific development period, the findings are not necessarily representative of the conditions around the school and the neighborhood when they were first constructed. It is im portant to note, that land use zo ning designations are variably dynamic, while street and road ne tworks are relatively static. Ov er time, the different uses of land occupation (e.g., buildings, structures, open spaces) with their unique uses come and go, while streets tend to undergo minimal changes. However, in conducting this study, it is assumed that what is there now, existed there when the area was originally constructed. Researching the evolution of development across the examined time periods could potentially impact the findings of this study. Ideally, a study of this nature requires more research and anal ysis than simply using a GIS for making interpretations. A final limitation in this study was the inability to conduct field audits of the subject schools. S ite visits were not possible due to time and monetary constraints, but if performed could have presented more accu rate findings. Key elements recommended for physical examination could include: construction of the school facility (design elements), placement and arrangement of the school on the s ite, street conditions around the school (design 81

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and m aintenance), investigation of adjacent land us es, and safety (objective) of the school and the surrounding neighborhood. Opportunities for Future Research The research on the topics of physical activit y and childhood obesity are extremely diverse, especially when concerning the impacts presen ted by the built environment. There are many arguments both for and against how the built environment, physical activity, and childhood obesity are related, but few are su fficient in making sound correlations. This is in part due to the complexities of urban environments and the behaviors of the people living within them. However, several things are for certain: Urban development has been increasingly moving to the periphery and away from urban cores, people are walking and bicycling less, and the overweight and obesity epidemic is real, placing unnecessary burdens on our society. Because were just beginning to realize that ther e may be harmful affects betw een the ways we develop our communities on the health of the people who inha bit them, the opportunities for future research on this and similar topics are plentiful. One particular set of data which could shine more light on the issue of childhood obe sity is the availability of BMI data. This information in conjunction with other methods of investig ation could help produce, more educated assumptions concerning the examination of all types of influences on a childs weight. Although there are laws in place, protecting the safety and personal privacy of minors in research st udies, there are ways to protect and keep sensitive data confidential, while stil l acquiring the necessary information in making more precise research evaluations. The availability of data concerning BMI levels for [wellintentioned] research use will prove to be extrao rdinarily beneficial for the health and well being of individuals and society as a whole. 82

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Specifically acknowledging this study, several issues should be addressed imm ediately, including the data retrieval and input of the residential parcel boundaries into GIS for Seminole County. A number of other studies would also pr ove beneficial. Other studies currently ongoing on this topic within the same study area (Steiner, et al., 2008) have conducted survey analysis of the number of children who walk and bicycle to school. Future research may want to consider additiona l surveys of the number of children who travel from school to home. Studies have shown that the number of children who travel home from school is in some instances greater than that traveling to school (Sch lossberg, et al., 2006). Understanding the travel patterns of children between school and home will help to support additional theories regarding th e impacts urban environments. Another opportunity for consider ation is to perform detailed field audits. Though they can be expensive and time intensive, physical interaction with the actual environment will provide more accurate interpretations of the conditions. This study utilizes only a few of the tools available in researching potentially walkabilit y. However, other tool s are available and are encouraged for use, especially if conducting fiel d audits. In particular, the Design Guidelines for Pedestrian-Friendly Neighborho od Schools, prepared by the City of Raleigh, North Carolina is an appropriate resource to consider (City of Raleigh, N.C., 2008). Conducting field audits will provide additional information to help support a nd quite possibly negate some of the findings from this study. When considering future research designs intend ed to examine evidence of causality in the relationship between the built environment, physi cal activity, and obesity, it is important to realize that sound conclusions can not be made based on the results of a single research study. All studies are unique and contain weaknesses. Its encouraged that both academics and 83

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practitioners branch out to gain an understanding of ot her disciplines and pract ices that deal with health issues, developm ent decisions, a nd issues of design. Having a well rounded understanding of the multitude of factors that contribute to the ways we live and function is imperative to making gainful contributi ons to studies such as this one. 84

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Historic School (Before 1950) Street Density: 21.6 Intersection Density: 185.2 P R D Ratio: 1.5 Pre-Growth Management (1950 1985) Street Density: 19.2 Intersection Density: 152.0 PRD Ratio: 1.7 Post-School Coordination (After 1995) Street Density: 17.6 Intersection Density: 106.7 PRD Ratio: 1.8 Pre-School Coordination (1986 1995) Street Density: 14.0 Intersection Density: 88.3 PRD Ratio: 2.0 Figure 5-1.C onnectivity Indicators of Sample Schools in Orange County 85

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Historic School: (Before 1950) Street Density: 9.3 Intersection Density: 31.8 PRD Ratio: 1.5 Gross Residential Density: 0.4 Net Residential Density: 0.8 EWA: 0.72 Figure 5-2. Effective Walking Area of Sa mple Elementary School in Seminole County 86

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87 Historic School (Before 1950 ) Street Density: 13.5 Intersection Density: 62.7 PRD Ratio: 1.4 Pre-Growth Management (1950 1985) Street Density: 15.7 Intersection Density: 115.6 PRD Ratio: 2.2 Pre-School Coordination (1986 1995) Street Density: 21.0 Intersection Density: 148.4 PRD Ratio: 1.8 Post-School Coordination (After 1995) Street Density: 21.0 Intersection Density: 104.1 PRD Ratio: 1.6Figure 5-3. Connectivity Indicators of Sa mple Schools in Seminole County

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LIST OF REFERE NCES 1000 Friends of Florida, Florida 2060: A Population Distribution Scenario Retrieved February 7, 2009, from http://www.1000friendsofflor ida.org/planning/main.asp Atash, F. (1 994). Redesigning suburbia for walking and transit: Emerging concepts. Journal of Urban Planning and Development 120 (1), 48-57. Aultman-Hall, L., Roorda, M., & Baetz, B. (1997). Using GIS for Evaluation of Neighborhood Pedestrian Accessibility. Journal of Urban Planning and Development 123(1), 10-17. Bejleri, I, Steiner, R.L., Provost, R.E ., Fischman, A., & Arafat, A.A. (2008). Understanding and Mapping Elements of Urban Form that Affect Childrens Ability to Walk and Bicycle to School: A Case Study of Two Tampa Bay Counties Unpublished document, University of Florida. Boarnet, M. & Crane, R. (2001). The Influence of Land Use on Travel Behavior: Specification and Estimation Strategies. Transportation Research Part A: Policy and Practice 35(9), 823-845. Boarnet, M.G., (2004). The Built Environment and Physical Activity: Empirical Methods and Data Resources. Prepared for the Transportation Research Board and the Institute of Medicine Committee on Physical Activity, Health, Transportation, and Land Use, TRB Special Report 282. Boggs, G.H. & Apgar, R.C. (1991). Concurrency and growth management: A lawyers primer. Journal of Land Use and Environmental Law 7(1), 1. Calthorpe, P. (1993). The Next American Metr opolis: Ecology, Community, and the American Dream, New York: Princeton Architectural Press. Campbell, E.K. & Wang, Q. (2008). Pupil Transportation: Factors Affecting Mode Choice and the Amount of Parent-driven Trips to School, University of Verm ont, Department of Community Development and Applied Economics, No: 09-3753. Retrieved February 24, 2009, from http://www.uvm.edu/~transctr/trbpapers/ECam pbellTRBPoster09.pdf Centers for Disease Control and Prevention (2006). NHANE S data on th e Prevalence of Overweight Among Children and Adolescents: United St ates, 2003, NCHS (National Center for Health Statistics) Health E-Stat. Retrieved February 7, 2009, from http://www.cdc.gov/nchs/products/pubs/pubd/hestats/overweight/overwght_child_03.htm Centers for Disease Control and Prevention (2007). New CDC Study Finds No Increase in Obesity Am ong Adults; But Levels Still High, NCHS (N ational Center for H ealth Statistics). Retrieved February 7, 2009, from http://www.cdc.gov/nchs/pressroom /07newsreleases/obesity.htm Cervero, R. & Kockelman, K. (1997). Travel Dem and and the 3Ds: Density, Diversity, and Design. Transportation Research Design Part D 2(3), 199-219. 88

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Forsyth, A. (2003). Measuring Density: Working Definitions for Residential Density and Building Intens ity. Design Center for American Urban La ndscape, College of Architecture and Landscape Architecture, University of Minnesota, Design Brief, No. 8. Frumkin, H., Frank, L., & Jackson, R. (2004). Urban Sprawl and Public Health: Designing, Planning, and Building for Healthy Communities Washington D.C.: Island Press Frank, L., Kerr, J., Chapman, J., & Sallis, J. (2007). Urban Form Relationships with Walk Trip Frequency and Distance Among Youth. American Journal of Health Promotion 21(4Supp), 305-311. Frank, L., Sallis, J., Saelens, B., Bachman, W., & Washbrook, K., (2005). Travel Behavior, Environmental, & Health Impacts of Community Design & Transportation Investment LUTAQH: A Study of Land Use, Transportati on, Air Quality, and Health, King County, Washington Frank, L.D., Engelke, P.O., & Schmid, T.L. (2003). Health and Community Design: The Impact of the Built Environment on Physical Activity Washington D.C.: Island Press. Frank, L.D., Schmid, T.L., Sallis, J.F., Chapman, J ., & Saelens, B.E. (2005). Linking Objectively Measured Physical Activity with Objectively Measured Urban Form: Findings from SMARTRAQ. American Journal of Preventive Medicine 28(2S2), 117-125. Fulton, J.E., Shisler, J.L., Yore, M.M., & Casperse n, C.J. (2003). Active Transportation to School: Findings From a National Survey. Research Quarterly for Exercise and Sport 76(3), 352357. Goldsmith, S.A. (1992). Reasons why bicycling and walking are not being used more extensively as travel models Case Study No. 1, National Bicycling and Walking Study, U.S. Department of Transportation, Federal Highway Administration, Washington D.C. International City/County Management Associati on (2008). ICMA IQ Repor t Special Edition, Item No. E-43527 (40). Retrieved December 6, 2008, from http://icma.org/documents/SGNReport.pdf Kahn, R. (2008). Just E at Less and Move More, Saint Louis Behavioral Medicine Institute, Eating Disorders News 1(3). Retrieved November, 6, 2008, from http://www.slbmi.com/eating_disorde rs/ED%20News/2008/volum e1issue32008.pdf Knack, R.E. (2008). Great Streets: What m akes them special? Planning: The Magazine of the American Planning Association, 74(1), 12-17. Lucy, W.H. (1994). If Planning Includes Too Much, Maybe It Should Include More. Journal of the American Planning Association 60(3), 305-318. Lynch, K. (1960). Image of the City Cambridge, Massachusetts: The MIT Press. 90

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Maryland D epartment of Planning (2008). Managing Maryland's Growth: Smart Growth, Community Planning and Public School Construction, Models and Guidelines 27(2008001). Retrieved: January 12, 2009, from http://www.mdp.state.md.us/pdf/MG27.pdf Ogden, C.L., Carroll, M.D., & Flegal, K.M. (2008). High Body Mass Index for Age Among US Children and Adolescents, 2003-2006. Journal of the Americ an Medical Association 299(20), 2401-2405. Powell, D.L. (1993). Managing Floridas Growth: The Next Generation Florida State University Law Review, 223(2), 223-339. Powell, D.L. (1999). Back to Basics on School Concurrency Florida State University Law Review 451(2), 451-486. Robinson, T.N. (1999). Reducing Children's Televisi on Viewing to Prevent Obesity: A Randomized Controlled Trial. Journal of the American Medical Association 282(16), 1561-1567. Saelens, B.E., Sallis J.F., Black, J.B., & Ch en, D. (2003). Neighborhood Based Differences in Physical Activity: An Environment Scale Evaluation. American Journal of Public Health 93(9), 1552-1558. Schilling, J. & Linton, L.S., (2005). The Public H ealth Roots of Zoning: In Search of Active Livings Genealogy. American Journal of Preventive Medicine 28(2S2), 96-104. Schlossberg, M., Greene, J., Phillips, P.P., Johnson, B., & Parker, B. (2006). School Trips: Effects of Urban Form and Distance on Travel Mode. Journal of the American Planning Association 72(3), 337-346. Serdula, M.K., Ivery, D., Coates, R.J., Freedman, D.S., Williamson D.F., & Byers, T. (1993). Do obese children become obese adul ts? A review of the literature. Journal of Preventive Medicine, 22(2), 167-177. Spengler, J.O., Young, S.J., & Linton, L.S. (2007). Schools as a Community Resource for Physical Activity: Legal Considerations for Decision Makers. American Journal of Health Promotion 21(4Supp), 390-396. Starnes, E., Stein, J., Crider, L., Audirac, I., & Pither, A. (1992). Home-To-School Transportation study: Executive Summary Department of Urban and Regi onal Planning, University of Florida. Steiner, R.L., Bejleri, I., Fischm an, A., Provost, R.E., Arafat, A.A ., Guttenplan, M., & Crider, L.B. (2008). How Policy Drives Mode Choice in Ch ildrens Transportation to School: An Analysis of Four Fl orida School Districts In Publication, Univ ersity of Florida. 91

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92 Steiner, R.L., Bejleri, I., Wheelock, J.L., Boles, G ., Cahill, M., & Perez, B.O. (2008). Understanding and Mapping Institutional Impediments to Wa lking and Bicycling to School: A Case Study of Hillsborough County. Transportation Research Record 2074, 3-11. Steiner, R.L., Crider, L.B., & Betancourt, M. (2006). Safe Ways to School: Th e Role in Multimodal Planning Florida Department of Transportation Systems Pla nning Office. Retrieved February, 6, 2008, from http://www.dot.state.fl.us/researchcenter/Completed_P roj/Su mmary_PL/FDOT_BD545_32_rpt.pdf Strauss R.S., Rodzilsky, D., Burack, G., & Colin, M. (2000). Psychosocial correlates of physical activ ity in healthy children. Archives of Pediatrics and Adolescent Medicine 155(8), 897902. Telama, R., Yang, X., Viikari, J., Valimaki, I., Wa nne, O., & Raitakari, O. (2005). Physical Activity from Childhood to Adulthood: A 21-Year Tracking Study. American Journal of Preventive Medicine, 28(3), 267-273. U.S. Department of Transportation Federal Highway Administration. (2009). Travel Demand Management Retrieved February 16, 2009, from http://ops.fhwa.dot.gov/tdm/index.htm US Census Bureau; 2007 Am erican Community Survey, 1-Year Estimates; generated using American Factfinder; Retrieved March 7, 2008, from http://factfinder.census.gov/servle t/S TTable?_bm=y&-geo_id=04000US12&qr_name=ACS_2007_1YR_G00_S1401&-ds_name =ACS_2007_1YR_G00_&-_lang=en&redoLog=false Wang, G. & Dietz, W.H. (2002). Economic Burden of Obesity in Youths Aged 6 to 17 Years: 19791999. Pediatrics 109(5), 1-6. Wang, Y., & Lobstein, T. (2006). Worldwide trends in childhood overweight and obesity. International Journal of Pediatric Obesity, 1(1), 11. Weight Control Information Network. (2009). National Institute of Di abetes and Digestive and Kidney Diseases (NIDDK). Retrieved: January 21, 2009, from http://win.niddk.nih.gov/st atistics/index.htm #econ

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BIOGR APHICAL SKETCH Jeffrey Matthew Schmucker, the son of Deborah Eckenrode Burns and Bradley William Schmucker, was born December 1978. Jeff received his Masters of Arts degree in urban and regional planning at the Universi ty of Florida in 2009. Before attending graduate school, he attained a Bachelors of Science degree in natu ral resources and conservation also from the University of Florida. In addition to his academic engagements, Jeff has also had the opportunity to gain valuable pr ofessional experiences having work ed for several private sector architectural and design firms, non-profit organizations, and th rough his employment with the University of Florida where hes been able to teac h and develop courses at the graduate level. Jeffs studies have primarily focused on urban and environmental design and issues regarding health and the built environment. Jeffs dedi cation to excellence as he pursues his planning career begins with his belief that by fostering planning and development practices that support healthy, sustainable environments, we can provide livable communities for generations to come. 93