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HEALTHY INDIANAPOLIS

Personal Health and the Built Environment in the Low-Density City

Prepared by: Eric Lucas Prepared for: LA 590, Jody Rosenblatt-Naderi Date of Submission: July 20, 2012


Table of Contents

Acknowledgements�������������������������������������������������� iii

Methodology��������������������������������������������������������������� 13 Conclusions

Preface���������������������������������������������������������������������� v

���������������������������������������������������������� 24

Parks���������������������������������������������������������������������� 24 Walking and Biking��������������������������������������������������� 24

Introduction���������������������������������������������������������������1 Analysis I: Identifying Built Environment Characteristics Associated with Personal Health in the Fifty Largest US Metropolitan Statistical Areas �����������������������3

Transit��������������������������������������������������������������������� 25

Conclusions�������������������������������������������������������������27 References��������������������������������������������������������������29

Methodology ���������������������������������������������������������������� 3 Findings������������������������������������������������������������������������ 3 Conclusions ��������������������������������������������������������������� 6

Analysis II: Identifying Built Environment Characteristics Associated with Personal Health in the Fifty Largest, Low-Density US Metropolitan Statistical Areas�7 Methodology����������������������������������������������������������������� 7 Findings������������������������������������������������������������������������ 7 Conclusions��������������������������������������������������������������� 10

Analysis III: Identifying Smaller MSA Low-Density Cities with Healthy Characteristics������������������������������11 Methodology��������������������������������������������������������������� 11 Findings���������������������������������������������������������������������� 11 Conclusions��������������������������������������������������������������� 11

Analysis IV: Parks, Walking, Biking, and Public Transportation Characteristics of Low-Density Healthy Peer Cities�����������������������������������������������������������������������13 i


List of Figures Figure 1: Personal Health Index (PHI) Rankings Classified by City Density������������������������������������������������������������������������� 4 Figure 2: Relationship of Personal Health Index (PHI) Rankings to Population Density, Parks, and Playgrounds���������������������� 4 Figure 3: Relationship of Personal Health Index (PHI) Rankings to Percent Walking, Biking, or Taking Transit to Work������������� 4 Figure 4: Relationship of Personal Health Index (PHI) to ParkRelated Expenditures����������������������������������������������������������� 5 Figure 5: Relationship of Personal Health Index (PHI) Rankings to Parkland as Percentage of City Area��������������������������������� 5 Figure 6: Relationship of Personal Health Index (PHI) Rankings to Amount of Farmers’ Markets��������������������������������������������� 5 Figure 7: Personal Health Index (PHI) Rankings and Low-Density Cities������������������������������������������������������������������������������� 8 Figure 8: Relationship of Personal Health Index (PHI) Rankings to Parkland as Percentage of City Area in Low-Density Cities� 8 Figure 9: Relationship of Personal Health Index (PHI) Rankings to Park-Related Expenditures of Low-Density Cities��������������� 8 Figure 10: Relationship of Personal Health Index (PHI) Rankings to Amount of Parks and Playgrounds in Low-Density Cities���� 9 Figure 11: Relationship of Personal Health Index (PHI) to Percent Walking, Biking, or Taking Transit to Work in Low-Density Cities���������������������������������������������������������������������������������� 9 Figure 12: Relationship of Personal Health Index (PHI) Rankings to Amount of Farmers’ Markets in Low-Density Cities������������ 9 Figure 13: Population of Healthy Low-Density Cities and Indianapolis������������������������������������������������������������������������������ 14 Figure 14: Parkland as Percentage of City Area in Healthy LowDensity Cities and Indianapolis������������������������������������������� 14 Figures 15: Acres of Parkland by City and Agency������������� 15 Figures 16: Percentage of Park Types in Healthy Low-Density Cities and Indianapolis������������������������������������������������������� 16 Figure 17: Amount of Parks and Playgrounds in Healthy LowDensity Cities and Indianapolis������������������������������������������� 17 Figure 18: Park-Related Expenditures Comparison between Healthy Low-Density Cities and Indianapolis������������������������ 17 Figures 19: Total Spending on Parks and Recreation per Resident, by City and Agency��������������������������������������������������� 18 Figure 20: Percent of Residents Walking, Biking, or Taking Transit to Work in Healthy Low-Density Cities and Indianapolis (Metropolitan Statistical Area Statistics)�������������������������������������� 20 Figure 21: Percent of Residents Walking, Biking, or Taking Transit to Work in Healthy Low-Density Cities and Indianapolis (City Statistics)�������������������������������������������������������������������������� 20 Figure 22: Percent of Residents Walking to Work in Healthy Low-Density Cities and Indianapolis; 2000, 2005, 2010������ 21 ii

Figure 23: Percent of Residents Biking to Work in Healthy LowDensity Cities and Indianapolis; 2000, 2005, 2010������������� 22 Figure 24: Percent Taking Public Transit to Work in Healthy Low-Density Cities and Indianapolis; 2000, 2005, 2010������ 22 Figure 25: Pedestrian and Bicyclist Fatalities in Healthy LowDensity Cities and Indianapolis������������������������������������������� 23 Figure 26: Relationship between Pedestrian/Bicyclist Fatalities and Percent Walking or Biking to Work in Healthy Low-Density Cities and Indianapolis������������������������������������������������������� 24


Acknowledgements

I wish to thank the following individuals for their guidance and input into this work. »» Jody Rosenblatt-Naderi, Chairperson of the Department of Landscape Architecture, Ball State University »» Martha Hunt, Associate Professor of Landscape Architecture, Ball State University I also wish to acknowledge the following data sources, used extensively in this report: »» US Census Bureau »» Centers for Disease Control and Prevention, Behavioral Risk Factor Surveillance System »» American College of Sports Medicine, American Fitness Index »» National Highway Traffic Safety Administration, Fatality Analysis Reporting System »» Trust for Public Land, 2011 City Parks Facts This study is burdened by the following limitations: »» The weighting of personal health indicators used in the American Fitness Index to determine the health of a city is not published. Understanding the relative importance of personal health indicators would aid this study. »» Some detailed park information for Salt Lake City is unavailable. Further avenues will be explored in an attempt to secure this information. iii


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Preface

This paper follows other work to date that has attempted to understand how built environment factors can improve the overall physical health of cities’ residents. In previous efforts, the author has sought to understand the role of urban-based food systems that seek to increase consumption of fruits and vegetables, how street and open space interventions can be used to increase levels of physical activity. Additionally, a spatial analysis of Marion County has indicated high concentrations of residents who are more at-risk for chronic health disparities. The work herein attempts to narrow the scope of study to parks, biking, walking, and public transportation in the context of the low-density city.

Garfield Park, Indianapolis (photo: Eric Lucas)

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Introduction

Across the country, many examples of healthy cities can be

density, Minneapolis for example, may not work in a low-density

seen. “Healthy cities” can be defined in a number of ways;

city such as Indianapolis. In fact, when more closely examining

including economic health, social health, environmental health,

the American Fitness Index rankings for Personal Health Indica-

personal physical health, and so on. Though each category of

tors only, only a handful of low-density cities perform well.

health undoubtedly affects the others, and all are inextricably tied to one another, for the purposes of this report, the term

Upon this discovery, a need to further understand low-den-

“healthy city” is used narrowly to refer to residents’ personal

sity city built environment and personal health characteristics

health. Each year, geographically-diverse cities such as Wash-

emerged. A series of analyses were conducted at multiple lev-

ington DC, Minneapolis, Boston, Portland, Denver, San Fran-

els to identify built environment characteristics closely associat-

cisco and others top various “healthy cities” lists and are viewed

ed with personal health. Analyses were undertaken for all cities,

as models for other cities to emulate. Often, this group of cities

low-density cities, and, finally, for a group of low-density cities

is thought of as pioneers and leaders in emerging trends, and

defined as Healthy Peer Cities. This small group of four cities

much can be learned from the walking, biking, transportation,

(Salt Lake City, Virginia Beach, Colorado Springs, and Durham)

and parks planning and policy initiatives that these cities enact

exhibited high ratings for personal health, despite beting cities

to promote healthier lifestyles for residents.

of low-density. Each analysis yielded a clear list of built environment characteristics closely associated with personal health.

Indianapolis, of course is not known as a “healthy city”. In fact,

However, the most important analysis, that of Healthy Peer Cit-

the collective measure of residents’ personal health continually

ies, also identified exemplary built environment characteristics in

places the city near the bottom of most “healthy city” lists. For

these cities that can serve as a model for Indianapolis.

Indianapolis, this reality does not align with its stated identity as the “Sports Capital of the World”; and as a result, the city is

With this research, a path toward more sound recommenda-

actively pursuing a handful of initiatives that seek to improve the

tions specific to low-density cities has emerged. In future ef-

physical health of residents.

forts, initiatives in Healthy Peer Cities will be further examined for applicability to Indianapolis. Out of this examination, specific

In previous papers, my work has noted the Indianapolis initia-

recommendations for improving Indianapolis residents’ personal

tives and others occurring in pioneer/leader cities. Most of

health will be formulated.

these initiatives are seen in cities such as New York, Boston, Denver, Tampa/St. Petersburg, Minneapolis, and others. Upon further examination of these cities, it became apparent that initiatives and solutions that may work in a city with relatively high 1


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Analysis I: Identifying Built Environment Characteristics Associated with Personal Health in the Fifty Largest US Metropolitan Statistical Areas

The purpose of this analysis is to determine which built environ-

»» Population

ment characteristics are associated with personal health in cit-

»» Population density

ies. In that effot, a quantitative research method of analysis for the fifty largest Metropolitan Statistical Areas (MSAs) was com-

»» Park units

pleted. The basis of the analysis is the 2012 American Fitness

»» Park playgrounds

Index (AFI), which aggregates and tabulates Personal Health

»» Percent walking or biking to work

Indicators (PHI) and Built Environment Characteristics, hereafter

»» Percent taking transit to work

referred to as Community/Environment Indicators (CEI) for the fifty largest MSAs. Based on a ranking system developed by

»» Park related expenditures

the AFI, MSAs are ranked 1-50 for both PHI and CEI perfor-

»» Farmers’ markets

mance. Because the ultimate goal of the Top 10 by 2025 is to

»» Parkland as percent of city area

improve health, the PHI rankings were used in this analysis as a measure of the overall physical health of a city.

Findings Methodology To determine possible association of CEI and PHI, the identified those CEIs associated with healthier cities of all densities. Cities were grouped into five categories, based upon PHI ranking. The top ten cities were grouped in PHI 1-10; the second ten cities were grouped in PHI 11-20, and so forth. For all fifty cities, values were identified for a selected CEI. An average CEI was then calculated for each of the five PHI-rank categories. The average CEI values of all PHI-rank categories were was then compared to determine association. This process was repeated for the other selected CEIs. The individual CEIs used in the analysis are as follows: »» Land area

»» Less land area is associated with healthier cities. »» Higher density is associated with healthier cities. »» More parks are associated with healthier cities (with the exception of PHI Cities 41-50). »» Higher percent walking or biking to work is associated with healthier cities. »» Higher percent taking transit to work is associated with healthier cities. »» Higher park-related expenditures are associated with healthier cities. »» The number of farmers’ markets is not strongly associated with health of cities. »» The top 20 healthiest cities have a higher percentage of parkland to city area. 3


Figure 1: Personal Health Index (PHI) Rankings Classified by City Density Indicates number and density classification of cities, based upon groupings of cities as ranked by PHI.

Number of Cities Ranked 1-10 for PHI

5

Number of Cities Ranked 11-20 for PHI

2 4

Number of Cities Ranked 31-40 for PHI

1

Number of Cities Ranked 41-50 for PHI

1

3 6

Number of Cities Ranked 21-30 for PHI

High Density Cities

2 2

3

2

1

3

3

3

4

Intermediate-High Density Cities

5

Intermediate-Low Density Cities

Low Density Cities

Figure 2: Relationship of Personal Health Index (PHI) Rankings to Population Density, Parks, and Playgrounds Indicates average population density, park units per 10,000 residents, and park playgrounds per 10,000 residents, based upon PHI ranking.

Avg. of All Cities Ranked 1-10 for PHI

4.6

11.4

Avg. of All Cities Ranked 11-20 for PHI

4.4

10.0

Avg. of All Cities Ranked 21-30 for PHI

3.7

8.9

Avg. of All Cities Ranked 31-40 for PHI Avg. of All Cities Ranked 41-50 for PHI

4.8

4.6

Population Density (persons per acre)

Park Units (per 10,000)

2.1

2.2

1.7

3.1

7.4

2.2

2.7 Park Playgrounds (per 10,000)

Figure 3: Relationship of Personal Health Index (PHI) Rankings to Percent Walking, Biking, or Taking Transit to Work Indicates the average percent of residents walking, biking, or taking tranist to work, based upon PHI ranking.

Avg. of All Cities Ranked 1-10 for PHI

6.9%

Avg. of All Cities Ranked 11-20 for PHI

5.7%

Avg. of All Cities Ranked 21-30 for PHI

4.1%

Avg. of All Cities Ranked 31-40 for PHI Avg. of All Cities Ranked 41-50 for PHI

3.1% 1.4%

4

3.3% 2.8%

2.2%

1.8%

% Taking Transit to Work

3.9%

% Walking or Biking to Work


Figure 4: Relationship of Personal Health Index (PHI) to Park-Related Expenditures Indicates average park-related expenditures, based upon groupings of cities as ranked by the PHI.

Avg. of All Cities Ranked 1-10 for PHI

$172.60

Avg. of All Cities Ranked 11-20 for PHI

$110.30

Avg. of All Cities Ranked 21-30 for PHI

$79.00

Avg. of All Cities Ranked 31-40 for PHI

$95.30

Avg. of All Cities Ranked 41-50 for PHI

$76.56 Park-Related Expenditures (per capita)

Figure 5: Relationship of Personal Health Index (PHI) Rankings to Parkland as Percentage of City Area Indicates the average percent of parkland as percentage of city area, based upon PHI ranking.

Avg. of All Cities Ranked 1-10 for PHI

14.5%

Avg. of All Cities Ranked 11-20 for PHI

14.2%

Avg. of All Cities Ranked 21-30 for PHI

8.3%

Avg. of All Cities Ranked 31-40 for PHI

7.6%

Avg. of All Cities Ranked 41-50 for PHI

7.9% % Parkland as City Area

Figure 6: Relationship of Personal Health Index (PHI) Rankings to Amount of Farmers’ Markets Indicates the average number of farmers’ markets per 1,000,000 residents, based upon PHI ranking.

Avg. of All Cities Ranked 1-10 for PHI

19.7

Avg. of All Cities Ranked 11-20 for PHI

13.3

Avg. of All Cities Ranked 21-30 for PHI

15.0

Avg. of All Cities Ranked 31-40 for PHI

10.8

Avg. of All Cities Ranked 41-50 for PHI

15.2 Farmers Markets (per 1,000,000) 5


Conclusions Though this research indicates a number of built environment characteristics are clearly associated with personal health in cities, the near nil representation of low-density cities in the PHI top 20 is cause for further exploration into the characteristics of that category of city density.

6


Analysis II: Identifying Built Environment Characteristics Associated with Personal Health in the Fifty Largest, Low-Density US Metropolitan Statistical Areas Thie purpose of this analysis is to determine which built envi-

were identified for selected CEIs. For each selected CEI, an

ronment characteristics are associated with personal health in

average was calculated for low-density cities in the PHI top 20

low-density cities. In that effort, a quantitative research method

and an average was calculated for all other low density cities.

of analysis for the fifty largest low-density Metropolitan Statisti-

These averages were compared, along with Indianapolis. The

cal Areas (MSAs) was completed. The basis of the analysis is

individual CEIs used in the analysis are as follows:

the 2012 American Fitness Index (AFI), which aggregates and tabulates Personal Health Indicators (PHI) and Built Environment

»» Land area

Characteristics, hereafter referred to as Community/Environ-

»» Population

ment Indicators (CEI) for the fifty largest MSAs. Based on a ranking system developed by the AFI, MSAs are ranked 1-50 for both PHI and CEI performance. Because the ultimate goal of

»» Population density »» Park units

the Top 10 by 2025 is to improve health, the PHI rankings were

»» Park playgrounds

used in this analysis as a measure of the overall physical health

»» Percent walking or biking to work

of a city. The low-density cities (and associated PHI rank) are: Salt Lake City (12), Virginia Beach (19), Nashville (21), Charlotte

»» Percent taking transit to work

(22), Kansas City (30), Indianapolis (37), Orlando (38), Memphis

»» Park related expenditures

(40), Jacksonville (41), Louisville (46), Oklahoma City (48), , and

»» Farmers’ markets

Birmingham (50).

»» Parkland as percent of city area

Following Hurricane Katrina, New Orleans (49) experienced substantial population losses. To prevent skewing of results, New Orleans was omitted from this study.

Findings »» Amount of land area is not strongly associated with healthier cities.

Methodology To determine possible association of CEI and PHI, this analysis measured CEIs for low-density cities ranked in the PHI top 20 (Salt Lake City and Virginia Beach) against all other low-density cities and Indianapolis. For all twelve low-density cities, values

»» Population density within this group is not indicative of a healthier city. »» The following characteristics are associated with healthier cities. On average, the two healthiest low-density cities have the following attributes compared to the averages of the eleven other low-density cities. 7


Figure 7: Personal Health Index (PHI) Rankings and Low-Density Cities Indicates the number of low-density cities as ranked by the PHI.

Number of Cities Ranked 1-10 for PHI Number of Cities Ranked 11-20 for PHI

2

Number of Cities Ranked 21-30 for PHI

3

Number of Cities Ranked 31-40 for PHI

3

Number of Cities Ranked 41-50 for PHI

5 Low Density Cities

Figure 8: Relationship of Personal Health Index (PHI) Rankings to Parkland as Percentage of City Area in Low-Density Cities Indicates the average percent of parkland as percentage of city area in low-density cities, based upon PHI ranking.

Cities in Top 20 for PHI

12.2%

Cities in Bottom 30 for PHI Indianapolis

5.6% 4.8%

% Parkland as City Area

Figure 9: Relationship of Personal Health Index (PHI) Rankings to Park-Related Expenditures of Low-Density Cities Indicates the average park-related expenditures of low-density cities, based upon PHI ranking.

Cities in Top 20 for PHI

$96.00

Cities in Bottom 30 for PHI Indianapolis

$69.10 $43.00

Park-Related Expenditures (per capita) 8


Figure 10: Relationship of Personal Health Index (PHI) Rankings to Amount of Parks and Playgrounds in Low-Density Cities Indicates the average amount of parks per 10,000 residents and playgrounds per 10,000 residents in low density cities, based upon PHI ranking.

Cities in Top 20 for PHI Cities in Bottom 30 for PHI Indianapolis

4.2

5.4 2.1

3.4 2.6

1.6

Park Units (per 10,000)

Park Playgrounds (per 10,000)

Figure 11: Relationship of Personal Health Index (PHI) to Percent Walking, Biking, or Taking Transit to Work in LowDensity Cities Indicates the average percent of residents walking, biking, or taking tranist to work in low-density cities, based upon PHI ranking.

Cities in Top 20 for PHI Cities in Bottom 30 for PHI Indianapolis

2.4%

3.4% 1.6% 1.8%

% Walking or Biking to Work

1.2% 0.9%

% Taking Transit to Work

Figure 12: Relationship of Personal Health Index (PHI) Rankings to Amount of Farmers’ Markets in Low-Density Cities Indicates the average number of farmers’ markets in low-density cities, based upon PHI ranking.

Cities in Top 20 for PHI

16.8

Cities in Bottom 30 for PHI

13.1

Indianapolis

12.6

Farmers Markets (per 1,000,000) 9


»»

96% more walking/biking to work.

»»

75% more taking transit to work.

»»

46% more park units/10,000.

»»

63% more parkland as percent of city area.

»»

93% more park playgrounds.

»»

33% more spent on parks per capita.

»»

34% more farmers’ markets.

»» On average, the two healthiest low-density cities have the following attributes compared to Indianapolis. »»

89% more walking/biking to work; 13,729 more people should be walking/biking to work.

»»

161% more taking transit to work; 11,710 more people should be taking transit to work.

»»

108% more park units/10,000; 226 more park units should be provided.

»»

153% more parkland as percent of city area; 17,004 acres more parkland should be provided.

»»

159% more park playgrounds; 206 more park playgrounds should be provided.

»»

123% more spent on parks per capita; $53 more per capita should be spent.

»»

33% more farmers’ markets; 3-4 more farmers’ markets should be provided.

Conclusions The figures noted above are not to be taken as recommendations for the City of Indianapolis, but are merely provided as a frame of reference. Further analyses will better determine the best approach to in improving built environment characteristics. Because of their high PHI scores and rankings, Salt Lake City and Virginia Beach are categorized as “Healthy Peer Cities”. This designation, which will be used throughout the balance of this paper, indicates cities of low-density that are also statistically healthy cities.

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Analysis III: Identifying Smaller MSA Low-Density Cities with Healthy Characteristics

Because just two low-density cities (Salt Lake City and Virginia Beach) rank in the top 20 PHI, this analysis was conducted to determine if other low-density cities, not in the largest 50 MSAs, exhibited similar healthy characteristics. Since the AFI relies heavily on data from the 2009 and 2010 Centers for Disease Control and Prevention Behavioral Risk Factor Surveillance System (BRFSS) to calculate PHI scores and ranking, a review of the appropriate indicators was conducted to determine if additional low-density cities should be considered in further analyses.

Methodology The following health factors were evaluated for low-density city performance. These indicators were selected to parallel the AFI indicators and were used calculate PHI scores and rankings. »» Asthma – adults who have been told they currently have asthma (BRFSS 2010) »» Fruits and Vegetables – adults who have consumed fruits and vegetables five or more times per day (BRFSS 2009) »» Overweight and Obesity – weigh classification by BMI (BRFSS 2010) »» Health status – how is your general health (BRFSS 2010) »» Exercise – during the past month, did you participate in any physical activities (BRFSS 2010)

week (BRFSS 2009) »» Health Care Access/Coverage – do you have any kind of health care coverage (BRFSS 2010) »» Diabetes – have you ever been told by a doctor that you have diabetes (BRFSS 2010) »» Cardiovascular Disease – ever told you had angina or coronary disease (BRFSS 2010) »» Tobacco Use – adults who are current smokers (BRFSS 2010)

Findings Two additional low-density cities emerged for inclusion in further analyses: Colorado Springs, CO (population 397,317, population density 3.3) and Durham, NC (population 229,171, population density 3.8).

Conclusions If the AFI weighting and scoring were better understood, a PHI rank could be estimated for these two cities. Nevertheless, the health data does indicate that these low density cities are on par with other healthy cities, regardless of density. As such, Colorado Springs and Durham are considered “Healthy Peer Cities” for the purposes of this paper.

»» Physical Activity – adults with 30+ minutes of moderate physical activity five or more days per week or vigorous physical activity for 20+ minutes three or more days per 11


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Analysis IV: Parks, Walking, Biking, and Public Transportation Characteristics of Low-Density Healthy Peer Cities

The purpose of this analysis is to identify Precedent Peer Cit-

Methodology

ies, which herein are defined as cities of low-density with high

Built environment systems were analyzed to determine the best

personal health. The initiatives taking place in these cities will

performing Peer Cities. The built environment systems analyzed

be further studied to understand their success and their broader

included: parks, walking, biking, and transit. The methodology

application in Indianapolis.

for analysis is specific to each system, and is described below.

Indianapolis Downtown Canal (photo: Daniel Schwen, http://en.wikipedia.org/wiki/File:Indy_Central_Canal.jpg)

13


Figure 13: Population of Healthy Low-Density Cities and Indianapolis Indicates the population of healthy low-density cities compared to Indianapolis.

Salt Lake City

186,440

Virginia Beach

666,908

Durham

229,171

Colorado Springs

397,317

Indianapolis

807,584 Population

Liberty Park, Salt Lake City (photo: http://www.slcgov.com)

Figure 14: Parkland as Percentage of City Area in Healthy Low-Density Cities and Indianapolis Indicates the percent of parkland as percentage of city area in healthy low-density cities and Indianapolis.

Salt Lake City

3.1%

Virginia Beach Durham

21.2% 4.1%

Colorado Springs Indianapolis

10.0% 4.8%

% Parkland » Data Purpose: This data is used to determine how much »» Data origin: Trust for Public Land (Trust for Public Land, as City »Area land Healthy Peer Cities devote to parks and open space. 2011)

»» Data definition:

14

»»

This data counts the park area; displayed as a percent of the city area.

»»

Total park area includes any city, county, metro, state, or federal public parkland within the city limits.

»»

Data includes water acreage or riparian waterways, and trails.

»»

Parkland outside the city limits, even if it is owned by the city park agency, is not included.

»» Data Analysis: The inclusion of county, metro, state, and federal parkland accounts for a number of cities that enjoy large amounts of open space owned/operated by these entities. There are vast differences in the acreage of park space in Peer Cities, ranging from just 3.1% in Salt Lake City to 21.2% in Virginia Beach. Indianapolis measures at the low end with 4.8%. This range suggests that in healthy low-density cities, the overall acreage of park space may not be as important as other factors that influence usage, such as number and types of parks, as well as parks location, safety, and accessibility.


Figures 15: Acres of Parkland by City and Agency Indicates the percent of public parkland owned and operated by the City and other independent agencies.

5%

31% 18%

3%

Virginia Beach Department of Parks and Recreation Virginia Department of Conservation and Recreation Back Bay National Wildlife Refuge

29%

Durham Parks and Recreation Department

Princess Anne Wildlife Management Area

43%

Virginia Beach

17%

Durham

2%

Colorado Springs Parks, Recreation and Cultural Services

5%

Eno River State Park (within city of Durham)

71%

Mackay Island National Wildlife Refuge

Indianapolis Department of Parks and Recreation

Colorado Parks and Wildlife (within Colorado Springs)

78%

El Paso County Parks (within Colorado Springs)

98%

Colorado Springs

»» Data origin: Trust for Public Land (Trust for Public Land, 2011) »» Data definition: »»

This data quantifies the amount of park space by contributing City and Agencies; displayed as a percent of total parkland.

»»

Total park area includes any city, county, metro, state, or federal public parkland within the city limits.

»»

Data includes water acreage or riparian waterways, and trails.

»»

Parkland outside the city limits, even if it is owned by the city park agency, is not included.

White River State Park Development Commission

Indianapolis

»»

Data was not available for Salt Lake City.

»» Data Purpose: This data is used to determine the amount of parkland contributed by agencies in Healthy Peer Cities. »» Data Analysis: This data illustrates that Indianapolis Department of Parks and Recreation owns and operates, by a significant margin, more parkland (as a percentage of overall parkland) than parks departments in other Healthy Peer Cities. This indicates that the city may shoulder too much burden in providing for parks space, and that the expertise and focus of other agencies may be able to assist in the ownership or operations of parkland. In some Healthy Peer Cities, municipal parks departments focus more on city-oriented parks, while other agencies focus on larger-scale regional parks. 15


Figures 16: Percentage of Park Types in Healthy Low-Density Cities and Indianapolis Indicates the amount of park types, represented by percentage of overall parks in healthy low-density cities and Indianapolis.

20% 2% 1% 2% 5% 14% 66%

6% 1%

Salt Lake City

7%

1%

20%

Neighborhood and Mini Parks

N

Regional Parks*

Regional Parks*

R

Community Parks**

C

Special Use Parks

S

Golf Courses

Golf Courses

G

Natural Resource Areas

Natural Resource Areas

N

Sports Complexes**** 62%

Sports Complexes**** 59%

S

Monuments-Memorials

Monuments-Memorials

M

Open Space Areas

Open Space Areas

O

Other

Other

O

Community Parks**

30%

Special Use Parks

Virginia Beach

Durham

3% 2% 10% 11% 10% 10% Neighborhood and Mini Parks 2%

1% 23%

6%

Regional Neighborhood and Parks* Mini Parks Parks** Regional Community Parks* Neighborhood and Mini Parks Community Parks**

Regional Parks* Community Parks** 11%

9%

Special Special Use ParksUse Parks Golf Courses Golf Courses

Special Use Parks Golf Courses

2% 1%

Natural Resource Natural Resource Areas Areas Sports Complexes**** Sports Complexes****

6%Natural Resource Areas 65%

4%

10%

48% Sports Complexes****

Monuments-Memorials Monuments-Memorials Open Space Areas Open Space Areas

Monuments-Memorials 9%

3%

48%

3% Open Space Areas

Other

Other

Colorado Springs

3%

Neighborhood and Mini Parks

Other

Indianapolis

* Equivalent to Signature Parks in Virginia Beach. Regional Park-type facilities are owned and operated by other entities in Durham. ** Also includes the Metro Park classification in Virginia Beach. *** Includes Cemeteries for Colorado Springs, Links for Virginia Beach, School Parks for Durham, and Downtown Parks for Durham. **** Includes Athletic Parks designated as Special Use Parks in Durham.

»» Data origins: »»

Colorado Springs: Colorado Springs Parks, Recreation & Trails Master Plan

»»

Durham: Department of Parks and Recreation Master Plan

»»

Indianapolis: 2009-2014 Indianapolis-Marion County Park, Recreation & Open Space Plan

»»

Salt Lake City: Salt Lake City Open Space Acquisition Strategy

»»

Virginia Beach: Virginia Beach Parks and Recreation, 2008

»» Data definition: »» 16

This data counts categorizes park facility types; displayed as a percentage of the overall amount

of parks. »»

Data includes all parks publicly owned and operated by the City Department of Parks and Recreation. Data does not include county, metro, state, and federal parkland.

»» Data Purpose: This data is used to determine the priorities that Healthy Peer Cities place on types of parks. »» Data Analysis: This data unmistakably illustrates that Healthy Peer Cities place an emphasis on providing more Neighborhood Parks and Mini Parks than does Indianapolis. Percent of Neighborhood Parks and Mini Parks to overall number of parks in Healthy Peer Cities averages 63% (ranging from 59% in Durham to 66% in Salt Lake City), compared to just 48% in Indianapolis. This data supports and strengthens the trends seen under “Amount of Park Units and Playgrounds”.


Figure 17: Amount of Parks and Playgrounds in Healthy Low-Density Cities and Indianapolis Indicates the number of parks and playgrounds per 10,000 residents in healthy low-density cities and Indianapolis.

Salt Lake City

3.3

4.4

Virginia Beach Durham

2.5

2.9

Colorado Springs Indianapolis

5.0

6.4 3.6

5.2 1.6

2.6 Park Units (per 10,000)

Park Playgrounds (per 10,000)

»» Data origin: Trust for Public Land (Trust for Public Land, 2011) »» Data definition: »»

This data counts the number of park facilities, regardless of size; displayed per 10,000 residents.

»»

Data includes all publicly owned and operated parks within the municipal boundary of the city, including national, state, county, regional, and municipal parks.

»»

Does not include private golf, tennis, swimming, or other clubs. Does not include parks in gated communities.

»» Data Purpose: This data is used to determine how Healthy Peer Cities balance park acreage with total number of facilities. »» Data Analysis: For the purposes of this study, this data accurately measures public the number of parks in cities. The inclusion of county, metro, state, and federal parkland accounts for a number of cities that enjoy large amounts of open space owned/operated by these entities. This data strengthens the suggestion (as noted in the Parkland as Percentage of City Area analysis) that the number of parks may be a better indicator of healthy cities. All healthy cities have higher ratios of parks per residents than Indianapolis.

Figure 18: Park-Related Expenditures Comparison between Healthy Low-Density Cities and Indianapolis Indicates park-related expenditures of healthy low-density cities and Indianapolis.

Salt Lake City

$45.00

Virginia Beach Durham

$147.00 $47.00

Colorado Springs Indianapolis

$63.00 $43.00 Park-Related Expenditures (per capita)

»» Data origins: Trust for Public Land (Trust for Public Land, 2011) »» Data definition: »»

This data tabulates the total operational and capital spending on parks and recreation; displayed

in dollars per resident. »»

Operational spending costs included: landscape and tree maintenance and all other maintenance tasks, recreational programming, administration, and debt service 17


»»

Capital spending costs included: capital improvements, land acquisition, and funds spent out of the agency’s budget to purchase parkland.

»»

Spending on golf, marina, parking operations, and salaries is included.

»»

Spending on zoos, museums, aquariums, professional sports stadiums, or cemeteries, is not included.

»»

Spending on facilities and programs from outside the city limits is not included, even if the park system extends past the official city boundaries.

»» Data Purpose: This data is used to determine the over-

all amount of investment in public parks by Healthy Peer Cities. »» Data Analysis: Interestingly, this data illustrates that increased spending is not necessarily associated with Healthy Peer Cities. This appears to dispel the common conception that more spending will result in a better parks system. This data suggests that other factors that support park usage, such as park type, park placement, real and perceived park safety, and park accessibility may be critical considerations to address limited funding. This data supports and strengthens the trends seen under “Amount of Park Units and Playgrounds” and “Percentage of Park Types”.

Figures 19: Total Spending on Parks and Recreation per Resident, by City and Agency Indicates the total spending on parks and recreation per resident, by city and agency in healthy low-density cities, Indianapolis, Columbus, and Louisville.

$4,000,000 6%

$1,949,036 3% $15,000 0%

Virginia Beach Department of Parks and Recreation

$34,000 0%

Durham Parks and Recreation Department

Virginia Department of Conservation and Recreation (within Virginia Beach) Back Bay National Wildlife Refuge

$57,606,664 91%

Princess Anne Wildlife Management Area

$10,696,846 100%

Virginia Beach

$1,797,728 7%

$360,000 1%

Eno River State Park (within city of Durham)

Durham

Colorado Springs Parks, Recreation and Cultural Services

$1,490,000 4%

Indianapolis Department of Parks and Recreation

El Paso County Parks (within Colorado Springs)

$23,066,183 92%

Colorado Parks and Wildlife (within Colorado Springs)

Colorado Springs 18

$33,178,752 96%

White River State Park Development Commission

Indianapolis


$5,366,171 12%

Columbus Recreation and Parks Department

Columbus and Franklin County Metro Park District (within Columbus)

$40,330,087 88%

Columbus »» Data origins: Trust for Public Land (Trust for Public Land, 2011) »» Data definition: »»

This data tabulates the operational and capital spending on parks and recreation categorized by contributing entities (city and agencies); displayed in dollars per resident.

»»

Spending includes items noted under “Total Spending on Parks and Recreation”.

»»

Data was not available for Salt Lake City.

»» Data Purpose: This data is used to determine the cost share to the municipal governments of Healthy Peer Cities. Two additional regaional cities (Louisville and Colum-

$6,753,000 21% Louisville Metro Parks

$26,139,385 79%

Waterfront Development Corporation

Louisville bus) are included because of their diversified approach to parks spending. »» Data Analysis: Similar to the “Acres of Parkland by City and Agency” analysis, this data illustrates that Indianapolis Department of Parks and Recreation contributes more to spending (as a percentage of overall spending) than parks departments in most other Healthy Peer Cities, as well as two additional regional cities (Columbus and Louisville). Cities spending less (as a percentage of overall spending) are home to more agencies advocating for and spending on parks than does Indianapolis. In difficult economic times, when city budgets have been slashed, parks departments tend to suffer first. When the city shoulders most of the spending burden, the impact can be significant.

Acacia Park, Colorado Springs (photo: http://sundrenchedmoments.blogspot.com)

19


Figure 20: Percent of Residents Walking, Biking, or Taking Transit to Work in Healthy Low-Density Cities and Indianapolis (Metropolitan Statistical Area Statistics) Indicates the percent walking, biking, or taking transit to work in healthy low-density cities MSAs and the Indianapolis MSA.

Salt Lake City

2.9%

3.0%

Virginia Beach

1.8%

3.8%

Durham

4.0%

4.7%

Colorado Springs

5.3%

Indianapolis

1.8%

0.9%

0.9%

% Walking or Biking to Work

»» Data origin: US Census, 2010 American Community Survey 1-Year Estimates (US Census Bureau) »» Data definition: »»

This 2010 data estimates the percent of workers walking, biking, or taking public transportation to work.

»»

Data is for the Metropolitan Statistical Area.

% Taking Transit to Work

»» Data Purpose: This data is the basis of comparison in the American Fitness Index, and is thus used to establish the walking, biking, and public transportation habits within the MSA of Healthy Peer Cities. »» Data Analysis: Not surprisingly, all Healthy Peer Cities have substantially higher percentages of residents walking, biking, or taking public transportation to work.

Figure 21: Percent of Residents Walking, Biking, or Taking Transit to Work in Healthy Low-Density Cities and Indianapolis (City Statistics) Indicates the percent walking, biking, or taking transit to work in healthy low-density cities and Indianapolis.

Salt Lake City Virginia Beach

8.5% 2.1% 0.8%

Durham

4.7%

Colorado Springs Indianapolis

3.3%

3.7% 0.8% 2.4%

1.8%

City % Walking or Biking to Work

»» Data origin: US Census, 2010 American Community Survey 1-Year Estimates (US Census Bureau) »» Data definition: »»

This 2010 data estimates the percent walking, biking, or taking public transportation to work.

»»

Data is for the City.

»» Data Purpose: To better understand alternative and active transportation habits in the the low-density city, it is necessary to review data specific to cities. This data is 20

5.5%

City % Taking Transit to Work

used to establish the walking, biking, and public transportation habits within the city limits of Healthy Peer Cities. »» Data Analysis: The percent walking, biking, or taking public transportation to work is quite different between the MSA and the city. With the exception of Virginia Beach, Healthy Peer Cities still have a higher total percentage of residents walking, biking, or taking public transportation to work than does Indianapolis. The percentages in Salt Lake City and Durham are exemplary; suggesting that much could be learned from studying the initiatives that have produced positive results in these cities.


Downtown Durham (http://www.flickr.com/photos/reallyboring)

Figure 22: Percent of Residents Walking to Work in Healthy Low-Density Cities and Indianapolis; 2000, 2005, 2010 Indicates the percent of residents walking to work in years 2000, 2005, and 2010 in healthy low-density cities and Indianapolis.

5.8% Salt Lake City 161% Increase from 2005 to 2010

4.9%

Durham 210% Increase from 2005 to 2010 4.2%

3.6% 3.1%

3.1% 2.5% 2.5% 2.0%

Salt Lake City

1.6%

2.0% 1.9% 1.9%

2.0% 1.3%

Virginia Beach

Durham 2000

»» Data origin: US Census, 2010 American Community Survey 1-Year Estimates (US Census Bureau), 2005 American Community Survey (US Census Bureau), 2000 US Census Summary File 3 (US Census Bureau). »» Data definition: »»

This 2000, 2005, and 2010 data estimates the percent of workers walking to work.

»»

Data is for the City.

»» Data Purpose: To better understand if and how lowdensity city walking to work habits have changed over

2005

Colorado Springs

Indianapolis

2010

time. This data is used to establish Precedents Healthy Peer Cities. »» Data Analysis: Interestingly, all cities saw declines in the percent of residents walking to work between 2000 and 2005. Conversely, all cities, except Virginia Beach and Indianapolis saw an increased percent of residents walking to work between 2005 and 2010. Again, Salt Lake City and Durham exhibit exemplary performance during the 2005-2010 rebound; suggesting that much could be learned from studying the initiatives that have produced positive results in these cities. 21


Figure 23: Percent of Residents Biking to Work in Healthy Low-Density Cities and Indianapolis; 2000, 2005, 2010 Indicates the percent of residents biking to work in years 2000, 2005, and 2010 in healthy low-density cities and Indianapolis.

2.7% Salt Lake City 169% Increase from 2005 to 2010

1.5%

1.6%

Indianapolis 500% Increase from 2005 to 2010 0.5%

0.8% 0.6% 0.3% Salt Lake City

0.4% 0.4% 0.5%

Virginia Beach

Durham 2000

2005

»» Data origin: US Census, 2010 American Community Survey 1-Year Estimates (US Census Bureau), 2005 American Community Survey (US Census Bureau), 2000 US Census Summary File 3 (US Census Bureau).

This 2000, 2005, and 2010 data estimates the percent of workers biking to work.

»»

Data is for the City.

Colorado Springs

0.2%

0.1%

Indianapolis

2010

work habits have changed over time. This data is used to establish Precedents Healthy Peer Cities. »» Data Analysis: Biking to work habits in all cities except Indianapolis have steadily increased from 2000-2010, though Indianapolis has increased the percent biking to work by five-times from 2005-2010. Again, Salt Lake City stands apart from the other cities, with 2.7% percent of residents biking to work. Much could be learned from studying the initiatives that have produced steadily positive results in Salt Lake City.

»» Data definition: »»

0.5% 0.6% 0.6%

»» Data Purpose: To better understand if and how biking to

Figure 24: Percent Taking Public Transit to Work in Healthy Low-Density Cities and Indianapolis; 2000, 2005, 2010 Indicates the percent of residents taking public transit to work in years 2000, 2005, and 2010 in healthy low-density cities and Indianapolis. 7.0% 6.2% 5.5%

Durham 165% Increase from 2005 to 2010 Virginia Beach 160% Increase from 2005 to 2010 0.7% 0.5% 0.8%

Salt Lake City

3.3%

2.5%

2.3%

2.0% 1.1%

Virginia Beach

Durham 2000

22

3.3%

2005

0.8%

Colorado Springs 2010

1.9% 1.8%

Indianapolis


»» Data origin: US Census, 2010 American Community Survey 1-Year Estimates (US Census Bureau), 2005 American Community Survey (US Census Bureau), 2000 US Census Summary File 3 (US Census Bureau). »» Data definition: »»

This 2000, 2005, and 2010 data estimates the percent taking public transportation to work.

»»

Data is for the City.

»» Data Purpose: To better understand if and how lowdensity city public transportation to work habits have

changed over time. This data is used to establish Precedents Healthy Peer Cities. »» Data Analysis: Taking public transportation to work habits from 2000-2010 are mixed. While Salt Lake City has the highest ridership at 5.5%, it has also seen a 22% decline in ridership between 2005 and 2010. Durham and Virginia Beach have each experienced a significant increase in ridership from 2005 and 2010. The initiatives implemented in these cities, along with Salt Lake City, should be studied for their ability to produce a high degree of ridership and/or a dramatic increase in ridership.

1700 South, Salt Lake City (photo: http://www.saltcycle.org)

Figure 25: Pedestrian and Bicyclist Fatalities in Healthy Low-Density Cities and Indianapolis Indicates the number of pedestrian and bicyclist fatalities, per 100,000 population in healthy low-density cities and Indianapolis.

Salt Lake City

1.3

Virginia Beach

1.1

Durham

1.5

Colorado Springs

0.4

Indianapolis

1.6 Pedestian and Bicyclist Fatalities per 100,000 Population, 2006-2010 Average

»» Data origin: Fatality Analysis Reporting System (National Highway Traffic Safety Administration). »» Data definition: »»

The figures displayed are average pedestrian and bicyclist fatalities from 2006-2010 for each city; displayed in number per 100,000 population.

»»

Data is for the City.

»» Data Purpose: To better understand the safety of biking

and walking in low-density cities. This data is used to establish Precedents Healthy Peer Cities and to compare against the percentage of residents walking and biking to work. »» Data Analysis: Most cities are clustered from 1.1 to 1.6 fatalities per 100,000 population. Indianapolis is at the bottom of the list at 1.6, while Colorado Springs stands out from the others at a 0.4 rate. The safety initiatives implemented in Colorado Springs should be studied. 23


Figure 26: Relationship between Pedestrian/Bicyclist Fatalities and Percent Walking or Biking to Work in Healthy LowDensity Cities and Indianapolis Indicates the relationship of pedestrian/bicyclist fatalities and percent of residents walking or biking to work in healthy low-density cities and Indianapolis. 1.6

Indianapolis

2.4% 1.1

Virginia Beach Colorado Springs Durham Salt Lake City

3.1% 0.4 3.7% 1.5 4.7% 1.3 8.5%

Pedestian and Bicyclist Fatalities per 100,000 Population, 2006-2010 Average

»» Data origin: Fatality Analysis Reporting System (National Highway Traffic Safety Administration) and 2010 American Community Survey 1-Year Estimates (US Census Bureau).

plementing initiatives that promote successful parks systems

»» Data definition:

those elements may be applied to other low-density cities, such

»»

Fatalities figures displayed are average pedestrian and bicyclist fatalities from 2006-2010 for each city; displayed in number per 100,000 population.

»»

Percent walking or biking to work is 2010 estimates.

»»

Walking and biking to work data is for the City. Fatalities data is for the County.

»» Data Purpose: To better the how more walking and biking to work relates to the safety of biking and walking in low-density cities. This data is used to establish Precedents Healthy Peer Cities. »» Data Analysis: This data clearly illustrates that increased biking and walking activity is associated with fewer fatalities. Salt Lake City and Colorado Springs exhibit exemplary performance; suggesting that much could be learned from studying the initiatives that have produced positive results in these cities.

Conclusions The preceding data indicates that Healthy Peer Cities are im24

% Walking/Biking to Work

and increased walking, biking, and transit use.

These initia-

tives should be examined to understand the design and policy recommendations that are resulting in positive trends and how as Indianapolis. The following cities exhibit exemplary performance in the following categories, and as such should be considered Precedent Peer Cities.

Parks Salt Lake City and Colorado Springs are able to focus on Neighborhood Parks as a core component of their overall parks system; which is important in overall health of cities. This focus may be made possible by other agencies actively advocating for and owning and operating parks within the city. Additional agency participation is extremely high in Colorado Springs. Spending on parks in these cities is relatively low. Salt Lake City spends approximately the same on parks as Indianapolis. This low spending may indicate poor parks condition or efficiently operated departments and agencies.

Walking and Biking Within the city, Salt Lake City and Durham enjoy high rates of residents walking and biking to work, and have both seen dramatic increases in such activity since 2005. Moreover, along


with Colorado Springs, Salt Lake City and Durham see low rates of pedestrian fatalities, despite higher rates of walking and biking.

Transit Within the city, Salt Lake City and Durham enjoy high rates of residents taking public transportation to work. Durham has seen a dramatic increase in such activity since 2005. Though Salt Lake City has seen a decline in ridership since 2005, ridership levels are still significantly higher than other Peer Cities.

25


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26


Conclusions

This research has clearly indicated that “healthy” low-density cit-

and snowy winters, yet still enjoy a high percentage of active

ies depend on a successful and integrated network of parks,

transportation.

biking and walking facilities, and public transportation. This integrated network should be considered the basis of planning and

Though not an integral component of my work going forward,

design principals. These findings support other scholarship that

the public transportation systems in Salt Lake City and Durham

has previously concluded that parks, biking, walking, and pub-

are worthy of further research to understand their recipe for suc-

lic transportation are important to health. Previous scholarship

cess; particularly as Indianapolis seeks to implement its regional

specific to low-density cities has not been identified.

transit initiative, IndyConnect.

If the city of Indianapolis is serious about improving the health

The next steps for my work include research into Precedent

of residents, significant investment is necessary to foster an im-

Peer Cities. This work, along with previous research into indus-

proved built environment infrastructure that promotes walking,

try best practices and emerging practices, will round out strate-

biking, parks, and public transportation. Through the research

gies that promote increased physical activity. From these strat-

contained in this paper, those built environment components

egies, existing conditions can be more accurately analyzed and

have been studied in the context of the low-density city and a

future planning and design solutions developed. It is thought

clear path to further examination of precedents has been identi-

that this work will be demonstrated in one or more Indianapolis

fied.

neighborhoods.

Future research should seek a better understanding of the parks systems in Salt Lake City and Colorado Springs. Spending, ownership, and operations by independent agencies appears to be a lacking element of the Indianapolis system. Additionally, the focus of “healthy cities” on more parks in neighborhoods is not seen in Indianapolis. Salt Lake City, Durham, and to a degree in Colorado Springs, have employed successful initiatives to promote walking and biking, and have done so in a way that promotes safety. This is an exciting avenue to further explore in context to climate, as Salt Lake City and Colorado Springs both experience cold 27


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28


References

American College of Sports Medicine. (2011). ACSM American Fitness Index. ACSM American Fitness Index. Colorado Springs Parks, Recreation & Cultural Services. (n.d.). Parks, Trails & Open Space. Retrieved July 14, 2012, from Parks, Recreation & Cultural Services: http://www.springsgov.com/Page.aspx?NavID=1214 Durham Department of Parks and Recreation. (2003). Durham Department of Parks and Recreation Master Plan. Durham: Durham Department of Parks and Recreation. Indy Parks and Recreation. (2009). 2009-2014 Indianapolis-Marion County Park, Recreation & Open Space Plan. Indianapolis: Indy Parks and Recreation. National Highway Traffic Safety Administration. (n.d.). 2010 Traffic Fatalities by State. Retrieved July 17, 2012, from Fatality Analysis Reporting System: http://www-fars.nhtsa.dot.gov/States/StatesCrashesAndAllVictims.aspx Salt Lake City Open Space Lands Program. (2010). Salt Lake City Open Space Acquisition Strategy - Draft. Salt Lake City: Salt Lake City Open Space Lands Program. Trust for Public Land. (2011). City Park Facts. Retrieved from Trust for Public Land: http://cityparksurvey.tpl.org/reports/index.asp US Census Bureau. (n.d.). 2010 American Community Survey 1-Year Estimates. Retrieved July 17, 2012, from American Factfinder: http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?fpt=table US Census Bureau. (n.d.). Commuting Characteristics by Sex. Retrieved July 17, 2012, from 2005 American Community Survey: http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?pid=ACS_05_EST_S0801&prodType=table US Census Bureau. (n.d.). Journey to Work: 2000. Retrieved July 17, 2012, from Census 2000 Summary File 3 (SF 3) - Sample Data: http://factfinder2.census.gov/faces/tableservices/jsf/pages/productview.xhtml?fpt=table Virginia Beach Parks and Recreation. (2008, November 18). Inventory of Sites Summary. Virginia Beach Outdoors Plan. Virginia Beach, VA.

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