measuring walkability in gainesville’s urban areas:...
TRANSCRIPT
MEASURING WALKABILITY IN GAINESVILLE’S URBAN AREAS: A CASE STUDY OF MILLHOPPER AND DOWNTOWN
By
ALLISON REAGAN
A THESIS PRESENTED 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
UNIVERSITY OF FLORIDA
2018
© 2018 Allison Reagan
To my supportive family and friends
4
ACKNOWLEDGMENTS
I would like to thank my chair, Dr. Ilir Bejleri who helped guide me with my
research and classes through both my undergraduate and graduate years. Dr. Bejleri
was always willing to answer all of my questions and encourage me to build on my own
ideas. I would also like to thank my co-chair Dr. Ruth Steiner for valuable input on all
things walkability and getting me through the IRB process.
I would also like to thank my graduate advisor Stanley Latimer who has helped
me in all my times of crisis. Stanley’s office door is always open and he always makes
time to listen to every student who enters his office. Without his help, I would not have
been able to graduate.
Last but not least, I would like to thank my close friends and family for the
continuous support all throughout my academic career. Thanks to you my sanity has
been kept in check.
5
TABLE OF CONTENTS page
ACKNOWLEDGMENTS .................................................................................................. 4
LIST OF TABLES ............................................................................................................ 8
LIST OF FIGURES .......................................................................................................... 9
LIST OF ABBREVIATIONS ........................................................................................... 10
ABSTRACT ................................................................................................................... 11
CHAPTER
1 INTRODUCTION .................................................................................................... 13
2 LITERATURE REVIEW .......................................................................................... 16
Background ............................................................................................................. 16 The Walkability Concept ......................................................................................... 17
Why is it Important? .......................................................................................... 17 The problem ............................................................................................... 17
Positive impacts ......................................................................................... 18 Defining Walkability .......................................................................................... 20
Measuring Walkability ............................................................................................. 23 Factors that Influence Walkability ..................................................................... 23 How to Measure Walkability ............................................................................. 24
Indicators ................................................................................................... 26 Density and land use mix ........................................................................... 26
Street network connectivity ........................................................................ 27 User perception and the importance of indicators ...................................... 28
Past research methodologies ..................................................................... 29
3 METHODOLOGY ................................................................................................... 36
Conceptual Framework and Study Design .............................................................. 36 Study Areas ............................................................................................................ 36
Scale ................................................................................................................ 36 Site Overviews ................................................................................................. 37 Morphology Comparisons ................................................................................. 38 Zoning .............................................................................................................. 40 Block Groups .................................................................................................... 41
Data Collection – Walkability Indicators .................................................................. 41 Independent and Dependent Variables ............................................................ 42
Choice of Indicators .......................................................................................... 42 Calculating the Final Walkability Index ............................................................. 42
6
Net residential density ................................................................................ 43 Building density (mass v. void) ................................................................... 43
Sidewalk coverage ..................................................................................... 44 Intersection density .................................................................................... 44 Entropy index ............................................................................................. 44 Destinations ............................................................................................... 46 Access to transit. ........................................................................................ 48
Survey ..................................................................................................................... 49 Purpose ............................................................................................................ 49 Audience and Approach ................................................................................... 49
4 RESULTS ............................................................................................................... 62
Walkability Index ..................................................................................................... 62 Residential Density ........................................................................................... 62
Building Density ................................................................................................ 63 Sidewalk Coverage .......................................................................................... 63 Intersection Density .......................................................................................... 64
Entropy Index (Land Use Mix) .......................................................................... 64 Access to Transit .............................................................................................. 65
Destinations ...................................................................................................... 66
Final Index ........................................................................................................ 66
Survey ..................................................................................................................... 68 Who is Walking? ............................................................................................... 68
Where are They Walking? ................................................................................ 69 Why are They Walking? ................................................................................... 69 How Did They Get There? ................................................................................ 72
5 DISCUSSION ......................................................................................................... 75
The Index ................................................................................................................ 75
The Survey ............................................................................................................. 77
Limitations ............................................................................................................... 79 Walkability Index .............................................................................................. 79
Survey .............................................................................................................. 80 Recommendations .................................................................................................. 80
Index ................................................................................................................ 80
Survey .............................................................................................................. 80 Future Research ..................................................................................................... 81
6 CONCLUSION ........................................................................................................ 82
APPENDIX
A MORPHOLOGY FEATURES: STREET, BLOCK, AND FIGURE GROUND ........... 84
Street Network ........................................................................................................ 84 Blocks ..................................................................................................................... 85
7
Block Dimensions ................................................................................................... 86 Figure-Ground ........................................................................................................ 88
Block/Figure Ground Overlay .................................................................................. 89
B WALKABILITY INDEX MAPS ................................................................................. 90
General Site Locations............................................................................................ 90 Zoning Maps ........................................................................................................... 91 Modified Block Groups ............................................................................................ 93
Destinations Result ................................................................................................. 94
C SURVEY DOCUMENTS ......................................................................................... 95
Informed Consent Form .......................................................................................... 95 Intercept Survey ...................................................................................................... 96 Recruitment Script .................................................................................................. 97 Survey Results ........................................................................................................ 98
Downtown ......................................................................................................... 99 Millhopper ....................................................................................................... 130
LIST OF REFERENCES ............................................................................................. 160
BIOGRAPHICAL SKETCH .......................................................................................... 163
8
LIST OF TABLES
Table page 2-1 Definitions of walkability ..................................................................................... 34
2-2 Example Urban Design Quality Definition ........................................................... 34
3-1 List of example indicators ................................................................................... 51
3-2 Net residential density measures ........................................................................ 53
3-3 Building density measures .................................................................................. 53
3-4 Sidewalk availability measures ........................................................................... 53
3-5 Intersection density measures ............................................................................ 53
3-6 Entropy index measures ..................................................................................... 53
3-7 Destination weights ............................................................................................ 54
3-8 Destination measures ......................................................................................... 54
3-9 Access to transit measures ................................................................................ 54
4-1 Walkability index results ..................................................................................... 73
9
LIST OF FIGURES
Figure page 2-1 Ewing & Handy – Perceptions and Walkability ................................................... 35
3-1 Conceptual Framework ...................................................................................... 55
3-2 Downtown site map ............................................................................................ 56
3-3 Millhopper site boundary .................................................................................... 57
3-4 Example walkability indices ................................................................................ 58
3-5 Building density .................................................................................................. 59
3-6 Sidewalk availability ............................................................................................ 59
3-7 Intersection density ............................................................................................. 60
3-9 Destinations ........................................................................................................ 61
4-1 Walkability index results map ............................................................................. 74
A-1 Downtown street network and Millhopper street network ................................... 84
A-2 Downtown blocks and Millhopper blocks ............................................................ 85
A-3 Downtown block dimensions .............................................................................. 86
A-4 Millhopper block dimensions............................................................................... 87
A-5 Downtown and Millhopper figure grounds .......................................................... 88
B-1 General site locations ......................................................................................... 90
B-2 Downtown zoning map ....................................................................................... 91
B-3 Millhopper zoning map ....................................................................................... 92
B-4 Modified block groups ......................................................................................... 93
B-5 Destinations heat map ........................................................................................ 94
C-1 Informed consent form ........................................................................................ 95
C-2 Intercept survey form .......................................................................................... 96
C-3 Recruitment script ............................................................................................... 97
10
LIST OF ABBREVIATIONS
ACPA Alachua County Property Appraiser
APHA American Public Health Association
FDOR Florida Department of Revenue
FGDL Florida Geographic Data Library
GIS Geographic Information System
RTS Regional Transportation System
11
Abstract of Thesis Presented 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
MEASURING WALKABILITY IN GAINESVILLE’S URBAN AREAS: A CASE STUDY OF MILLHOPPER AND DOWNTOWN
By
Allison Reagan
May 2018
Chair: Ilir Bejleri Cochair: Ruth Steiner Major: Urban and Regional Planning
The popularity of the personal automobile has caused a general decrease in
physical activity and a movement away from the human scale in our urban
environments. This research explores the relationship between the physical
characteristics of the built environment and the walkability of two urban areas in
Gainesville, Florida. The research uses a multi-method approach using a GIS-based
walkability index and an intercept survey of walkers to validate the quantitative results.
The Downtown study area was found to be the most walkable of the two locations with
no single variable contributing the most to the final index score due to the
multicollinearity among the indicators. Overall, the street network played a vital role in
influencing how people and different land uses interact with one another. The street
network is a common factor among all indicators in how it is designed, the patterns in
which it travels, and how oriented they are towards creating accessible, pedestrian
friendly environments. Lastly, there were some major differences in the demographic
makeup of the two survey populations, however, all respondents shared a desire for
12
more functional destinations within a closer proximity and infrastructure based
improvements such as sidewalks, streetlights, and shading.
13
CHAPTER 1 INTRODUCTION
In the last few decades, America has begun to experience the negative
consequences of a built environment that no longer caters to the pedestrian, where a
growing dominance of the automobile has guided development and growth of its cities.
The transition into an auto-oriented society coincided with the birth of the American
Dream in the Post-World War II era, where the suburban lifestyle became the common
way of life for the majority of the population. Negative consequences of auto-oriented
society include air pollution, overconsumption of fossil fuels, and social and class
segregation. However, perhaps the most important negative consequence in relation to
this research is the movement away from the human-scale and its effects on public
health. Lack of physical activity, no longer supported by the urban street, has been
attributed to the obesity epidemic and this discovery opened the gates to exploring the
relationship between the built environment and physical activity, and later, walkability.
Leaders in the fields of public health, transportation, and planning have been
tasked with discovering how to transform over-scaled communities into healthy, safe,
and vibrant places for the pedestrian. The planning field’s reaction to this problem is
seen in the philosophies of new urbanism, transit oriented development (TOD), smart
growth, and traditional town planning. These philosophies share many commonalities in
the solutions they propose centering around trip degeneration and an increased reliance
on non-motorized transport (i.e. walking and biking); notable solutions include diverse
mix of land uses, mixed-use retail /residential complexes, larger sidewalks, smaller
blocks, and narrower streets. In the search for walkability, walkable communities are
often identified as reminiscent images of past ‘traditional cities’ or those of old Western
14
Europe where many are revered for their rich character and street life (i.e. presence of
people interacting in the at the street level). Some may argue these images are
unrealistic, but the need for the revival of a vibrant street life is valid.
There is undisputedly a dramatic lack of pedestrian-friendly environments in
urban America, however, there is no clear consensus on a solution. There is a general
belief among those in planning related fields that compact development and
accessibility increase quality of life (Leslie, et al., 2007) and experts have begun to
explore methods in which to measure the concept of walkability. These efforts have
helped identify some strong correlations between the built environment and pedestrian
behavior and perceptions. Nonetheless, current practice attempting to create healthier
communities is still dominated by assumptions, rather than a unified base of scientific
evidence. At least in the United States, there is no universal walkability index or
standard that is used by all municipalities and practitioners.
The following research attempts to answer the question “how do the physical
characteristics of the built environment affect the potential walkability of an area?” in
reference to Gainesville, Florida. The primary objective of this research is to attempt to
objectively measure features of the built environment, adapted to the current conditions
of Gainesville, and assess their relationship with the potential walkability of a space or
area. This research attempts to develop a generic index to potentially be referenced by
others in the urban planning field. An additional survey component is included to
validate the objective measurements by actual users of the built environment. This
index, or one similar, could be used by others in the planning field, particularly those at
the municipal level, as a guide to rediscovering their existing built environment and
15
guiding future development where it is needed most for the betterment of the
communities.
16
CHAPTER 2 LITERATURE REVIEW
Background
Long curving roads of Cape Cod homes lying neatly on clean-cut grass plots and
a family station wagon sitting in the driveway iconized the suburbs of post-World War II
America. With the return of the veterans came a dramatic rise in weddings and birth
rates and a booming industrial economy. This set the stage for the success of the
suburban single-family owned home representing the ‘American Dream.’ With the
growing popularity of both residential and racial segregation through single-use zoning,
the suburbs continued to expand farther and farther out with each new influx of
residents (Wolf, 2008). Urban centers were either drained of resources or demolished
as highways carved into the landscape the new lifestyle of middle-class America. As
suburbs continued to sprawl, street design moved farther from the small, grid-style
streets of the urban city center to the vast, open winding roads of the suburbs, where
buildings and people alike were segregated by use and affluence and “the automobile
became a perquisite to social and economic viability” for the average American
(Browner, 2013, p. 2). Since then, our ever-increasing “reliance on cars has been
codified into the legislative fabric of our cities in transportation and design standards of
our streets” (Forsyth & Southworth, 2008, p. 1).
While Jane Jacobs, author of The Death and Life of Great American Cities,
advocates for many of the solutions proposed in the walkability literature, she does not
believe automobiles are the sole cause for the loss of pedestrian and community space.
While it may certainly be a major factor to consider, she claims the issue lies within the
outdated teachings of urban planning and design itself, dating back to Ebenezer
17
Howard and Le Corbusier. Instead of eliminating or decreasing automobile traffic as a
solution to poorly designed streets and spaces, planning professionals should focus on
finding a way to create streets and spaces where both pedestrians and vehicles thrive in
harmony (Jacobs, 1961).
The creation of diverse walkable cities and communities is a global concept
certainly not limited to one nation and the results of this research should not be limited
in its applicability, however, this research recognizes a strong need for reform and
redevelopment in American urban infrastructure. For this research, walkability will be
defined as the extent to which the built environment supports pedestrian activity by
providing diverse and safe access to quality destinations.
The Walkability Concept
Why is it Important?
Walking is the first thing an infant wants to do and the last thing an old person wants to give up. Walking is the exercise that does not need a gym. It is the prescription without medicine, the weight control without diet, and the cosmetic that can’t be found in a chemist. It is the tranquilizer without a pill, the therapy without a psychoanalyst, and the holiday that does not cost a penny. What’s more, it does not pollute, consumes few natural resources and is highly efficient. Walking is convenient, it needs no special equipment, is self-regulating and inherently safe. Walking is as natural as breathing. (John Butcher, Founder Walk21, 1999)
The problem
Post-World War II, America has experienced a decline in overall physical activity
and an increase in health problems such as heart disease and obesity. According to the
American Public Health Association (APHA), childhood obesity has tripled in the last
thirty years and in 2010 APHA predicted that by 2015, seventy-five percent of adults will
be overweight. Negative health impacts from poor transportation policy can be seen the
most in lower-income and minority communities, whom have the highest use of public
18
transit, but a lower quality pedestrian infrastructure. These negative health impacts
place a strain on quality of life as well as the local and national economy through hidden
health costs (APHA, 2014).
Current deficiencies in pedestrian infrastructure also create a safety concern for
many individuals who rely on walking for transportation. A study in Seattle on pedestrian
traffic fatalities found the absence of sidewalks and crosswalks along busy streets
between major destinations to be the largest contributors to pedestrian fatalities
(Harrufff, Avery, & Alter-Pandya, 1998). Having long distances between signalized
crosswalks or intermittent breakage between stretches of sidewalks encourages
pedestrians to walk on the road or jaywalk as a faster and more convenient option.
Examples of this phenomenon can be seen in many American cities, including
Gainesville, Florida.
Positive impacts
Active transportation – walking or biking for transportation needs – can promote
the development of healthier populations. For instance, “women who walk or bike 30
minutes a day have a lower risk of breast cancer” (APHA, 2010, p. 1). Active
transportation has also shown to be as effective as structured workouts in improving
health both physically and mentally (APHA, 2010). A study conducted in Metro
Vancouver found residents living in the most walkable areas were half as likely to be
overweight compared those in the less walkable neighborhoods (Frank, Delvin,
Johnstone, & Loon, 2010). However, walkable pedestrian spaces can provide numerous
benefits far beyond health. One of the most popular statements cited in walkability
literature is Ann Forsyth & Michael Southworth’s claim that “walkability is the foundation
for the sustainable city” (2008, p. 1). High quality, walkable neighborhoods have
19
become reserved for the affluent, valued for their aesthetic and recreational appeal
rather than functional use (Bradshaw, 1993). Further research has revealed gross
inequalities in the walking environments of minority and low-income communities, in
comparison to their wealthier counterparts, even though those of low-income are far
more likely to rely on public transportation (APHA, 2015). Excluding personal
handicaps, walking is the most equitable form of transportation, not limited by race, age,
ethnicity, or income (Lo, 2009; Talen, 2002). Further increasing the use of public
transportation and non-motorized transportation such as walking can reduce personal
vehicular emissions, reduce car ownership and maintenance costs, as well as reduce
the external cost of roadway and parking maintenance for the city or local government.
An estimated 25 cents per vehicle-mile-reduced is saved when replacing short-vehicle
trips with walking (Litman, 2017). In addition, traveling by foot promotes social
interaction and community engagement. In Bradshaw’s walkability index his survey
measures the “chances of meeting someone you know while walking” (Bradshaw,
1993). Lastly, and perhaps the most obvious benefit of walking is that, being fueled by
human power, it produces no greenhouse gases.
“With the advent of public health research and incentives, better planning and
design of the pedestrian environment has finally gained traction in planning policy
[today]” (Reagan, 2017, p. 10). At the turn of the century, researchers began to explore
solutions to return urban development to the smaller, healthier, walkable streets of the
traditional city. The two primary approaches to moving away from personal vehicles can
be simplified as a) developing a strong public transportation network or b) increasing
20
soft forms of transportation–i.e. physical activity such biking and walking. The following
research will be exploring the latter.
Defining Walkability
In this paper, the built environment will be interpreted as follows: “physical
features of the urban landscape (i.e. alterations to the natural landscape) that
collectively define the public realm, which might be as modest as a sidewalk or an in-
neighborhood retail shop or as large as a new town” (Cervero & Kockelman, 1997, p.
200).
Due to the recent nature of the concept, walkability remains relatively ambivalent
in an established definition. Instead the term is interpreted uniquely by each field of
practice involved in its investigation. Overall, the walkability discourse can be
categorized into two broad directions of perspectives: a means of transportation or a
social construct. In the first, walking is a mode of transport equivalent to other vehicular
modes such as driving or traveling by train. The transportation perspective introduces
the flow capacity discourse where an unimpeded flow is valued as good pedestrian
activity. The social perspective encompasses the many other reasons for traveling by
foot: exercise, recreation, shopping, social interaction, spiritual rejuvenation, or charity
(Lo, 2009). In Paulo de Cambra’s research on pedestrian accessibility and
attractiveness in Lisbon, Portugal he defines the three primary motives for walking as
transport, exercise, and recreation/pleasure. See Table 2-1 for a table of multiple
definitions of walkability as introduced in the literature.
In light of the struggle to simplify what defines an environment as a good
walkable space, it is best to first understand the theories as to how we moved away
from building them. Post-World War II expanded the popularity of the suburb and the
21
Cold War era further fueled the movement away from the human scale. In a time of
paranoid McCarthyistic thinking, possessing a single-family home was not only
represented as the American Dream, but also proof of American patriotism. Residents
showed their dedication to the capitalistic society by parading their wealth with their
material goods (Browner, 2013). Streets are now over-scaled, typified by coarse blocks,
residential cul-de-sacs, homogeneous land uses, and placement of sidewalks on the
outskirts of expansive box store parking lots and multi-lane highways (Forsyth &
Southworth, 2008). Aside from the accommodation of the automobile, Bradshaw views
the loss of localism as one of the primary causes of America’s eroding walkable
infrastructure. People no longer ‘live local’, overlooking the resources of the local
community in favor of the comforts that can be provided by the single-family home. This
has led to an imbalanced infrastructure where many public problems are solved
privately. For instance, instead of investing in creating vibrant civic spaces where one
interacts with the community, people purchase health-club memberships and invest in
extensive home security systems and car alarms (Bradshaw, 1993).
One of the most notable first attempts at physically assessing the concept of
walkability was conducted by Chris Bradshaw. Instead of one single definition, he
categorized walkability into four basic characteristics:
1. A "foot-friendly" man-made, physical micro-environment: wide. level sidewalks, small intersections, narrow streets, lots of litter containers, good lighting, and an absence of obstructions.
2. A full range of useful, active destinations within walking distance: shops, services, employment, professional offices, recreation, libraries, etc.
3. A natural environment that moderates the extremes of weather- wind, rain, sunlight - while providing the refreshment of the absence of man's overuse. It has no excessive noise, air pollution, or the dirt, stains, and grime of motor traffic.
22
4. A local culture that is social and diverse. This increases contact between people and the conditions for social and economic commerce. (Bradshaw, 1993, par. 5).
It has been shown that the successful community design Bradshaw calls for is
significantly associated with moderate levels of physical activity (Frank et. al, 2005). In
recent years, there have been multiple attempts at redeveloping areas to create more
walkable spaces. However, due to the lack of a cohesive understanding of how
walkability should be measured among different fields, most attempts have failed (Lo,
2009). For instance, the public health field encourages the promotion of physical
activity, transportation engineers focus on creating efficient flow capacity for walking
transportation, urban design emphasizes the user experience from the aesthetic
viewpoint, and the planning field embraces a broader perspective, suggesting solutions
in policy changes and regulating future development.
Ria Hutabarat Lo examines the current discourse between the multiple
disciplines and contradictions in their understandings of the ideal ‘pedestrian space’. For
instance, the 2004 American Association of State Highway and Transportation Officials
(AASHTO) Green Book and the 2000 Highway Capacity Manual (HCM) guidelines both
attempt to create a pedestrian level of service measurement, yet still retain a bias
towards motorized transportation modes. In the 2004 AASHTO Green Book, pedestrian
infrastructure is designed per the road’s vehicular function and the HCM 2000
guidelines treat pedestrians as ‘atomistic’, non-social beings. In these guidelines,
pedestrian interaction/presence is a potential conflict while in planning it would be seen
as a sign of street vitality. Danish architect, Jan Gehl, argues in support of pedestrian
interaction and claims walkable environments should have a higher ratio of optional
23
pedestrian paths to encourage people to stay and interact with the street rather than just
pass through (Lo, 2009).
In contrast, one year after the publishing of Lo’s article, the Institute of Traffic
Engineers (ITE) created guidelines on designing walkable urban thoroughfares based
on context zones. This approach is seen in form-base codes where thoroughfare design
is dependent on the context zone, which is defined by the anticipated vehicular and
pedestrian use in dense urban environments. The features that create context in each
zone include land use, site design, urban form, and building design (i.e. human-scale
and architectural variety and number of entryways). Per the ITE, a walkable community
should form “a complimentary relationship between transportation, land use, and urban
design character of a place” (Institute of Transportation Engineers, 2010, p. 4). These
guidelines exemplify a shift of the transportation field toward better incorporating the
pedestrian perspective.
Measuring Walkability
Factors that Influence Walkability
Travel behavior research is extremely useful for understanding people’s
transportation choices and what factors most or least influence a user’s perceptions
when choosing a mode of transport or path. Using Susan Handy’s utility-maximization
model for travel, it is assumed “travelers will minimize travel time … to maximize utility”
(Cambra, 2012, p. 8). In this analysis utility is valued in terms of minimizing monetary
and travel time “costs” and increasing benefits such as comfort and convenience. By
this way of thinking walking would be the most obvious transportation choice if it
provided the shortest travel time. However, walking also offers other possible positive
24
attributes such as aesthetically pleasing scenery and social interaction which can
considerably add to a person’s potential utility (Cambra, 2012).
The conceptual framework of how perceptions of the physical environment
directly and indirectly influence walking behavior is best summarized by the work of
Ewing and Handy (see Figure 2-1). Urban design qualities are based on aesthetics and
user experience and can be interpreted differently by each individual. While important,
the subjective nature of design qualities and user perceptions make it very difficult to
analyze in a standardized and unbiased manner. Thus, Ewing and Handy attempted to
create uniform qualitative and operational definitions of five of the perceptual qualities
listed below to expand the opportunities to measure design features (see Table 2-2).
Of course, the relationship between an individual and their travel choices is not
limited solely to the physical characteristics of the built environment or urban design,
they are influenced in the long term by many other sociodemographic factors such as
lifestyles, social norms, income, disabilities, and personal preferences. If we examine
income for instance, a lack of bus service would more likely influence a low-income
person to walk than someone of higher income, who likely can afford a personal vehicle.
Persons of lower income can also be more likely to live in places of higher population
density (Marquet & Miralles-Gusach, 2014). Nonetheless, due to the limited scope of
the research, this paper will primarily focus on the relationship between the physical
attributes of the built environment and the decision to walk.
How to Measure Walkability
In the last two decades, there has been an increasing demand for more non-
motorized transportation options by creating environments more safe and conducive to
walking and biking. With the rise of recent urban design philosophies, such as new
25
urbanism, smart growth, and transit-oriented development (TOD), defining walkable
environments has taken on a more scientific approach, linking low-density single use
development with negative impacts on physical activity (including walking).
When measuring the relationship between the built environment and walkability,
analysis is conducted at either macro or micro scales, but unlikely together. The macro-
scale analyzes the overall urban form of a city or region, measuring objective features
such as average block size, street connectivity, land use diversity, and density. Data
sources are often easily accessible including information from public databases, GIS
maps, and satellite imagery. On the other hand, the micro-scale is analyzed at the street
level and is often typified by the more subjective analysis of quantifying urban design
qualities. Data can also be sourced from public databases, but is more conducive to
field/survey analysis, measuring features such as conditions of the sidewalk, abundance
or lack of street furniture, quality of landscaping, and level of enclosure.
Proponents of the macro-scale state street level analysis is “too micro to exert
any fundamental influences on travel behavior” (Cervero & Kockelman, 1997, p. 203)
while macro factors such as reduced transit costs from density and land use are “the
principal determinants of commuting choices” (Cervero & Kockelman, 1997, p. 203). On
the other hand, opponents such as Louis Neto, claim it is much easier to make changes
at the micro-level where the pedestrians experience the street. Additionally, urban form
is much harder to change as the urban environment is already built (Neto, 2015).
However, some may refute, identifying where urban form may be hindering walkability
can guide/prioritize future redevelopment and growth.
26
In conclusion, both scales offer their own merits and drawbacks. The quality of
analysis is dependent on the context of the research problem, the research methods,
and how the researcher decides to incorporate the levels of analysis into their research.
Indicators
When the concept of assessing the relationship between the built environment
and walkability first arose, academics and practitioners relied heavily on assumptions
formed by reviewing pre-existing walkable communities. While there remains no uniform
list of what specific factors strongly correlate with walking, in recent years there has
been extensive research trying to create a scientific base of built environment
correlates.
A diverse land use mix, density, street connectivity, and accessibility to non-
residential destinations most consistently appear in the literature as strongly correlating
with the walking.
Density and land use mix
They are often the most closely related walkability measures, especially when
discussing the trend of compact development. When walking for transportation, density
brings origins and destinations closer together (Cervero & Kockelman, 1997). A higher
density supports mix-use development by increasing access to more
services/destinations in shorter, walkable distances. Smaller blocks in high density
areas can also contribute to increased difficulty in driving and parking, with less large
parking lot development. A diverse mixed land use also “allows for a more varied built
form” (Reagan, 2017, p. 35). Studies have shown compact growth and mixed-use
development can improve quality of life, but not likely in areas that are already
predominantly low density (Yang, 2008).
27
Street network connectivity
This topic frequently appears in walkability literature, alongside land use mix and
density. Street network connectivity often refers to intersection density or a traditional
grid layout, with a high number of four-way intersections. The thought is a higher density
allows more route choices and a pedestrian can then travel more efficiently from place
to place. A higher density grid network also means smaller blocks and some studies
suggest that car travel is reduced in areas with short blocks and well-connected street
networks likely because a dense urban environment can provide more opportunities for
a shorter commute by transit, biking, or walking than by personal vehicle (Cervero &
Kockelman, 1997; Ewing & Cervero, 2010). Shorter blocks also equate to more street
frontage and more land dedicated to the street. However, some city leaders believe the
less area dedicated to the street, the better. Too much land dedicated to the street is a
waste of productive, taxable land – a view criticized by Jane Jacobs who believes a
vibrant street life is the foundation of city design (Jacobs, 1961; Price, 2013).
More street frontage also offers a greater potential for access to destinations
within walking distance. ‘Destinations’ can refer to amenities such as schools, parks,
shopping, civic squares, offices, and entertainment. Destinations can offer more
opportunities for social interaction, such as a place to stop for coffee on the way to work
or a spot in the park to people watch. Additionally, persons who live closer to diverse
retail opportunities are more likely to make shorter, frequent shopping trips in
comparison to persons who live in sprawling suburbs and must combine multiple
shopping trips and travel farther distances by car (Leslie et al., 2007). In a meta-
analysis of travel choice and the built environment, it was found lower number of vehicle
miles traveled (VMT) was most strongly related to accessibility to destinations. In
28
addition, the number of destinations was listed as one of the top three variables
correlated with walking next to land use diversity and intersection density (Ewing &
Cervero, 2010).
The remaining walkability indicators can be summarized as Kockelman and
Cerevo term ‘pedestrian oriented design,’ including physical factors and design qualities
such as shade trees along sidewalks, rear parking lots, entrances near curbsides, public
parks, raised crosswalks, bike lanes, and access to public transit (1997; Marquet &
Miralles-Gusach, 2014).
User perception and the importance of indicators
There is a consensus in all literature that there is no single characteristic which is
the most important or necessary contributor to walkability. This phenomenon is
sometimes referred to as spatial multicollinearity. Spatial multicollinearity is when urban
attributes are ‘spatially connected’, or in other words, complementary in their relations
between the built environment and walking. The interrelated nature of urban attributes
makes measuring walkability very difficult (Neto, 2015).
In numerous past research, scientists have attempted to categorize urban
attributes into more condensed and measurable lists, which will assess only the most
influential characteristics. Cervero and Kockelman assess travel demand by
categorizing the built environment into the 3Ds: density, diversity, and design (1997).
Handy & Ewing measured urban design qualities of the street by classifying the qualities
into 5 categories with a list of physical measurements for each (See Table 2-2) (2009).
With the creation of an extensive walkability index, deCambra organized his proposed
indicators in the 7Cs layout: connectivity, convenience, comfort, conviviality,
conspicuous, coexistence, and commitment (2012).
29
As mentioned prior, the high multicollinearity among indicators can make it
difficult to assess the importance of one indicator over another. This is due to the
unpredictability of human behavior. People walk for many different purposes and may
prioritize different factors accordingly. For instance, a commuter may care more about
sidewalk width and availability of coffee shops along their route while someone who
likes to walk for exercise may value design qualities which enhance the aesthetic
experience (Lo, 2009). Therefore, it is important to simultaneously incorporate known
walkability factors to create meaningful spaces that will influence pedestrian life
(Cervero & Kockelman, 1997).
Past research methodologies
As walkability research has developed, there have been numerous methods of
approach when attempting to assess the relationship between the built environment and
pedestrian accessibility. Chris Bradshaw is recognized as one of the first to develop a
relatively useful walkability index. The index ranges from 0.45 to 2.0 and can be
completed by an average community member who must answer 10 questions. The
index assesses walkability on the neighborhood scale, considering both physical
features and user perceptions such as density, parking places, frequency of transit
service, and women’s feeling of safety (Bradshaw, 1993).
More recent research projects of the 21st century almost all involve the use of
open source tools like Geographic Information Systems (GIS). For instance, Emily
Talen attempted to introduce a process for measuring accessibility in local urban
planning practice in Portland, Oregon. Talen used GIS to analyze the distance between
residential areas and neighborhood-level parks and schools (simple origin destination,
and distance analysis). Additionally, GIS results were supplemented by census tract
30
socioeconomic data, a common practice in much of the literature following her
publishing. Although Portland is viewed as a walkable city in support of smart growth
policies, only 12% of the residential parcels are within walking distance of a park or
school. Talen also discovered the greatest access to these facilities was in areas with a
higher percentage of low-income housing and minority populations (Talen, 2002).
Combining GIS and accelerometers, Frank et al. assessed the relationship
between measured levels of physical activity and the participants’ surrounding (home)
physical environment. GIS was utilized to assess land-use mix, residential density, and
street connectivity which were combined in a walkability index. Accelerometers were
used to measure the physical activity of 357 adults over a two-day period. Land-use
mix, residential density, and intersection density were positively (and significantly)
correlated with greater amounts of physical activity and concluded as a having a higher
walkability (Frank et. al., 2005). Lawrence Frank participated in another Australian study
in which Frank and his colleagues creates a GIS-based Walkability Index, in which
certain measures, such as proximity of destinations, intersection density, residential
density, and net retail area. Each measure was standardized by creating a score
between 1 and 10; the final walkability index was created by adding the sum of each
measure’s score, with a possible range of 4-40 (Leslie, et al., 2005).
There is much fewer research available on measuring user perceptions due to
the subjective nature of individual bias. In 2009, Reid Ewing and Susan Handy made a
notable contribution to the topic. The methodology included a panel of urban design
experts reviewing sets of video clips mimicking the pedestrian experience. The clips
were focused on commercial/main streets across the US. The paper then rates physical
31
features and their level of significance to each urban design quality (i.e. imageability or
enclosure). Furthermore, the research produces operational definitions for each of the
chosen eight urban design qualities, creating the possibility to objectively measure
design qualities at the street level (Ewing & Handy, 2009).
Louis Neto took a similar approach to define and quantify user perceptions by
utilizing an image-based survey. The survey first informed respondents of perceptual
qualities with visual examples. The survey then introduced images of example streets
from two neighborhoods—one characterized by organic growth patterns and the other
newer planned development—to determine the respondents’ perceptions of paths as
walkable or non-walkable environments. Neto then used a multiple linear regression
analysis to develop a weighting system based upon survey results. The index was
applied on two different streets, measuring 48 relevant indicators determined by the
survey. The street in the planned neighborhood was determined to be the most
walkable street and reflected many similarities with the survey respondents’ choices
(Neto, 2015).
One of the most recognizable tools that has developed today is Walk Score, an
online application which classifies how walkable an area is depending on how
accessible a point is to a set of amenities. Amenities are given a maximum value if
within a 5-minute walk (1/4 a mile) and zero points if beyond 30-minutes. In addition, the
company has recently expanded its scope of analysis to include a Bike Score and
Transit Score. The application uses an algorithm to analyze multiple possible walking
routes and awards points based upon distance to amenities in five minute to thirty
minute distances. The application also takes into account other morphological
32
characteristics such as block length and intersection density (Walk Score, n.d.). Critics
argue Walk Score does not account for the quality of the walking environment due to
dynamic environmental conditions as a result of income disparities (i.e. graffiti, poor
sidewalk conditions, and safety concerns) (Koschinsky & Talen, 2017).
These attempts to identify and assess the magnitude of the relationship between
objective factors of the built environment and walking is often a lack of an assessment
of how objective features are perceived by the pedestrian on an individual level. This
gap can be addressed through subjective behavioral surveys. Andrea Livi and Kelly
Clifton of the University of Maryland attempted to overcome previous survey bias by
creating a survey to address walking as both a physical activity and means of
transportation. The survey was conducted in three separate communities in the larger
College Park area via a door-to-door method. Their research found responses were
highest in areas with higher levels of community engagement and that there “was a
widespread ignorance of walking behaviors” (Livi & Clifton, 2015, p. 8). This survey has
influenced the creation of the surveyed used in this research as well as the choice of
survey method.
Overall, there is a general consensus in the ailments of our current urban
infrastructure and the role automobiles have played in creating it. Although ranging in
scale, time, cost and location, the literature has been able to provide a solid foundation
of measurable indicators to use in the assessment of Gainesville’s streets. Due to the
evidence of multicollinearity between built environment indicators, this research will not
attempt to measure potential walkability based upon one or two urban attributes
believed to be most influential nor will it claim one is of more significance than another.
33
Instead, this research will analyze a combination of physical attributes present, and
evaluate the quality of walkable space created. Past research has shown GIS and
satellite imagery to be successful tools in assessing the built environment and will be
utilized in the following project. There has also been a lack of validation of objective
measurements by human users. Other forms of validation have emerged in past
walkability index research, however, the validation efforts often cross-checked the
physical and socioeconomic characteristics of the site areas by field visits, but did not
involve human input. As a result, this research will plan to incorporate a survey
component.
34
Table 2-1. Definitions of walkability
Term Definition Source
Walkability “the extent to which the urban environment is pedestrian friendly”
(Cambra, 2012, p. 1)
Walkable “a street, neighborhood, or city conducive to walking.”
(Budick, 2008, para. 1)
Pedestrian Access “the quality of having interaction with, or passage to, a particular good service or facility.”
(Talen, 2002, p. 259)
Pedestrian Access “the ability to reach a given destination based on geographic distance”
(Talen, 2002, p. 260)
Walkable “capable of being traveled, crossed, or covered by walking; suited to or adapted for walking”
Dictionary.com
Walkable Encouraging physical activity; close; barrier-free; safe; upscale, leafy, or cosmopolitan
(Forsyth & Southworth, 2008)
Table 2-2. Example Urban Design Quality Definition
Urban Design Quality Qualitative Definition Operational Definition
Imageability “The quality of a place that makes it distinct, recognizable, and memorable… specific physical elements and their arrangements capture attention, evoke feelings, and create a lasting impression” (Ewing & Handy, 2009, p. 73)
• Number of people
• Proportion of historic buildings
• # of courtyards, plazas, and parks
• Presence of outdoor dining
• # of buildings with non-rectangular silhouettes
• Noise level
• # of major landscape features
• # of buildings with identifiers
35
Figure 2-1. Ewing & Handy – Perceptions and Walkability
36
CHAPTER 3 METHODOLOGY
Conceptual Framework and Study Design
This research will be exploring the relationship between characteristics of the
physical built environment, otherwise referred to as the urban form, and the potential
walkability of the area. In other words, the extent to which the built environment
supports pedestrian activity by providing diverse and safe access to quality destinations.
Please see Figure 3-1 for a visual representation of the research’s conceptual
framework. This is accomplished through a mixed method approach: through 1) the
creation of a walkability index calculated using objective measures in GIS and, 2) an
intercept survey.
It has been argued physical features alone do not provide a holistic
understanding of the walking experience in a particular environment. In other words,
objective measures, such as block length or density do not capture people’s overall
perceptions of the built environment. The perceptions of the individual pedestrian may
affect walking behavior equally, or to a greater extent than physical objective attributes.
Therefore, incorporating a subjective form of analysis in the form of an intercept survey
would increase the quality of the study as well as provide a form of possible validation to
the objective GIS measurements.
Study Areas
Scale
The following research was conducted on a macro-scale; research is focused on
the neighborhood-level, analyzing features such as sidewalk coverage, building density,
and street network connectivity. This research does not focus on the more subjective
37
features of the street such as level of enclosure, sidewalk condition, or presence of
shade trees. Due to the ease of accessing demographic data, site boundaries are
defined by the edges of US Census Blocks.
Site Overviews
The two following sites were chosen because they each contain hubs of
commercial and mixed-use activity likely to attract pedestrians.
As seen in Figure 3-2, the Downtown site is centered by the intersection of Main
Street and University Avenue and totaling roughly 571 acres. This area currently
functions as the city’s traditional Downtown. The site area has a more urban style of
development with a modified grid street network, small blocks, and houses important
governmental buildings for both the city and the county including Gainesville City Hall,
the Alachua County Administration Building, and the Alachua County Courthouse. If a
Walk Score was calculated from the Alachua County Administrative Building at the
corner of Main St and University (see the yellow dot in Figure 3-2) the site would receive
a Walk Score of 91, classified as ‘Walkers Paradise’ (WalkScore, n.d.).
Most of the housing within this site boundary is either multi-family housing
located within multi-use structures with retail on the bottom and residential on top or
smaller single-family housing located along the outer edges of the site. The average
population density is 7.76 people per acre. The median age of residents in the area is
20.42 years of age, roughly only four years less than the median age for the City of
Gainesville. This is very likely due to the high population of students in the city who
attend the University of Florida or Santa Fe College and the proximity of the site to
facilities for both institutions. The racial makeup of this site is approximately 67%
38
Caucasian, 25% Black or African American, 3% Asian,2% other race, 2% multiracial,
and 1% Native American (U.S. Census Bureau, 2010).
Seen in Figure 3-3, the Millhopper Area is approximately 593 acres and is
typified by more suburban development with large groups of single-family homes and a
central commercial corridor. This includes three shopping centers with large parking lots
and fast food/commercial strip development along the two arterial roads of NW 43rd St
and NW 16th St and single-family housing along interior collector and local streets (see
Figure 3-3). It should be noted part of the Millhopper site boundary expands into
unincorporated Alachua County, but the character of the site is generally seen as being
within the Gainesville area (see Figure B-1). If a Walk Score was calculated from the
Alliance Credit Union at the corner of NW 16th Blvd and NW 43rd St (see the yellow dot
in Figure 3-2), the site would receive a Walk Score of 62, classified as ‘Mostly Walkable’
(WalkScore, n.d.).
The average population density is 4.5 people per acre. The median age of
residents in the area is 44. The housing largely consists of single families and a few
retirement-oriented complexes. Two specific complexes for ages 55+ are the Atrium and
the Courtyards located along NW 25th Circle. The racial makeup of this site is
approximately 88% Caucasian, 5% Black or African American, 3% Asian, 2% other
race, and 2% multiracial (U.S. Census Bureau, 2010).
Morphology Comparisons
The following information references Figures A-1 through A-8 in Appendix A. To
begin, Downtown demonstrates a fine grain, modified grid network with high physical
and visual permeability and some grid erosion. This grid allows for more pedestrian
route choices and therefore more opportunities for social interaction. Millhopper, on the
39
other hand, appears more suburban in nature, with longer distances between route
changes and many dead-end streets, in the northwest corner in particular. While these
streets are closer together, they represent a line of strip mall and fast-food
establishments along the major arterial NW43rd and do not connect with one another. In
the center of the site there are also three large ‘gaps’ in the street network at the
intersection of NW 16th St and NW 43rd St. These locations currently host a cemetery
and two shopping centers with large street-front parking lots. This type of development
encourages vehicular travel as pedestrians have to travel longer distances to get from
one location to another.
As reflected by the street network, Downtown has mostly small and medium
blocks, while Millhopper’s are medium to large. Many blocks along the east, south, and
north of the site are characterized by long, but narrow blocks of single-family housing.
To note, a few of the blocks in Millhopper are cropped by the site boundary and are
larger than they appear.
When analyzing the figure ground, there is relatively more space than mass in
both sites, which indicates little definition of the street by building envelopes. The size of
the building footprints also indicates a higher density of single-family residential in the
southern and western portion of the Millhopper site. In Downtown, there is some
evidence of buildings defining the space and creating strong edges in bocks near the
intersection of University and Main. This could contribute to a stronger sense of place
by creating enclosure and the sense of an outdoor "room." However, this density pales
in comparison to other areas around the world such as New York and other famous
European cities such as London, Paris, and Florence, Italy. Millhopper shows no
40
evidence of any defining spaces, with all the buildings setback from the street.
Millhopper’s wide arterial roads also indicate the areas design for high volume vehicular
traffic.
Zoning
Due to zoning’s considerable influence on the policies and regulations that
dictate the function and aesthetic of American cities, a brief examination of each site’s
current zoning designation has been included. The City of Gainesville recently adopted
a new land development code. The new code is a hybrid of form-based code and
Euclidean zoning. One of the main benefits of adapting form-based code principles is a
more streamlined development process and greater legislative and administrative
efficiency. Certain areas of the city remained unaffected by these changes and retain
their previous zoning classifications. Downtown can be argued to have received the
greatest level of changes. However, the intent for the character and future development
of these areas remains relatively the same. See Figures B-2 and B-3 in Appendix B for
the zoning maps for each study area.
Of the two study areas, Downtown has a greater variety of zoning classes. The
most prominent zoning classes support mixed uses and high density such as
Downtown, multi-family medium residential, and three new Urban Zones: urban mixed
use 1(U6), urban mixed use 3(U9), and urban office residential (U4). Urban Zones 2-5
consists of a range of residential building types, some integration of offices and
neighborhood service, and medium-sized blocks. Urban Zones 6-9 “Consists of higher
density mixed use buildings that accommodate retail, offices, and apartments” (City of
Gainesville, 2017, p.14). This area has a higher street network density, wider sidewalks,
stricter street planting requirements, and buildings set closer to the street. Downtown
41
has the highest density, height, and use allowances, functioning as the most urban
classification. (City of Gainesville, 2017).
Office, Business and Retail/Services, Business Professional, and Multi-Family
medium density residential zoning classifications are centrally located within the
Millhopper study area. The remainder of the surrounding area is either Planned
Development (PD) and Single Family Residential. Overall the study area is
characterized by centralized medium-intensity uses surrounded by lower-intensity
single-family development.
Block Groups
Each study area is divided into four subsections. Subdivision of the study areas
was based off 2010 Census Block Groups. The actual Census Block Groups were
modified for this research for two reasons. First, Census Block Groups are based off
population, ranging between 600 and 3,000 people but often averaging around 1,500
(U.S. Census Bureau, 2010). Due to the abundance of single family housing in the
Millhopper area, the boundaries of the block groups were reduced in order to provide a
fair size comparison to the more dense Downtown study area. Second, the author
attempted to keep the boundaries in a relatively square shape. This task proved easier
in Downtown where many of the Census Block boundaries line up in a relatively straight
line due to the more grid-like street network. The more curved roads of the Millhopper
area created an irregular site boundary (see Figure B-4).
Data Collection – Walkability Indicators
There are many constraints to walking such as physical handicaps, extreme
weather, distance traveled (stamina), noise levels, or levels of violence and crime in an
area. The following model will attempt to measure the walkability of an environment for
42
a relatively healthy individual in a mild to moderate climate and no other possible
obstructions.
Independent and Dependent Variables
The independent variables are the chosen indicators measuring characteristics of
the built environment including connectivity, density, diversity, pedestrian friendliness,
and proximity. The dependent variable in this research is the generated walkability
index score for each site. The walkability index score represents the potential walkability
of the site areas based on the urban form.
Choice of Indicators
Past walking indices have typically been calculated by adding the sum of each
indicator’s z-scores. Most indices include some combination of residential density, street
network connectivity, commercial density, average block size, and land use mix. See
Table 3-1 for a list of the most frequent indicators which appeared in the literature and
Figure 3-4 below for a few example indices.
Calculating the Final Walkability Index
Out of the previously mentioned indicators the following were chosen for the final
index. The index was calculated by finding the sum of each indicator’s z-scores applied
at the block group level. The index scores are normalized to z-scores due to a lack of a
uniform unit of measurement between the indicators. Example screenshots of each
indicator and list of shapefiles used can be found in Figures 3-5 through 3-9 and Tables
3-2 through 3-9 at the end of the chapter.
WI = NRD + BD + SC + ID + EI + Dest +AT (3-1)
• NRD: Net Residential Density
• BD: Building Density
• SC: Sidewalk Coverage
43
• ID: Intersection Density
• EI: Entropy Index (Land Use Mix)
• Dest: Destinations
• AT: Access to Transit Net residential density
Net residential density functions as an indicator for general density patterns. To
begin, a household is “a residential unit of one or more people who live together and
may consist of a single family or some other grouping of people” (Agampatian, 2014, p.
33). A higher residential density can indicate a higher ratio of multi-family housing.
Commercial and recreational services are then likely to be built near dense residential
areas because the population can support the larger mix of services provided typical of
more urban, centralized environments (Agampatian, 2014).
NRD = Number of Households/Area of Residential Parcels (3-2)
Building density (mass v. void)
As revealed by the name, building density is a measure of density. The resulting
measurement will be a percentage of building coverage; the higher the percentage, the
higher the potential walkability. A value closer to zero would imply an area with relatively
little building mass and long spaces between structures, typified by suburban
development or shopping malls with large surface parking lots. A higher density is
representative of compact development where destinations and points of interest are
brought closer together. Compact development also means a denser street network and
reduced cost of public transit.
The author chose to incorporate the area of the entire site rather than total parcel
area to account for variations in street widths. Therefore, the building density indicator is
very unlikely to reach 100%.
44
BD = Area of All Buildings /Site Area (3-3)
Sidewalk coverage
Sidewalk coverage is a measure of pedestrian friendliness, or in other terms,
safety. It is assumed that greatest pedestrian safety and access is generated by the
presence of sidewalks on both sides of the street. The road length is multiplied by 2 to
account for this assumption. The closer to the value of 1 implies more sidewalk
coverage and separate spaces for pedestrians to travel off the roadway, and therefore
greater walkability.
SC = Total Length of Sidewalks / (2 x Length of Road Network) (3-4)
Intersection density
Intersection density is a measure of connectivity. For this indicator, Network
Analyst was used to generate a street network dataset and accompanying street
junctions. Only ‘true’ intersections consisting of 3 or more legs were included in the
analysis. Additionally, if two intersection points are less than 15 meters from one
another, it is considered one intersection.
Previous studies have found higher numbers of intersections to be positively
correlated with non-work walking trips and total distance traveled (McCormack & Shiell,
2011). A higher intersection density suggests a denser grid network and more route
choices for the pedestrian to get from point A to point B.
ID = Number of Intersections/Site Area (3-5)
Entropy index
The entropy index is a measure of diversity. The entropy index is used to
calculate the level of heterogeneity of land uses. The entropy index is measured at the
45
Census Block level using a GIS script, providing a score between 0 and 1. A value of 0
indicates a homogeneous land use pattern and value of 1 indicates an even distribution
of all land use types. The equation is as follows:
Entropy = 𝛴𝐴𝑃𝐴𝑥ln(𝑃𝐴)
ln(𝐴) (3-6)
Where,
𝑃𝐴= the proportion of total land area of each land use category A found in the
area being analyzed. A = total land uses considered in the study area. In this case A =
15. The generalized land use categories used for this equation are listed below:
1. Acreage Not Zoned for Agriculture 2. Agricultural 3. Centrally Assessed 4. Industrial 5. Institutional 6. Mining 7. Other 8. Public/Semi-Public 9. Row 10. Recreation 11. Residential 12. Retail/Office 13. Vacant Nonresidential 14. Water 15. Vacant Residential
Different types of facilities (i.e. destinations) generate a different level of utility
and frequency of visitation depending on socio-demographic group. For instance, bars
and clubs may be more popular among young adults and playgrounds and schools may
be more visited by families. Meanwhile, grocery stores present a high utility across all
socio-demographic backgrounds. As a result, a greater mix of land uses is most likely to
generate walking activity among all members of the population (Cerin et al., 2006).
46
Destinations
The destinations indicator is a measure of proximity. It describes the number and
variety of points of interest accessible within walking distance. The destination points
used were based on the availability of data and the likelihood of being drivers of
walking. To attempt to account for the use frequency of the destinations, a weighted
system was used. All destination types were weighted on a scale of 1-5 according to
findings from past studies and personal survey experience with 5 indicating the
destination most likely to produce foot traffic. Destination types with no precedents in
the literature were given a default value of 1. The method consisted of 6 steps:
1. Gathered all point of interest shapefiles, merged, and converted to point data. A new field ‘DestType’ was created in which the points of interest were classified into one of the classifications in Table 3-7.
2. The next step required the creation of Service Area buffers. As a result, a street network dataset was created using a road centerline shapefile. Using the Service Area buffer function in the Network Analyst extension, vector polygon buffers were created from each group of destination points. Since most weekday walking trips are 10 minutes or less, a 804-meter (0.5 mile) buffer distance was used. At this point, each polygon layer produced represents a type of destination.
3. The buffer polygons were converted into raster polygons. The values of all the raster cells were 1.
4. The raster layers were then reclassified. In this step the cells of each raster polygon were given the new weighted value according to Table 3-7. All cells outside the raster buffers were given a value of 0.
5. The Raster Calculator was employed to calculate the sum of all the overlapping polygons, giving each cell a value between 1 and 25. A value of 25 would occur if all raster polygons overlapped on that level. In other words, all destination types are within a 0.5-mile distance from that cell.
6. Zonal statistics were employed to find the mean value of all cells within an area. The modified block groups seen in Figure B-4 were used as the zonal boundaries for analysis.
7. The end result was a mean destination value per block group and overall site boundary seen in Figure B-5.
47
Access to schools and shopping malls within a 400 to 1500-meter distance has
been associated with transport-related walking on a regular basis (Ewing & Cervero,
2010). In addition, schools have been found to be major drivers in increasing walking
and biking in children, although the highest rates are mostly limited to already well-
connected neighborhoods (Steiner at al., 2008). In this research, “Schools” include both
primary, secondary, and college/university level of education. Ability to walk to school
may be of importance in this research due to both Gainesville’s high single-family and
college student population.
There have been several studies demonstrating commercial activity to have
positive correlations with walking behavior. For instance, Cervero & Kockelman found
placing grocery and convenience stores between business and residential areas
increases transit commuting. Another cross-sectional study of households from 32
different communities found food shops were consistently a frequent trip destination
among all sociodemographic backgrounds. Furthermore, proximity of retail shops and
other commercial destinations in a person’s neighborhood is strongly correlated with
walking trips (Cerin et al. 2006; Cervero & Kockelman, 1997). Boarnet et al. found an
increase in transportation-related walking trips for people who lived near commercial
centers (Cerin et al., 2006).
In the surveys conducted for this research, restaurants included venues such as
coffee shops and bakeries. While these destinations already function as a place for
social gathering, they are also popular locations for college students to study off-
campus. As a result, restaurants were valued as slightly more important than the default
value of 1 due to the Gainesville student population.
48
Frank et al. found people living in a neighborhood with parks and open spaces
were twice as likely to walk for a “home-based” walking trip, such as shopping and
recreation. Living in neighborhoods with a grocery store was associated with a 1.5 times
greater likelihood of getting sufficient daily physical activity (2010). Distance to a grocery
store has also been found to be negatively associated with the frequency of walking to
other stores within the neighborhood. In other words, the lower the distance between
the home and the grocery store, the greater the frequency of walking trips generated
(McCormack & Shiell, 2011).
Access to transit
Access to transit is a measure of proximity. Gainesville does not have a metro or
form of light or heavy rail, therefore, ‘transit’ refers to Gainesville’s RTS bus service. The
higher the ratio of bus stops to site area indicates a greater access to public transit. A
greater access to transit stops would theoretically reduce car ridership by providing an
alternative mode of transportation. Studies have found the closer an individual is to a
transit stop, the more likely they are to use public transit to travel to work. Walking
would increase as individuals walk to and from the bus stop to their destination of
choice. This intermediate mode of travel occurring between a transit stop and the final
destination is referred to as the first/last mile phenomenon (Hsiao, S., Lu, J., Sterling, J.,
& Weatherford, M.,1997). Taking the bus may also be a more attractive alternative to
traveling a destination where it is difficult to find free parking, such as in downtown
Gainesville. This measure is limited in that it does not take into account the frequency of
bus service nor the destinations associated with each bus route.
AT = Number of Bus Stops/ Site Area (3-7)
49
Survey
Purpose
The survey provides a possible form of validation by assessing the impact of
physical features in the walking environment on walking behavior through the
perceptions of walkers. In other words, the purpose of the survey is to see if there are
any parallels between the perceptions of the pedestrian’s view and the index’s results in
determining if the site area is walkable.
Audience and Approach
Many of the questions in the survey were influenced by “Issues and Methods in
Capturing Pedestrian Behaviors, Attitudes and Perceptions: Experiences with A
Community-Based Walkability Survey” by Andrea Livi and Kelly Clifton from the
University of Maryland (2015). However, unlike the previous study, this research will use
an intercept-survey method of approach. The aim of the survey is to obtain responses
on the perceptions of pedestrians in a walking environment and therefore, the survey
only approached those who were performing the activity. This decision is made under
the assumption an individual already walking may walk more often and be more
cognizant of what features may affect their walking behaviors more than the average
citizen.
Prior to conducting the surveys, the researcher visited both study areas and
observed the general walking patterns of pedestrians within each location. The survey
was conducted in person on a handful of both weekdays and weekends over a period of
two months. Survey questions and read and responses recorded by the researcher
using pen and paper. Responses were later digitized into UF’s survey software
Qualtrics for data analysis. During the intercept survey, the surveyor attempted to
50
survey people of all ages above 17, regardless of race or ethnicity. Individuals jogging,
walking at a very fast pace, or walking in the opposite direction were not considered.
See figures C-1 through C-3 in the Appendix C for a copy of the recruitment script
informed consent form, and intercept survey.
51
Table 3-1. List of example indicators
Indicators Type Measurement Relationship to Walkability
Intersection Density Connectivity # of intersection points/ site area (Ac)
Also referred to as intersection density. A higher number indicates more intersections and therefore the assumption of more connectivity as compared to cul-de-sac and pod-like development. The closer to 1.0, the more walkable an area is assumed to be.
Street Network Density Connectivity Total length of street centerlines/area
The higher the density of street networks, the smaller the blocks and greater amount of path options for pedestrians.
Connectivity Index Connectivity # of street segments / # of intersections
Range is from 0 to 1.5. The closer to the number 1.5 indicates a perfect grid network.
Gross Residential Density Density # of residential units/ all acres of land (Ac)
A high residential density is needed to support a variety of commercial and recreational uses in the surrounding area.
Net Residential Density Density # of residential units/ acres of land designated residential (ELU)(Ac)
A higher density of net residents indicates more multi-family developments which supports more urban, mixed-use developments, often associated with more walkable environments.
Building Density (Mass) Density total bldg sq ft/ total site acres
Brings origins and destinations closer together. Reduces the cost of public transit.
Land Use Mix Diversity Shannon Index (GIS Script) determining proportion of mix of land uses
The more varied the spread of land uses, the greater the opportunity for mix of uses and destinations. Having retail and convenience stores close to residential homes can reduce out-of-neighborhood vehicular travel. For instance, siting retail and grocery shops between transit stops and residential homes can encourage transit commuting by linking work and errands on the way home. Also allows for a more varied built-form which can be conducive to walking.
52
Table 3-1. Continued
Indicators Type Measurement Relationship to Walkability
Sidewalk Coverage Pedestrian Friendliness
Total length of sidewalk (on both sides of street) in ratio to total length of street (%)
Presence of sidewalks offer a safe walking space for pedestrians to travel separate from motor vehicle traffic. A higher percentage of sidewalks would indicate more walking options for the pedestrian.
Sidewalk Continuity Pedestrian Friendliness
Longest stretch of unimpeded sidewalk in feet
Discontinuity of sidewalk presence can hinder walkability by obstructing safe/proper access from one destination to another. The longer the length of continuous sidewalk, the further the pedestrian can travel.
Sidewalk Density Pedestrian Friendliness
Total sidewalk length/SF
The higher the density, the more sidewalks present along street blocks, and more possible safe paths for pedestrians.
Destinations Proximity # of points of interest within 1/2-mile buffer of site areas
“People who live near multiple and diverse retail [and service] opportunities tend to make more frequent, more specialized and shorter shopping trips, many by walking” (Leslie, et al., 2005)
Access to Transit Proximity # of transit stops/ site area (Acres)
If multiple transit stops are located near home and destinations, it may become more convenient to travel by bus than by car.
Net Retail Floor Area Ratio (FAR)
Proximity Total SF of retail/ area of retail parcels
A higher ratio indicates retail is closer to the street edge (i.e. smaller setbacks), a lower amount of surface parking, and less pedestrian interaction with vehicles.
53
Table 3-2. Net residential density measures
Measure Unit of Measurement
Shapefile Source
# of households N/A 2017 county parcel data
FDOR
Area of residential parcels
Acres 2017 county parcel data
FDOR
Table 3-3. Building density measures
Measure Unit of Measurement
Shapefile Source
Building Footprints Square Feet 2017 county parcel data
FDOR
Site Area Acres Census Blocks FGDL – U.S. Census
Table 3-4. Sidewalk availability measures
Measure Unit of Measurement
Shapefile Source
Sidewalk Length Feet Sidewalk line data Alachua County GIS Dept
Road Length Feet Road Centerlines data
ACPA
Table 3-5. Intersection density measures
Measure Unit of Measurement
Shapefile Source
Intersection Points N/A Road Centerline Street Network Dataset
ACPA & Network Analsyt
Site Area Acres Census Blocks FGDL – U.S. Census
Table 3-6. Entropy index measures
Measure Unit of Measurement
Shapefile Source
Land Use Mix (EI) Entropy Index Value
Generalized Land Use
FGDL
Measure Unit of Measurement
Shapefile Source
Land Use Mix (EI) Entropy Index Value
Generalized Land Use
FGDL
54
Table 3-7. Destination weights
Table 3-8. Destination measures
Measure Shapefile Source
Points of Interest (POI) County parcel data; Alachua park points, RTS POI
FDOR, RTS, Alachua County GIS
Road Network Road Centerline Street Network Dataset
ACPA & Network Analyst
Table 3-9. Access to transit measures
Measure Unit of Measurement
Shapefile Source
Bus Stops N/A RTS bus stops RTS Site Area Acres Census Blocks FGDL – U.S.
Census
Destination Type Weight
Bank/ Financial Institution 1
Church 1
Grocery Store 5
Nightclub, Bar, or Lounge 1
Park 4
Restaurant 2
School 3
Shopping Center 3
Sports Facility 3
Theater 1
55
Figure 3-1. Conceptual Framework
56
Figure 3-2. Downtown site map
57
Figure 3-3. Millhopper site boundary
58
Figure 3-4. Example walkability indices
59
Figure 3-5. Building density
Figure 3-6. Sidewalk availability
60
Figure 3-7 intersection density
Figure 3-8. Existing land use (left) and entropy index (right)
61
Figure 3-9. Destinations
62
CHAPTER 4 RESULTS
This chapter is divided into two sections to examine and discuss the results of
the walkability index and the intercept surveys.
Walkability Index
In the section below, the results and findings will be presented for the walkability
index. The index results are broken down by each indicator, independent of the
composite index. The section concludes with a final presentation of the composite index
results.
Residential Density
Overall, Downtown showed higher levels of net residential density ranging from
4.01 to 6.58 housing units per acre per block group and an average 4.83 housing units
per acre overall. The highest density was found in block group 3, almost exclusively
consisting of residential structures. Block group 3 encompasses a major portion of the
neighborhood, the Duckpond. The Duckpond contains many historic, colonial-style
homes with narrow streets and mostly 0.2 to 0.3-acre residential lots. Millhopper, on the
other hand, has densities ranging from 1.08 to 4.16 housing units per acre, and
averaging 2.77 housing units per acre. The highest residential density was found in
block group 2 where there are two retirement communities and a few multi-family
apartment complexes. A large box store shopping center containing a Fresh Market as
well as a pedestrian-oriented shopping center, Thornebrooke Village Shopping Center
are located within the area of high residential density.
63
Building Density
Neither site had significantly high levels of building coverage, although
Downtown had the highest density overall. Building density values varied in Downtown
from 8% to 23% building coverage, with an overall 17% coverage. Millhopper values
remained relatively homogeneous, ranging from 10 to 13% building mass coverage and
an overall 11% building coverage.
Sidewalk Coverage
As a reminder, sidewalk coverage is calculated by measuring the total length of
the sidewalks divided by twice the length of the road centerlines. This due to the
assumption mentioned earlier, that the benefits of safety and convenience provided by
the sidewalk is most optimal when there is sidewalk on both sides of the street.
There is a high level of variability of sidewalk coverage between both sites. In
Downtown sidewalks run mostly around commercial and institutional buildings, but there
is a fair amount of sidewalk coverage throughout the Duckpond neighborhood in block
group 3 as well. Sidewalk coverage ranges from 37% to 70%, with an average coverage
of 56%. Sidewalks in Millhopper mostly run along main thoroughfares, such as NW 43rd
St, NW 23rd Ave, and NW 16th Ave, as well as along major shopping centers. There is
little to no sidewalk coverage in residential areas. Sidewalk coverage ranges from 19%
to 75%, with an average coverage of 20%. Despite the lack of sidewalks, there are
many residents who walk throughout the residential areas, many of them walking their
dogs. This can be attributed to slow vehicular traffic and abundance of tree shading
surrounding the single-family homes.
With a range of 19% to 75% sidewalk coverage for Millhopper, the average of
20% may appear too low. This is because sidewalks along the arterial roads are not
64
double-counted. Block group boundaries are defined by Census Blocks which are
defined by road centerlines. For instance, NW 16th Ave runs between block group 2 and
3. When calculating the sidewalk coverage for block group 2, the analysis will include
the sidewalk length from sidewalks along the southern edge of NW 16th Ave, even
though the sidewalk is technically within block group 3’s boundary.
Intersection Density
The intersection density for Downtown is at least twice as high compared to
Millhopper. The ratio of intersection points to site area in Downtown range from 0.49 to
0.61, with an overall score of 0.54. Intersection density in Millhopper ranges from 0.13
to 0.32, with an overall score of 0.22. A score of 1 would indicate 1 intersection per acre
and roughly 208 by 208-foot blocks.
This can be explained by looking at the street network of both sites. Downtown is
typified by a modified grid network throughout the whole site, with larger blocks along
University Ave and in the southeast Power District. These larger blocks contain many
institutional and industrial buildings such as City Hall, the Chamber of Commerce, JR
Kelly Generating Station, and the Rosa Parks Downtown bus terminal. Millhopper on
the other hand, has longer curved blocks, typical of suburban development with less
overall intersections. However, there is slightly more street connectivity in some of the
residential neighborhoods to the southeast.
Entropy Index (Land Use Mix)
The entropy index is a measure of the level of diversification of land uses. The
entropy index values were calculated on the Census Block level and then their scores
were averaged per block group.
65
Both Downtown and Millhopper had a variation of entropy index values among
the blocks, each having a single block group with a low level of land use diversity. In
both cases, these areas were predominantly single-family housing. The highest index
values in Millhopper are found in block groups 1 and 2, containing multiple shopping
centers and higher levels of residential density. However, high net residential density
was not always associated with a higher entropy index value for both sites. This may be
due to Downtown offering a greater total variety of land uses. Keep in mind the entropy
index does not take into account the difference in total number of available land uses, it
only measures the evenness of distribution. For instance, if one area has 3 land uses
distributed in a 30-30-30 arrangement and another area has 5 land uses distributed in
20-20-20-20-20 arrangement, they would each produce a value of 1. Overall, Downtown
had the highest average entropy index value of 0.46 in comparison to Millhopper’s 0.19.
Access to Transit
Given the larger single-family population of Millhopper, it was not surprising to
find there were fewer bus stops within the study area, totaling only 27 to Downtown’s
70. Within the Downtown study area, block group 3 (the Duckpond neighborhood) only
had one bus stop. However, all other groups had more bus stops per acre. All bus stops
in the Millhopper study area were along the two main arterial roads, with no penetration
into the neighborhoods or commercial centers. On the other hand, Downtown’s more
evenly distributed roadway system allowed for more opportunities for public transit to be
integrated. Aside from the main arterials of Main St and University Ave, popular
destinations for bus stops include SW 2nd Ave, SW 4th Ave, Depot Avenue, and 6th St.
Both 2nd and Depot Avenue have undergone major reconstruction to incorporate
Complete Street characteristics, such as newly paved sidewalks, street trees, clearly
66
marked bike lanes and medians in the form of either bidirectional turning lanes or palm
trees.
Destinations
The destinations indicator is a measure of proximity. Raster analysis was used in
attempts to account for both the quantity and gravity of destinations within each area.
The final product is a mean score of all the cell values ranging from 1 to 27. A cell value
of 27 would mean all destination types are within a half-mile from the cell. The
destinations indicator showcased the greatest distinction between the two sites. Mean
destination values for Downtown ranged from 12.28 to 19.66. Block group 1 was likely
the highest scoring area due to the proximity of food stores along University Avenue.
However, the scoring does not take into account the quality of the grocery, from whether
it is a small corner store neighborhood grocery to a 60,000-square foot Publix. The
Downtown area also has an abundance of religious institutions, but with a weight of 1,
this would not have as strong an influence as a grocery store, with a weight of 5.
Nevertheless, Downtown has a larger amount of destinations spread throughout the
study area, while most of the Millhopper points of interest are centrally located or along
NW 43rd and NW 16th Ave, segregated from single-housing. Millhopper’s mean scores
ranged from 4.33 to 8.70, with the highest mean value being located in the block group
with the highest building, commercial, and residential density.
Final Index
The final index is a composite of the standardized scores of all of the indicators,
whose values based on past studies are positively associated with higher levels of
physical walking activity (see Table 4-1 and Figure 4-1). There is no predetermined
specified range for the resulting index values, however, the higher the index value, the
67
more walkable a location. Index values were generated for each of the modified block
groups as well as for the overall sites. Downtown scores ranged from -0.16 to 0.19, with
the highest score in block group 1 and the lowest in block group 4. Millhopper scores
ranged from -0.36 to 0.46 with the highest score in block group 2.
68
Survey
In the section below, the results and findings will be presented for the intercept
surveys. The results will be organized by categorizing question results into 4 sections:
who is walking, where are they walking, why are they walking, and how did they get
there. Survey figures and graphs can be found in Appendix C. A total of 60 surveys
were collected for the Downtown site and 41 collected for Millhopper.
Who is Walking?
A majority of respondents were female for both sites, 64% in downtown and 73%
in Millhopper. However, there were major differences in the age of respondents. 51% of
respondents in Downtown were between the ages of 18 and 24 years of age, and 71%
were 34 years or younger. In contrast, 54% of respondents in Millhopper were 65+ and
62% over the age of 55. This could potentially affect the results and their interpretations
due to the different priorities and preferences of the two age groups. Respondents in
the Millhopper area were 93% Caucasian, while Downtown had more variation in the
racial makeup of its respondents, with 66% Caucasian and 20% African American or
Hispanic. Both ratios are relatively consistent with the racial profiles collected in the
2010 Census.
While almost all respondents in Millhopper were residents of Gainesville, and
most within the study area, 19% of Downtown respondents were from out of town. In
most cases, respondents from out of town were brought to Downtown by residents of
Gainesville. In this respect, Downtown was treated as a tourist attraction. Its uniform
architectural style, small blocks, central plaza (Bo Diddley Plaza), brick pavers, and
abundance of local non-chain restaurants provides an opportunity for residents to bring
their guests for a casual stroll before lunch or dinner. Aside from Depot Park,
69
Gainesville does not have many other strongly pedestrian-oriented areas within the city.
Although with the passage of the new land development code and an increasing trend
of development along North 13th Street and streetscaping improvements along NW 1st
Ave in Midtown, just north of the University, there may be evidence of pedestrian
oriented development in the coming years.
Where are They Walking?
The majority of respondents in both areas spend more than 21 minutes a day
walking, with more people falling under the category of 21 to 60 minutes a day. In
addition, 37% of Downtown respondents and 56% of Millhopper respondents reported
to walk for more than 10 continuous minutes 7 days a week. Such activity would
suggest some form of significant walking trip or destination is made on a daily basis.
Most walking activity of Downtown respondents occurs near home (32%), work
(25%), school (16%), and walking trails (16%). Meanwhile almost half of Millhopper
users’ trips occur near home (48%), shopping (21%), and work (14%). These responses
are reflective of the common demographics of each respondent group. The younger
Downtown respondents are more likely to be working or in school and therefore spend
more time on the UF campus or near their daily place of employment compared to the
large portion of retired Millhopper respondents. In addition, many of the retiree
communities are multi-family-style dwellings, all within walking distance to the two major
shopping centers and Thornebrooke Village Shopping Center which may explain the
higher level of activity near shopping areas.
Why are They Walking?
The top three reasons most people were walking in Downtown were for grocery,
restaurant, and no destination. ‘Grocery’ can include small grocery/food stores, large
70
box grocery stores such as Publix, or farmers’ markets. In the case of Downtown, all
respondents were referring to their trip to the farmers market that occurs every
Wednesday from 4-7pm. ‘No Destination’ refers to people walking for recreational
purposes including those walking their dogs. In contrast, respondents in the Millhopper
area had no destination, store, and restaurant as their top 3 options. ‘Store’ refers to
retail and services such as nail or hair salons. Food stores are excluded from the store
option. No Destination was likely the most popular choice in this area due to the high
number of retired, elderly residents who walk for their health or leisure. Additionally,
Downtown does not have a lot of centrally located retail as seen in Thornebrooke
Shopping Center. Instead Downtown has a variety of bars, restaurants, and civic
centers.
Respondents were asked what would make them likely to walk more than they
do now as well as provide any additional commentary on walking in the study areas or
how it might compare to their own neighborhood. The two most common responses in
both locations was a desire for more sidewalks and more destinations close by their
home. Millhopper respondents were more concerned with the quality of the sidewalk
surface, likely because of the larger elderly population whom could be more vulnerable
to tripping hazards. For Downtown, destinations often referred to retail and grocery
stores. While some Millhopper respondents also said a they would like to see more
shops, there was no desire for another grocery store. This is due to the location of both
a Publix and Fresh Market within the study area although it could possibly be more
beneficial to spread the super markets further apart. Both stores are located within large
71
shopping centers, set far back from the street, fronted by large parking lots and with
their backs to residential complexes or another parking lot.
One long-time resident of Downtown claims Gainesville has experienced a
diminishing number of points of interest over the last 30 years including the loss of the
post office, the hospital where Innovation Square now sits, and the closing of the
Gainesville Co-Op grocery store. The resident also claimed there are too few residents
to support business in the area alone and more residents would make pedestrians feel
safer throughout the day. Most other responses were related to physical infrastructure
and street furniture including greater building density, and more crosswalks, street
lighting, shade trees, and walking trails.
Most people from both areas feel Downtown and Millhopper are very safe areas,
although there were several female respondents in Downtown who claimed to feel
unsafe walking around at night and believes there should be more street lighting and/or
some form of police or security patrol. This concern was not shared in the Millhopper
area. This may be due to the large amount of single-family residences spread
throughout the area, providing ‘eyes on the street’ compared to central Downtown’s
many bars and clubs as well as some vacant buildings within the developing Innovation
Square and in southern Downtown along Main St approaching Depot park. Here the
buildings are spread apart, with little commercial activity, especially at nighttime hours.
Most of the respondents in Millhopper enjoy spending time in the Thornebrooke
Shopping Center, even just to people watch. But north of Thornebrooke or to the west of
NW 43rd St, many respondents claimed you’re unlikely to see any people walking. This
particular section of the street is characterized by various commercial or financial
72
institutions divided by curb cuts which break up the sidewalk network and non-
connecting parking lots.
How Did They Get There?
While Downtown is a popular destination for walking, 57% of people traveled
there by automobile (either driver or passenger), 32% by walking,7% by bus, and only
5% by other means of transportation such as bicycle or scooter. In contrast, 66% of
respondents in Millhopper arrived there by walking, 34% by automobile, and 0% by any
other form of transit. These findings suggest there may not be enough residential
density to support the downtown area. To further add, Downtown’s census population
density of 7.76 people per acre is low for most city centers. This may be further
supported by the fact that 80% of Millhopper respondents came from home compared to
Downtown’s 63%. However, it is not to say that a large number of home-based trips is
the ideal for increasing walking, a successful walkable environment should also
encourage intermediate trips, such as stopping at a coffeeshop on the way to work or
errand-based trips like going to the grocery store or doctor’s office on the way home
from work.
Most Downtown users listed unpleasant weather, not enough destinations, and
too busy as the primary reasons for not walking more than they do currently. Time
played a heavier role in the responses of those in Millhopper, with unpleasant weather
and health reasons falling in behind. Only 5% of responses in Millhopper complained of
not enough destinations and only 10% of respondents from both groups felt unsafe.
73
Table 4-1. Walkability index results
Downtown Net Res Density
Building Density
Sidewalk Coverage
Intersection Density
Entropy Index
Access to Transit
Destinations Final Index Values
Group 1 5.21 0.12 0.37 0.60 0.71 0.10 19.66 Group 2 4.01 0.23 0.68 0.49 0.43 0.17 16.2 Group 3 6.58 0.14 0.70 0.61 0.09 0.01 12.28 Group 4 5.35 0.08 0.42 0.56 0.69 0.12 14.24 Overall 4.83 0.17 0.56 0.54 0.46 0.12 15.75 ZGroup1 -0.07 -0.35 -1.00 0.64 0.79 0.00 1.29 0.19 ZGroup2 -1.22 1.38 0.80 -1.38 -0.17 1.05 0.19 0.09 ZGroup3 1.23 -0.04 0.92 0.83 -1.35 -1.35 -1.05 -0.12 ZGroup4 0.06 -0.99 -0.71 -0.09 0.73 0.30 -0.43 -0.16 Millhopper Net Res
Density Building Density
Sidewalk Coverage
Intersection Density
Entropy Index
Access to Transit
Destinations Final Index Values
Group 1 1.08 0.10 0.38 0.20 0.41 0.04 6.91 Group 2 4.16 0.13 0.75 0.13 0.37 0.04 8.70 Group 3 3.32 0.10 0.19 0.28 0.06 0.05 7.77 Group 4 2.50 0.10 0.64 0.32 0.14 0.05 4.33 Overall 2.77 0.11 0.19 0.22 0.19 0.05 7.13 ZGroup1 -1.28 -0.50 -0.43 -0.38 0.96 -0.87 -0.01 -0.36 ZGroup2 1.06 1.50 1.03 -1.21 0.73 -0.87 0.94 0.46 ZGroup3 0.42 -0.50 -1.19 0.56 -1.08 0.87 0.45 -0.07 ZGroup4 -0.20 -0.50 0.59 1.03 -0.61 0.87 -1.38 -0.03
74
Figure 4-1. Walkability index results map
75
CHAPTER 5 DISCUSSION
The Index
Although comparable on some of the individual block levels, all average
indicators scores for the Downtown study area had scores indicating higher walkability.
Block group 1 in Downtown and block group 2 in Millhopper had the highest index
values, sharing commonalities in a diverse mix of land uses, multi-family housing, and
medium to high scores for destinations in relation to other block groups within the study
area. Block group 1 was especially influenced by its higher access to points of interest.
The lowest scoring block groups were 4 in Downtown and 1 in Millhopper. In Millhopper
Block Group 1, residential density and land use mix were the two largest contributing
factors to the final index score. While block group 1 did have the highest land use mix, it
did not have the highest destination score or a high residential density to support other
types of development. The highest land use mix value can also be attributed to the
vacant residential parcels which is listed as a separate land use. Additionally, it had very
low levels of street connectivity, where different uses were not interconnected and only
accessible to both pedestrian and vehicles by curb cuts along the main arterials of NW
43rd and NW 23rd Ave. Block group 4 in Downtown is the location of the Porter’s
neighborhood has low levels of building density and sidewalk coverage as well as high
levels of vacant residential which may contribute to a higher entropy score, but a low
generator for pedestrian activity.
The indicators seemed to have a positive association with one another, in which
if a site scored highly in one, it would likely score high in another indicator. However,
there were no instances in which the block groups that received either the highest or
76
lowest index values, scored the highest or lowest across all indicators. This could mean
scoring poorly in one indicator does not mean an area will guarantee a low level of
walkability. In some cases, characteristics of a neighborhood could overcome certain
barriers to walkability where pedestrian infrastructure may be lacking. For instance, a
lack of sidewalks may not be an issue if an area has a dense network of narrow streets
and frequent speed bumps, causing vehicles passing through to drive slow.
Overall, the street network plays a vital role in influencing how people and
different land uses interact with one another. The street network is a common factor
among all indicators in how oriented they are towards creating accessible, pedestrian
friendly environments. For instance, a more densely connected street network provides
a higher number of intersections, offers more space for sidewalks, supports higher
levels of building density which generates opportunities for new land use types, and
creates more route choices and shortens the distance between destinations.
The Millhopper street network functions similar to that of the early 20th century
American suburbs, where there is a hierarchical road network and, although perhaps
not to this extreme, divides neighborhoods and other activity centers into ‘pods.’ Each
pod then has its own use – such as a shopping center, a business park, a school, or
private residential community – separate from one another. Each of these areas is then
accessible by an individual collector street or curb cut onto the main arterial road
(Adams & Tisdell, 2013). This can be seen in most of the residential neighborhoods to
the west and north in the Millhopper area. While there may be some connectivity within
the neighborhood itself, those traveling within cannot go beyond the extent of the
neighborhood boundary without entering onto one of the main arterials.
77
Off-road trails have the potential to overcome this constraint by creating more
direct pedestrian or bike pathways through these pod-style developments where
vehicles may not be able to travel and are forced to travel twice or three times the
distance. However, these pathways can be difficult to create as they often pass through
privately owned properties and require access to additional public right of way or the
purchase of private utility agreements.
Walk score incorporates similar measures of pedestrian oriented design, such as
block length and intersection density. Walk Score also weights their destinations by their
distance from a point of origin. In contrast, the index performed in this research weights
the destinations by their gravity. Their gravity is the degree to how often a point of
interest would attract walkers. The researcher believes this method to be more
appropriate for predicting where pedestrians are more likely to walk and therefore,
produces a more accurate assessment of walkability. Although the weights in this
research were grounded in past literature as well as results from the intercept survey.
For applicability on a broader scale, it may be more appropriate to determine the gravity
of destinations by existing federal documents, such as the National Household Travel
Survey or other reports produced by the Bureau of Transportation Statistics.
The Survey
Overall, respondents from both locations shared a desire for closer destinations,
more sidewalks, and street furniture such as shade trees, street lights, and benches. In
addition, there was an exaggeration of the distribution of the number of young or elderly
respondents compared to census data for both study areas. Nonetheless Downtown
possesses a relatively high concentration of young adults under the age of 30 while
Millhopper has a notable larger concentration of adults 55 and above. These
78
demographic differences may result in bias answers due to variation in lifestyle needs
and preferences as well as reflect the type of residential development in the area. Some
of these personal preferences and concerns were reflected in the survey results, such
as the more senior members’ need for flat and smooth walking surfaces. By only
selecting individuals who were already walking, this research recognizes the views of
the residents in the surrounding community may not be reflected. Additionally, there
may not be many people walking in areas with poor pedestrian infrastructure or places
of interest where people may gather. As a result, the survey may only collect data from
people walking in areas that are centers of commercial activity or have higher levels of
pedestrian-supportive street design.
A large portion of the respondents in Millhopper were 55+ years of age and many
respondents enjoyed the proximity of the nearby shopping centers, feeling all their basic
needs were met. For those who did not live nearby and drove to the location, many
enjoyed visiting the Thornebrooke Village Shopping center to people watch and window
shop. Downtown residents often were walking for the purpose of purchasing food in a
social setting. This includes both restaurants and the farmer’s market, where many
families and couples can be found sitting around Bo Diddley Plaza. On non-farmers’
market days people still gathered in Bo Diddley to eat meals from the surrounding food
stands and coffee shops. Downtown could benefit from more functional commercial
uses, such as a large chain grocery store as seen in the Millhopper sites. There are
likely no such commercial establishments at this time because Downtown does not
have as large of a catchment area as Millhopper with its abundance of residential
properties.
79
Exercise and recreation were the primary reasons for walking in both site areas,
while walking for transport was not found to be a major reason for walking on either site.
Additionally, convenience was found to be tied for the second-most popular reason for
walking in downtown, but was not a popular reason in Millhopper. This may suggest
Downtown has a more connected street network system making it easier to travel for
non-leisure purposes. Lastly, automobile traffic posed as a barrier to walkability as a
safety concern in both study areas, but may have been more relevant in Millhopper due
to the two five-lane highways running through the center of the study area. Lack of
adequate street lighting or police presence also posed as a safety concern for some
women in Downtown.
Limitations
Walkability Index
Overall. As with most GIS-related analysis, the quality of the results is
dependent on the accuracy of the data used and its sources.
Entropy Index. Although an uneven mix of land uses may pose some detriment
to walking, the entropy calculations do not consider the specific composition of all land
use types within a given community. For instance, one area could have an even
distribution of 3 land use types, and another 6, but still receive the same index value of
1. Broad generalization of land uses may also limit the depth of analysis that can be
explored between certain land use types and walking (Cerin et al., 2006).
Limits of Scope. The selected walkability indicators do not consider parking lots
or bike lanes. The index also does not distinguish between factors which may influence
work and non-work walking trips differently.
80
Survey
Initial surveys were conducted in the month of December and January. As a
result, there was not an accurate representation of the amount of people normally
walking, due to holiday travel and cold weather. Additionally, during this time of year the
sunset begins as early as 5-5:30pm. This may cause some pedestrians to not walk
around later in the day as they might during the spring and summer months when the
sun sets closer to 8-8:30pm.
On the Millhopper site, there are two shopping centers, both of which do not
allow solicitation. As a result, surveys could only be conducted around the perimeter
sidewalks of these centers.
Recommendations
Index
In this research, there were not enough quantitative results to run any in-depth
regression analysis. The model could be expanded to a larger city scale by using Model
Builder to provide more results to examine any trends among the indicators.
Survey
For questions regarding where respondents live or work, instead of simply asking
where respondents live, the researcher could show the respondent a reference map of
the study area in question and ask if they live or work within its boundaries. This method
could provide more immediate information regarding whether the person is walking near
their personal neighborhood or if they live within walking distance to their work or shops.
Additionally, survey responses could then be analyzed based upon the responses of
those who live in the study area and those who live elsewhere in the city.
81
The survey used in this research does ask about transportation choice regarding
their arrival to the study area in question. However, it may also be more enlightening to
inquire what mode of transportation respondents use the most on weekdays and what
mode of transportation they use the most on weekends. This could provide further
information on where and when their usual walking trips are occurring and how
supportive walkers are of other forms of alternative transportation such as bicycle, bus,
or car share.
It may also be beneficial to ask how far did respondents travel from their last
destination and by what mode. It may also be beneficial to ask how far respondents
usually walk in a day, however, personal perceptions of distance may be highly skewed.
An example reference distance most respondents would likely be familiar with should be
provided if the researcher chooses to screen for this question.
Future Research
It would be interesting to explore how walkability may differ among different
socioeconomic groups. For instance, the urban poor often live in more compact areas
(with higher population densities) because they have lower rates of motorization
(Marquet & Miralles-Guasch, 2014). In addition, although the lower income groups often
walk more than those of higher brackets, they have the lowest quality of walking
environments (APHA, 2010).
82
CHAPTER 6 CONCLUSION
In conclusion, areas with high residential density, intersection density, a diversity
in land uses and proximity to popular destinations tended to have higher levels of
potential walkability. However, as reflected upon in earlier literature, there was no
indication of one factor having the greatest influence over the walkability of the area.
Instead, all the indicators are related through their connection with the street, how it is
designed and in what pattern it travels. Downtown scored the highest among the
indicators of the walkability index with the highest scoring block group being block group
1. Meanwhile Millhopper’s highest scoring block group was group 2. The area of highest
walkability had dense street network, higher commercial activity, and better accessibility
to destinations that are frequently visited. Downtown's potential higher walkability is
most likely due to its dense street network and variety of land uses. For the survey
portion, most respondents stated they walked for exercise or recreational purposes.
Respondents listed sidewalks, more destinations near home, and shade trees for a
more comfortable walking environment would make them more likely to walk.
After considering the implications of this research, the City of Gainesville would
benefit from incentivizing street connections between residential neighborhoods and
other developments. It will encourage higher rates of connectivity and force less people
onto arterial roads. The researcher also encourages further efforts to increase the
number of off-road pedestrian and bike trails in areas where street connections may not
be feasible. Currently, Gainesville’s new hybrid form-based code uses street-level
infrastructure and aesthetic requirements such as, open space (open space is not
required in Gainesville but encouraged), street lights, and shading, which could benefit
83
walkability in many urban neighborhoods. Areas of the City where the new form-based
code does not apply could be improved by applying the urban transect zone
classifications, found in the form-based code, throughout city limits and/or by providing
incentives for increased street network connectivity and providing discounted fees for
the development of essential uses such as a grocery store or pharmacy in an area
where one is not within a half mile.
84
APPENDIX A MORPHOLOGY FEATURES: STREET, BLOCK, AND FIGURE GROUND
Street Network
Figure A-1. Downtown street network and Millhopper street network
85
Blocks
Figure A-2. Downtown blocks and Millhopper blocks
86
Block Dimensions
Figure A-3. Downtown block dimensions
87
Figure A-4. Millhopper block dimensions
88
Figure-Ground
Figure A-5. Downtown and Millhopper figure grounds
89
Block/Figure Ground Overlay
Figure A-6. Downtown and Millhopper figure ground overlays
90
APPENDIX B WALKABILITY INDEX MAPS
General Site Locations
Figure B-1. General site locations
91
Zoning Maps
Figure B-2. Downtown zoning map
92
Figure B-3. Millhopper zoning map
93
Modified Block Groups
The pictures below depict the modified block groups used I the analysis. The cross-hatched areas are the original
2010 Census Block Groups that were trimmed to allow for a more equal comparison of sites.
Figure B-4. Modified block groups
94
Destinations Result
Figure B-5. Destinations heat map
95
APPENDIX C SURVEY DOCUMENTS
Informed Consent Form
Figure C-1. Informed consent form
96
Intercept Survey
Figure C-2. Intercept survey form
97
Recruitment Script
Figure C-3. Recruitment script
98
Survey Results
The attached reports are exported directly from the Qualtrics survey software
reports tool.
99
Downtown
Walkability Survey - Downtown
Q - What is the purpose of your trip today?
100
Q - What is the purpose of your trip (continued)?
Credit Union
Theater
Theater
Window Shopping
101
Q - How did you get here?
102
Q - Where did you come from?
103
Q - Where did you come from (continued)?
Where did you come from (continued)?
School
UF
School
Airport
Restaurant
Restaurant
Reitz
UF Campus
Family members
Hotel
Hotel
104
Q - How much time do you spend walking each day?
105
Q - On average how many days a week do you walk for more than 10 continuous minutes?
106
Q7 - In what areas do you typically walk?
107
Q11 - When you go out walking, where do you go? (check all that apply)
108
Q12 - When you go out walking, where do you go (continued)?
When you go out walking, where do you go (continued)?
Parking
N/A
N/A
Bars
Mountains
109
Q13 - Why do you walk? (check all that apply)
110
Q14 - Why do you walk (continued)?
Why do you walk (continued)?
Do not Walk
Physical Therapy
When I have no ride
N/A
To get to work
111
Q - What keeps you from walking more than you do now?
112
Q - Is there anything that would make you likely to walk more? For example, more shade trees, more sidewalks, smaller blocks, more crosswalks, narrow streets, more bus stops, more restaurants, etc... Answer Category
More bus stops on campus Infrastructure
If city amenities were closer Infrastructure
More crosswalks and more convenient locations. A more aesthetically pleasing.
Infrastructure
more streetlights so that I feel safer Infrastructure
More crosswalks Infrastructure
shade trees, concerned with too much car traffic Infrastructure
More sidewalks/ pedestrian crossings. Better feeling of safety by getting rid of panhandlers.
Infrastructure
more sidewalks and public art Infrastructure
Closer grocery shopping and stores Infrastructure
Grocery stores close by Infrastructure
Smaller blocks, wider sidewalks with more shade, more destinations
Infrastructure
Smaller blocks, more places to visit, prettier paths to walk on Infrastructure
Wider crosswalks Infrastructure
More streetlights Infrastructure
sidewalks, more shops, other means of transportation Infrastructure
More sidewalks infrastructure
If there were more pleasant waking areas (i.e. nicer sidewalks, crosswalks, and greater accessibility between locations).
Infrastructure
More benches and shopping Infrastructure
Well designed public spaces, art, unique shopping, well lit areas, and safety insured (security)
Infrastructure
more destinations Infrastructure
More places to walk, such as more trails or places that are free Infrastructure
Closer destinations, more shading, more streetlighting, feel safer.
Infrastructure
Closer destinations, more shading, greater feeling of safety, more streetlights
Infrastructure
113
More public restrooms, more seating/benches Infrastructure
Clothing stores, more shops like the record store Infrastructure
More windows on buildings, more density, smaller blocks Infrastructure
More building density and more eyes on the street (windows) Infrastructure
Want more bars Infrastructure
More sidewalks Infrastructure
Crosswalks and more streetlighting Infrastructure
Shade trees, more destinations that cater to entertainment and shopping
Infrastructure
More sidewalks and shade Infrastructure
Proximity of shops, bars and restaurants. Need more parking Downtown.
Infrastructure
More trees and lighting Infrastructure
More sidewalks Infrastructure
Main post office for Gainesville has left and become the hippodrome, the hospital left and is now innovation square. However there are a lot of restaurants in the area, some of the restaurants have left and there has gradually been a diminishing of points of interest over time making the area less convenient. The area is also missing a food store within walking distance. There are also too few residence to support business in the area. More residents make the area safer for pedestrians. Do not fix the environment by adding fancy sidewalks but by having usable destinations. Parking garage is also obstructive to pedestrian environment, all concrete walls. It needs a pedestrian edge.
Infrastructure
More sidewalks and bike lanes Infrastructure
More shading to provide cooler areas to walk Infrastructure
More crosswalks by my apartment, more sidewalks on local roads
Infrastructure
More shade, more small quick crosswalks, more sidewalks. Infrastructure
More sidewalks Infrastructure
Walking trails near my home Infrastructure
Would like more shade trees along SW 2nd Ave. Also, I would walk Downtown more if there were clothing stores there.
Infrastructure
If there were a larger Downtown area Infrastructure
114
Better shopping areas and walking trails Infrastructure
More attractive destinations such as bars and clubs. Infrastructure
more shade trees, more sidewalks, smaller blocks, more crosswalks, narrow streets, more bus stops, better transit, and more street furniture
Infrastructure
not really, Downtown is a nice place to walk No
nope no
Everything's fine No
No problems No
I'd walk more if my car broke Personal
If my car broke Personal
If my scooter broke Personal
More internal motivation Personal
Needs to be more people who respect pedestrians. Personal
more security for late evening walks Security
Nothing, only thing that usually stops me is the weather. Weather
Good weather would make me walk Weather
115
116
Q - Is there anything else you'd like to say about walking in your neighborhood or this area?
Answer Category
More inclined to walk if they extended bike lanes fro 8th Ave to Depot Park
Bike lanes
Downtown is very nice and clean. Clean
Downtown is nice, convenient, and well kept Clean
Best to walk where things are close and no more than 30 minutes away by walking. Proximity is very important
Distance
Downtown has a lot of activities Distance
Nope N/a
nope N/a
nope N/a
nope N/a
nope N/a
nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
No problems N/a
Nope N/a
nope N/a
Nope N/a
nope N/a
Feel safe walking in Downtown. Parking can be a deterrent to come Downtown. It limits the places you can walk to. Most places Downtown are clustered together. However, I am deterred by the homeless activity Downtown. I'd like to see more walking around Gainesville in general. In general, Floridians are not walkers
Other
117
because it is too hot. Planners and policymakers need to make the environment more comfortable for the people.
we've got a lot of progress to make in Gainesville. Bogota is a very walkable city.
Other
Gainesville is a great area that has very nice walking spots Other
I like walking around to get my vitamin D Other
Very seasonal area. Other
I live in the suburbs which is not very walkable Other
Neighborhood I live in is not walking friendly Other
It's a very nice place to walk Other
Might get shot in the neighborhood I live in Other
Not that many sidewalks at home so I have to drive everywhere Other
Downtown is great Other
It's a very relaxing area that gives you peace of mind Other
There's nowhere to leisurely walk by my apartment Other
It's good! Other
I love it, walking is much better than driving Other
I love the area. Other
It's really quiet. Other
My area in Gainesville where my house is located is nearby a playground frequently occupied by parents and kids which creates a fun and friendly environment.
Park space
Difficult to find parking at night Parking
the area is very friendly People
Do not enjoy panhandlers People
Do not enjoy panhandling People
Surprised how many people are out, it is a very lively place People
Everyone is friendly People
sometimes feel unsafe at night Downtown Safety
More street lights for safety Safety
118
At home in South Florida, it is too dark and I feel unsafe. Also, as a female I feel more unsafe.
Safety
I usually feel safe with lights around but sometimes I feel sketched out as a woman
Safety
Smoother surface walking Sidewalks
Walking in the rain in Downtown is unpleasant because of uneven sidewalks allowing for puddles to form. Everything on the west side of Gainesville is too far away from each other for walking
Sidewalks and distance
Would like to see more walking trails. Much more walkable than where I used to live in South Florida.
Walking trails
The community where I live (no Downtown) has walking trails which is a huge bonus. Community created them. Commute with nature. The residents ave rambling rights with two separate communities. About 200 acres and 30 people.
Walking trails
119
Q - What is your gender?
120
Q - What is your age?
121
Q - To which race do you most identify with? (optional)
122
Q21 - Are you a resident of Gainesville, Fl?
123
Q - In what neighborhood? (optional)
In what neighborhood? (optional)
Downtown
NW Gainesville
Stephen Foster
Stephen Foster
West of I-75
Sorority Row
Sorority Row
West of Campus, 35th St
Pleasant Street
NW Gainesville
Duckpond
UF Campus
UF Campus
By Oaks Mall
Downtown
Downtown
Downtown
Boulware Springs
Downtown
Pleasant St
Pleasant St
Pavilion on 62nd
University Club
University Commons
39th Street
124
Behind firestation
13th
Pineridge
Downtown
Newberry Road
Northwest, near Santa Fe
Florida Park
Duckpond
Southside
Downtown
West Gainesville
Wildflower
Apartment Complex
Near Campus (UF)
SW Apartments
Downtown
Downtown
The Duck Pond
Park Avenue
125
126
Q - Would you consider yourself more knowledgeable than the average person in any of the following fields: urban planning, architecture, urban design, or landscape architecture?
127
Q - Where do you work?
128
Q - List Here
List Here
Farm in Alachua
self-employed
Silver Springs State Park
Yes
BUDA design agency Downtown
Chuy's
Chuy's
self-employed
self-employed yoga teacher
Chick Fil A
Starbucks @ UF
yoga studio
34th & University
Mojos in Downtown
Waitress Sushi Matsuri
Elementary School Dance Coach
UF Mover Guys
Childcare
Graphic design and marketing
Various clubs Downtown
Scruggs and Carmichael
Alachua County Courthouse
Self employed
Near Taco Bell
Kimley-Horn
129
N/A
Mobiquity
Part time - helps people around the neighborhood
Babysitter
Vet School
UF Vet Student
Eaton Lighting Solutions
UF
Grad Student Fellow
Palm Beach Central High School
VA Hospital
Museum of Natural History
130
Millhopper
Walkability Survey - Millhopper
Q - What is the purpose of your trip today?
131
Q - What is the purpose of your trip (continued)?
What is the purpose of your trip (continued)?
Bus Stop
Credit Union
clubhouse
Friends house
Credit Union
Bus Stop
132
Q - How did you get here?
133
Q - How did you get here (continued)?
No answers
134
Q - Where did you come from?
135
Q4 - Where did you come from (continued)?
Restaurant
restaurant
136
Q - How much time do you spend walking each day?
137
Q - On average how many days a week do you walk for more than 10 continuous minutes?
138
Q - In what areas do you typically walk?
139
Q10 - In what areas do you typically walk (continued)?
UF Campus
Gym
Golf Course
140
Q - When you go out walking, where do you go? (check all that apply)
141
Q - When you go out walking, where do you go (continued)?
When you go out walking, where do you go (continued)?
around the neighborhood
looking for feeders for fish tank
142
Q - Why do you walk? (check all that apply)
143
Q - Why do you walk (continued)?
Yard Work
Travel to Work
walk with child
144
Q - What keeps you from walking more than you do now?
145
Q - Is there anything that would make you likely to walk more? For example, more shade trees, more sidewalks, smaller blocks, more crosswalks, narrow streets, more bus stops, more restaurants, etc... Answer Category
More people out, safe sidewalks along roads, more destinations close by. Cars will still go through lights, no one stops for pedestrians
Infrastructure
More sidewalks and bars Infrastructure
More sidewalks, bars, and shade trees Infrastructure
Living in an area where destinations are closer to my home Infrastructure
More restaurants, more streetlights, more sidewalks, partner to walk with
Infrastructure
Sidewalks, shade trees, and grassy areas for my dog Infrastructure
Sidewalks, crosswalks, destinations within close proximity to each other (close to each other)
Infrastructure
Better roadways and sidewalks, there are a lot of tripping hazards. Infrastructure
More destinations, wider sidewalks, and more lighting Infrastructure
Better shops, more frequent bus stops, smoother sidewalks Infrastructure
More shops, more frequent bus stops, fix cracks in sidewalks Infrastructure
More shops, more frequent bus stops, fix cracks in sidewalks and roadway
Infrastructure
More shops, more frequent bus stops, fix cracks in sidewalks and roads
Infrastructure
More sidewalks Infrastructure
More crosswalks Infrastructure
Higher density, less traffic, more shade Infrastructure
Smaller Streets, higher density, shade trees, and traffic calming measures
Infrastructure
Need more amenities Infrastructure
More benches and more crosswalks on 43rd and near fast food establishments
Infrastructure
More shade trees Infrastructure
More sidewalks, greater feeling of safety Infrastructure
Safer crosswalks Infrastructure
146
More shade, soft sidewalks, safer crosswalks, and safer drivers Infrastructure
Reduce noise from vehicle traffic Infrastructure
Prettier landscaping makes walking more enjoyable Landscape
New scenery, new water features Landscape
Nope, I walk enough No
I like walking in my neighborhood. If anything, i'll walk more when I see a friend who is walking their dog.
No
Nope No
Nope No
Not around here No
Nope No
Less traffic on the road. Pedestrians are second-hand citizens Other
Walking groups Other
Time an if body feels healthy Personal
More single men walking in my age group Personal
Would walk more if I were healthier Personal
Another dog to walk Personal
Good looking ladies walking Personal
More time Personal
147
148
Q - Is there anything else you'd like to say about walking in your neighborhood or this area?
Answer Category
University/College Park area has more destinations within walking distance and smaller streets in comparison to the Millhopper area
Distance
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
Nope N/a
I appreciate having a lot of views of nature Nature
Great spot to walk in. Love the trees and lots of other nature to look at.
Nature
The area is perfect. The trees and landscaping are very pleasant and therapeutic. The nature in the area helps clear the mind.
Nature
This area is wonderful. Everything is centrally located. Meets all my needs.
Other
Good area to walk. Used to walk down to park on 8th Other
Very safe, visually pleasant, very flat area, everything is conveniently nearby
Other
Easily tire over the same places over and over Other
Very pleasant area Other
The area is pedestrian friendly Other
Perfect, everything I need is here Other
Wish people would clean up after their dogs Other
Lack of respect for pedestrians. Downtown or around campus is a bit better. Walking on campus, in general, is nicer. There is little chance of seeing someone walk in the suburbs north of thronebrooke.
People
Neighbors and restaurants are great. Friendly surrounding store staff People
149
Very enjoyable, nice neighbors People
Everyone in the neighborhood knows each other. Community is the key to activating walking. Additionally, most people in this neighborhood have similar lifestyles
People
Our neighborhood better in Fl Park than Millhopper Area People
The area is pretty safe to walk in (Millhopper & 34th) Safety
Feel safe; you run into people you know often; good place to walk Safety
Pretty safe Safety
Feel safe Safety
Area feels safe Safety
Feel safe Safety
Feel safe Safety
Neighborhood feels safe Safety
Nope. The area is pretty safe with a lot of sidewalks and crosswalks Safety
Like millhopper, pretty safe Safety
Very safe Safety
Make area more safe for children Safety
Like Thornebrooke shopping centers music. Good place to wander before food
Shopping
Everybody is out when it is warm around thornebrooke shopping center - window shopping and eating at Chopstix.
Shopping
150
151
Q - What is your gender?
152
Q - What is your age?
153
Q - To which race do you most identify with? (optional)
154
Q - Are you a resident of Gainesville, Fl?
155
Q - In what neighborhood? (optional)
In what neighborhood? (optional)
NW Gainesville
NW Gainesville (28th Lane)
NW Gainesville
NW Gainesville
middle of the country
Northwest Gainesville
Magnolia Parke Area (NW 39th Ave)
Varsity House (By SW 20th Ave)
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Pavilion on 62nd
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Millhopper Pines
Pebble Creek (North Millhopper)
Palm View Estates (NW Gainesville)
Millhopper Pines
Palm view Estates (NW Millhopper)
156
Millhopper Pines
Landmark Woods
College Park
College Park
The Courtyards (in Millhopper)
Pebble Creek Villas
Northwest Gainesville
Northwest Millhopper
Rock Creek Subdivision
courtyards
Northwest Gainesville/Millhopper
Northwest Gainesville
Northwest Gainesville
157
Q - Would you consider yourself more knowledgeable than the average person in any of the following fields: urban planning, architecture, urban design, or landscape architecture?
158
Q - Where do you work?
159
Q - List Here
160
LIST OF REFERENCES
Adams, D., & Tisdell, S. (2013). Shaping places: urban planning, design, and development. New York: Routledge.
Agampatian, R. (2014, April). Using GIS to measure walkability: A Case STudy in New
York. Stockholm, Sweden: Royal Institute of Technology (KTH). American Public Health Association. (2010). Fact Sheets: Transportation - Active
Transportation. Retrieved from APHA: https://www.apha.org/~/media/files/pdf/topics/transport/apha_active_transportation_fact_sheet_2010.ashx
American Public Health Association. (2014). Fact Sheets: Transportation -
Transportation and Public Health. Retrieved from APHA: https://www.apha.org/publications-and-periodicals/fact-sheets
Bradshaw, C. (1993). Creating -- And Using -- A Rating System For Neighborhood
Walkability Towards An Agenda For "Local Heroes". 14th Interenational Pedestrian Conference. Boulder, Colorado.
Browner, S. (2013). The Post-World War II Suburb in the United States. The First-Year
Papers (2010 - present). Trinity College Digital Repository, Hartford, CT. http://digitalrepository.trincoll.edu/fypapers/46
Cambra, P. J. (2012, October). Pedestrian accesibility and attractiveness: indicators for
walkability assessment (doctoral dissertation). Lisbon, Portugal: Instituto Superior Técnico.
Cerin, E., Leslie, E., du Toit, L., Owen, N., & Frank D., L. (2006, September).
Destinations that matter: Associations with walking for transport. Health & Place, 13(3), 713-724. doi:https://doi.org/10.1016/j.healthplace.2006.11.002
Cervero, R., & Kockelman, K. (1997). Travel demand and the 3Ds: density, diversity,
and design. Transportation Research Part D: Transport and Environment, 2(3), 199-219.
City of Gainesville. (2017). Article IV zoning. Land development code (30). Retrieved
from http://www.cityofgainesville.org/Portals/0/plan/Form%20Based%20Code%20Final/Final%20Ordinance/Article%20IV_20170720.pdf
Ewing, R., & Cervero, R. (2010). Travel and the built environment: a meta-analysis.
Journal of the American Planning Association, 76(3), 265-294. Retrieved from http://dx.doi.org/10.1080/01944361003766766
161
Ewing, R., & Handy, S. (2009). Measuring the unmeasurable: urban design qualities related to walkability. Journal of Urban Design, 65-84. doi:10.1080/13574800802451155
Forsyth, A., & Southworth, M. (2008). CIties afoot -- pedestrians, walkability, and urban
design. Journal of Urban Design, 1-3. Frank, L. D., Delvin, A., Johnstone, S., & Loon, J. (2010, October). Neighborhood
Design, Travel, and Health in Metro Vancouver: Using a Walkability Index . Vancouver: University of British Columbia. Retrieved from http://act-trans.ubc.ca/files/2011/06/WalkReport_ExecSum_Oct2010_HighRes.pdf
Harruff, R. C., Avery, A., & Alter-Pandya, A. S. (1998). Analysis of circumstances and
injuries in 217 pedestrian traffic fatalities. Accident Analysis & Prevention, 30(1), 11-20.
Hsiao, S., Lu, J., Sterling, J., & Weatherford, M. (1997). Use of geographic information
system for analysis of transit pedestrian access. Transportation Research Record: Journal of the Transportation Research Board, (1604), 50-59.
Institute of Transportation Engineers. (2010). Designing Walkable Urban
Thoroughfares: A Context Sensitive Approach. Washington, DC: Institute of Transportation Engineers.
Koschinsky, J., & Talen, E. (2017). How walkable is walker's paradise? Environment
and Planning B: Urban Analytics and City Science, 44(2), 343-363. Leslie, E., Coffee, N., Frank, L., Owen, N., Bauman, A., & Graeme, H. (2005).
Walkability of local communities: Using geographic information systems to objectively assess relevant environmental attributes. Health & Place, 111-122.
Livi, A. D., & Clifton, K. J. (2015, February 03). Issues and Methods in Capturing
Pedestrian Behaviors Attitudes and Perceptions: Experiences With a Community-Based Walkability Survey. Retrieved from ResearchGate: https://www.researchgate.net/publication/267945519_issues_and_methods_in_capturing_pedestrian_behaviors_attitudes_and_perceptions_experiences_with_a_community-based_walkability_survey
Litman, T. A. (2017). Economic value of walkability. Victoria Transport Policy Institute. Lo, R. H. (2009). Walkability: what is it? Journal of Urbanism: International Research on
Placemaking and Urban Sustainability, 145-166. Marquet, O., & Miralles-Gusach, C. (2014). The Walkable city and the immportance of
the proximity environments for Barcelona's everyday mobility. Cities, 42, 258-266.
162
McCormack, G. R., & Shiell, A. (2011). In search of casuality: a systematic review of the
relationship between the built environment and physical activity among adults. International Journal of Behavioral Nutrition and Physical Activity, 8(125). doi:doi:10.1186/1479-5868-8-125
Neto, L. (2015). The Walkability Index: Assessing the built environment and urban design qualities at the street level using open-access omni-directional and satellite imagery. University of Manchester, Planning in the Faculty of Humaninties. Massachusettes: University of Manchester School of Environment, Education, and Development.
Reagan, A. (2017). Measuring walkability: gainesville's urban core. 1-81. Gainesville,
FL: University of Florida. Talen, E. (2002). Pedestrian access as a measure of urban quality. Planning & Practice
Research, 17(3), 257-278. U.S. Census Bureau. (2010). 2010 U.S. Census Blocks in Florida (File Geodatabase
with Associated Redistricting Tables) [Data file]. Available from: http://www.fgdl.org (Accessed 21 September 2017). Florida Geographic Data Library, University of Florida, Gainesville, FL.
Walk Score. (n.d.). Walk Score Methodology. Retrieved from Walk Score:
https://www.walkscore.com/methodology.shtml Wolf, M. (2008). The Zoning of America. Lawrence, Kansas: University Press of
Kansas. Yang, Y. (2008). A Tale of Two Cities: Physical Form and Neighborhood Satisfaction in
Metropolitan Portland and Charlotte. Journal of American Planning Association, 307-323.
163
BIOGRAPHICAL SKETCH
Allison Reagan was born September 1995 in Reston, Virginia. She moved to
Gainesville in August of 2013 and enrolled in the College of Design, Construction, and
Planning’s 4 + 1 Program for the completion of a bachelor’s in Sustainability and the
Built Environment and master’s in Urban and Regional Planning in a period of five
years. Allison received a Bachelor of Science degree in Sustainability and the Built
Environment from the University of Florida in 2017. She continued her graduate
education at the University of Florida and received a degree of Master of Arts in Urban
and Regional Planning in 2018.