Dallas walkability

DOWNTOWN DALLAS W A L K A B I L I T Y S T U D Y 2016

Table of Contents

Table of Contents 1.

Executive Summary

6

2.

Introduction

10

3.

Background Information

14

4.

Study Area a.

City of Dallas b.

Downtown Dallas

18

5.

Data Collection a.

Interviews

22

6.

Data and Variables 26 a.

Field Variables i.

Imageability ii.

Enclosure iii.

Human Scale iv.

Transparency v.

Complexity vi.

Control Variables • Active Patio • Width of Sidewalk • Homeless People • Street Canopy (Covered Sidewalks) vii.

Pedestrian Activity b.

GIS Variables i.

Design ii.

Density iii.

Diversity iv.

Destination Accessibility v.

Distance to Transit vi.

Demographics vii.

Employment Concentration viii.

Parks Proximity

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7.

Analysis and Results a.

Urban Design Features i.

Imageability ii.

Enclosure iii.

Human Scale iv.

Transparency v.

Complexity vi.

Control Variables • Active Patio • Width of Sidewalk • Homeless People • Street Canopy (Covered Sidewalks) b.

GIS Variables i.

Density ii.

Design iii.

Diversity iv.

Destination Accessibility v.

Distance to Transit vi.

Demographics vii.

Employment Concentration viii.

Parks Proximity

42

8.

Recommendation a.

Imageability I. Main Street II. Elm Street III. Commerce Street IV. Other Significant Segments b.

Enclosure I. Main Street II. Elm Street III. Commerce Street IV. Other Significant Segments

82

c.

d.

e.

9.

Table of Contents

Table of Contents Human Scale I. Main Street II. Elm Street III. Commerce Street IV. Other Significant Segments Transparency I. Main Street II. Elm Street III. Commerce Street IV. Other Significant Segments Complexity I. Main Street II. Elm Street III. Commerce Street IV. Other Significant Segments

References

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CHAPTER

1

Executive Summary

Executive Summary This research evaluates the ďŹ ve urban design qualities, four built environmental indicators speciďŹ c to the City of Dallas as well as six GIS indicators to identify urban design as well as other qualities that affect physical activities of the people in Dallas Downtown Improvement District in 402 block faces. This study covers a comprehensive incorporation of the experience of observers for imageability, enclosure, human scale, transparency and complexity, and statistical analysis (GIS and SPSS) to measure development density, landuse mix, street design, destination accessibility, and distance to transit ,demographics, employment concentration and number of parks.

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Chapter 1

1 This research evaluates the ďŹ ve urban design qualities, four built environmental indicators speciďŹ c to the City of Dallas as well as six GIS indicators to identify urban design as well as other qualities that affect physical activities of the people in Dallas Downtown Improvement District in 402 block faces. This study covers a comprehensive incorporation of the experience of observers for imageability, enclosure, human scale, transparency and complexity, and statistical analysis (GIS and SPSS) to measure development density, landuse mix, street design, destination accessibility, and distance to transit ,demographics, employment concentration and number of parks.

The research team from the Institute of Urban Studies (IUS) in the College of Architecture, Planning and Public Affairs at the University of Texas at Arlington collected data during summer 2016 and continued analysis through fall 2016 to deliver a comprehensive report from the analysis with high graphics and visualization. The result of this study determines the high scored and low scored block faces in each qualities and provides policy and design recommendation such as improvements in crosswalks, landscape features and furniture, adding public art and creating more diverse colors and strategies to boost the retail activities as well as diverse land use in streets such as Elm, Main, Commerce and in low scored. The policy recommendations are intended to improve quality of life and place for all community of users in Downtown Area.

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Chapter 1

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CHAPTER

2

INTRODUCTION

INTRODUCTION Numerous studies show that walking(the physical activity) and walkability(the quality of walking conditions, comprising safety, comfort, and convenience) provide numerous benefits for society, such as accessibility, consumer cost savings, public cost investments (reduced external costs), more efficient land use, community livability, enhanced fitness and public health, economic growth, and provision for equity aims (Litman, 2014). A considerable and growing number of international researches is founding strong evidence for a link between neighborhoods built environments and walking activity of residents. Inhabitants of neighborhoods considered as more ‘walkable’, aesthetically appealing, and with a variety of destinations try to have more physical activity (Witten, Blakely, Bagheri, & Badland, 2012).

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Chapter 2

2 INTRODUCTION Numerous studies show that walking(the physical activity) and walkability(the quality of walking conditions, comprising safety, comfort, and convenience) provide numerous benefits for society, such as accessibility, consumer cost savings, public cost investments (reduced external costs), more efficient land use, community livability, enhanced fitness and public health, economic growth, and provision for equity aims (Litman, 2014). A considerable and growing number of international researches is founding strong evidence for a link between neighborhoods built environments and walking activity of residents. Inhabitants of neighborhoods considered as more ‘walkable’, aesthetically appealing, and with a variety of destinations try to have more physical activity (Witten, Blakely, Bagheri, & Badland, 2012).

Until recently, the built environment has been described mostly in comprehensive terms referred to as the ‘D’ variables (Ewing & Cervero, 2001; Handy, 2005; Ewing, , Clemente, Handy, & Ross, 2005). The original three Ds, created by Cervero & Kockelman, (1997), are density, diversity, and design. The Ds were later developed to comprise destination accessibility and distance to transit (Ewing & Cervero, 2011). Furthermore, another set of D variables, associated with demographics, has been applied in travel investigations to control the independent influence of the built environment upon travel behavior (Ewing et al. under review).

In over 200 investigations, the built environment has been measured or operationalized in terms of the D variables (c.f. Badoe & Miller 2000; Crane 2000; Ewing and Cervero 2001; Stead and Marshall 2001; Cervero 2003; Saelens, Sallis, & Frank, 2003; Handy 2005; McMillan 2005; Heath et al. 2006; McMillan 2007; Cao, Mokhtarian, and Handy 2009; Pont et al. 2009; Ewing & Cervero, 2010). These investigations explain trip frequencies, mode choices, trip distances, and general vehicle miles traveled. A large subset of studies explains pedestrian mode,

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choice, or walking frequency, in terms of the D variables (Ameli, Hamidi, Garfinkel-Castro, & Ewing, 2015). Measurement of five of the six D variables (density, diversity, destination accessibility, distance to travel and demographics) is relatively straightforward and we can apply them independently although there is some overlap (e.g. diversity and destination accessibility). However, in general researchers prefer these four elements of the built environment and the metrics applied to operationalize them (Ameli, Hamidi, Garfinkel-Castro, & Ewing, 2015).

A number of current studies try to address the shortage of empirical research on urban design characteristics that affect walking activity. The first of these studies developed measurement protocols for nine urban design qualities cited in the literature (Ewing, , Clemente, Handy, & Ross, 2005; Ewing & Handy 2009). Findings of another study comprise an illustrated field manual (Clemente et al. 2005). Five of the nine urban design qualities that were effectively operationalized are imageability, enclosure, human scale, transparency, and complexity. The other four measures (coherence, linkage, legibility, and tidiness) were investigated but not operationalized in this study.

A following detailed study was undertaken to validate the urban design metrics expanded by the earlier ‘operationalization’ study (Ewing, , Clemente, Handy, & Ross, 2005; Ewing and Handy 2009).

The research was conducted in New York City, widely regarded as one of America’s most walkable cities (Purcie, et al., 2009). The urban design metrics, as a group, were found to add significantly to the explanatory power of the models (Purciel et al. 2009). Additionally, one metric, transparency, proved more significant than any other variable in a later study (Ewing et al. under review). Although it represents a critical step to empirical analysis of walkability, the Columbia University study (Purciel et al. 2009) possesses some limitations.

Most importantly, New York City is unique among cities in America in

Chapter 2

terms of walkability. This might limit the reliability of their results. The major threat to the validity of this research is the unstandardized methodology that was used for data collection. However, our research builds on existing studies and tries to validate the operationalized urban design measures against pedestrian counts in downtown Dallas, Texas. The fact that Dallas is a more typical American city than New York City, addresses the limitations of the previous validation research. We resolve the validity issue by following to a standardized methodology for collecting pedestrian counts.

This research evaluates the ďŹ ve urban design measures operationalized by the previous research studies to identify the walkable environment in Dallas. Every measure and its role in affecting walkability is concisely deďŹ ned. Moreover, we identify the way each measure contributes to the empirical model. The research, funded by the City of Dallas, has a goal of identifying urban design qualities that explain and forecast extends of physical activity in urban spaces. The measures, while evaluated for reliability and face validity, were not evaluated at the time for internal validity. In fact, the measures were not demonstrated to forecast pedestrian behavior or street life.

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CHAPTER

3

Background Information

Background Information Walking is considered as an important component of environmentally friendly, healthier, and socially active communities. Numerous investigations in different ďŹ elds have highlighted the value of walking for the residents (Mouraa, Cambraa, & Gonçalvesa, 2017). Since the lack of walking is a main risk factor for obesity, diabetes, cardiovascular, several kinds of cancers and even mental health (United States Department of Health and Human Servi, 1996).

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Chapter 3

3 Background Information Walking is considered as an importantcomponent of environmentally friendly, healthier, and socially active communities. Numerous investigations in different fields have highlighted the value of walking for the residents (Mouraa, Cambraa, & Gonçalvesa, 2017). Since the lack of walking is a main risk factor for obesity, diabetes, cardiovascular, several kinds of cancers and even mental health (United States Department of Health and Human Servi, 1996). Meanwhile, walking is a base of the sustainable city, social interaction, environmental and economic development, usually being the only way a lot of residents can access day-to-day activities. Moreover, it provides viable streets that lead to safer urban environments. Additionally, walking plays an important role in community safety, accessibility and social inclusion. Improving walkability has arisen as a crucial challenge to the design of the urban environment, as during the past century pedestrian access has decreased gradually in the majority of cities (Forsyth & Southworth, 2008) (Frank, Schmid, Sallis, Chapman, & Saelens, 2004) (Krambeck & Shah , 2006). Moreover, walking is a simple mode of getting around with few in necessities for special infrastructure in comparison to other means of transportation. While other ways of transport, particularly via private auto, have been extensively investigated during the past decades and have a significant degree of measurability (Moura, 2015). More recently, transportation and urban planning studies have found several patterns of association between walking activity and the built environment (Frank, Schmid, Sallis, Chapman, & Saelens, 2004). Accordingly, it is crucial to better understand what makes an environment more pedestrian friendly in order to provide more opportunities for residents to walk.

Although socio-economic features and individual preferences are substantial influences, the built environment plays a considerable role in peoples’ choices to walk (Lee & Moudon, 2006). Moreover, built environment qualities are usually a more controllable factor

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than altering individual’s behavior and lifestyle (Cerin, Saelens, Sallis, & Frank, 2006). Hence, besides demographic and psychosocial factors, we should consider the role of environments in physical activity behaviors (Sallis & Owen, Ecological models of health behaviour, 2002) and how features of the built environment influence the health of communities (Diez Roux, 2003).

In fact, walkability is defined as the suitability and attractiveness of the built environment for walking (Saelens, Sallis, & Frank, 2003). The main research challenge is how to measure a built environment’s conduciveness for walking.

Encouraging more walking trips and more time spent walking are beneficial societal goals of interest to a wide range of policy makers (Saelens, Sallis, & Frank, 2003). Researchers in disciplines of public health, urban planning and transportation fields have pointed out the importance of using objective measures to better understanding the relationships between physical environment characteristics and physical activity behaviors (Sallis & Owen, 2002). Urban planners tend to assess walking as a way to decrease vehicle miles traveled, greenhouse gas emissions, and urban sprawl (Ewing & Handy, 2009).

Public health scholars tend to measure walking due to its role in accomplishing the US government recommended daily extent of exercise, decreasing obesity, and dealing with chronic diseases (Gebel, Bauman, Sugiyama, & Owen, 2011) In order to measure walkability, some studies have applied systematic ratings of relevant environmental attributes in certain areas by skilled observers (Pikora, Giles-Corti, Bull, Jamrozik, & Konrad, 2003).

Some other researchers have applied Geographic Information Systems (GIS) data to create spatial analysis of resource accessibility (Giles-Cortia & Donovan, 2002). An evaluation of public health investigations on the environmental factors of physical activity in adults indicated that the most consistent evidence are accessibility

Chapter 3

of facilities, opportunities for activity, and aesthetics (Humpel, Neville, & Leslie, 2002). However, the majority of studies (15 of 19) focused on perceived rather than objective methods, and only two of the researches used GIS methodologies to construct objective methods of the applicable environmental (Giles-Cortia & Donovan, 2002).

Other tools and techniques have also been used, such as: audit tools, checklists, inventories, level-of-service scales, surveys, questionnaires and indices. While these tools are different in their application, they propose similar measurements: either a particular number that classifies the environment as high vs. low suitability for walking; or the number of features that increase or decrease walking. Furthermore, there have been methods established to address various scales, from the neighborhood scale to the street segments and even intersections (Ewing & Handy, Measuring the unmeasurable: Urban design qualities related to walkability, 2009) (Maghelal & Capp, 2011). The highest used tools are web-based applications such Walk Score (available at www.walkscore.com, and Walkshed (available at www.walkshed.org ) for urban areas and Walkonomics (www. walkonomics.com) for streets, in addition to PERS (Pedestrian Environment Review System), amongst 38 other instruments in the Active Living Research inventory (http://activelivingresearch.org). Walkability measurement can also assess indirect built environment characteristics, like the perception of the built environment, which have positive and negative effects on walking (Brown, Werner, Amburgey, & Szalay, 2007). Moreover, measurement of built environment qualities contains walking facilities, like the existence and quality of sidewalks and crosswalks, quantity of vehicle travel lanes, and nearby land use kinds and density (Moudon & Lee, 2003). Indirect built environment qualities also include the existence of other pedestrians or perceptions of safety from traffic or crime (Moudon & Lee, 2003). However, the inter- and intra-reliability are rarely evaluated (for example (Emery & Crump, 2003) and (Ewing R. , Handy, Brown son, Clemente, &

Winst, 2006) ), the question is on how to connect walkability scores (whether expressed quantitatively or qualitatively) with the visible walking activities. According to the review shown previously, diverse methodologies could be used to achieve public insight on the walkability of the built environment and compare results with walkability scores: 1. Pedestrian counts: linking walkability scores to pedestrian flow.

In this method, the fundamental hypothesis is that higher walking is related to higher walkability 2. Street surveys: connecting walkability scores to resident’s insight of the built environment. Interviewees are requested to assess the walking environment for several dimensions.

3. Home-based surveys: relating walkability scores to resident’s trip habits and lifestyle. In this method, respondents show the level walkability of the streets they know in the common set of streets they use.

The findings of an investigation conducted by the London Planning Advisory Committee provided the multidimensional 5C’s layout (Gardner, Johnson, Buchan, , & Pharoah, 1996) which has been commonly utilized to the present (Kamel, 2013). Based on this pattern, a pedestrian friendly environment has characteristics such as Connected, Convenient, Comfortable, Convivial and Conspicuous (Saelens & Handy, 2008).

Another study conducted by (Kim, Park, & Lee, 2014) examined the links between pedestrian satisfaction and several built environment variables, to advance understanding of urban design methods that can improve both pedestrian satisfaction and activities. Applying econometric tools, the writers demonstrated that there is considerable correlation between pedestrian satisfactions and built environmental factors, showing the value of considering psychological aspects for walkability research, like different pedestrian groups and trip motives.

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DOWNTOWN DALLAS WALKABILITY STUDY

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Study Areas

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a. City of Dallas b. Downtown Dallas

Study Areas

Dallas is a great reection of a vibrant atmosphere comprising talent, culture, art, entrepreneurship, investment, job opportunities, and a vibrant, diverse economy. Dallas also offers individuals and families a wide range of recreational opportunities, consisting of diverse cultural venues, galleries, parks, trails, forests, and lakes. All these opportunities in the City of Dallas are strongly associated with and depend upon the vitality and liveliness of Downtown area.

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Chapter 4

4.A City of Dallas Dallas is a great reflection of a vibrant atmosphere comprising talent, culture, art, entrepreneurship, investment, job opportunities, and a vibrant, diverse economy. Dallas also offers individuals and families a wide range of recreational opportunities, consisting of diverse cultural venues, galleries, parks, trails, forests, and lakes. All these opportunities in the City of Dallas are closely associated with and depend upon the vitality and liveliness of Downtown area.

When Dallas was a developing young city, in the 19th and early 20th centuries, the key locus of business and cultural activity was Downtown. As with most cities at the time, business and retail mixed with residential as well as civic structures and other public amenities within a radius that was convenient to travel by foot or was serviced by streetcar. Since then, population growth, cultural and demographic changes, and a variety of new opportunities changed the urban structure and growth patterns of Dallas. Population growth has changed the spatial distribution of the city, with the much of recent growth concentrated within the area between the Dallas North Tollway and the Central Expressway, and the city’s edges. While Downtown remained a center for employment in banking, law, government, and other corporate offices, residential moved out, and retail more often than not moved underground, into the Dallas Pedestrian Network tunnels.

Over the past ten years, considerable commercial and residential development has sprung up the Uptown, Downtown, and Oak Cliff communities (Dallas-OED, Dallas Economic Development, 2016a).

The city’s core has been experiencing higher densities, and more full time residents with these developments.

Rapidly growing residential neighborhoods, such as Uptown, Downtown, the Cedars, Oak Cliff, and Oak Lawn, are transforming into a dense and walkable urban core. With large population growth

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expected for the North Central Texas area Dallas, understanding and facilitating growth in pedestrian activity are pivotal concerns (NCTCOG, 2015). While Dallas is defined as an automobile-oriented city, developments described above have begun to offer alternative means of getting around. Recently developed and implemented planning efforts have created physical pathways for pedestrian movement in the Dallas (Dallas-OED, Dallas Economic Development, 2016a).

One of the paramount plans is the Downtown 360 strategic plan.

This strategic plan has been the guiding plan for Downtown Dallas since 2011. The plan identifies Downtown Dallas as an integrated urban center that is composed of interconnected districts linked by an accessible transit network. The plan identifies that Dallas offers a particular and distinct combination of places to live, open spaces to refresh, bustling street activity, outstanding business and retail, and dynamic urban adventures for residents, workers, and visitors.

The strategic plan also concedes challenges facing Downtown Dallas, especially consisting of streets that can be unfriendly to pedestrians. The plan described the impediments to pedestrian activity in Downtown Dallas, including cracked sidewalks, design obstructions, overhanging covering, lack of tree canopy and fast-traffic circulation. A better understanding of pedestrian walkability is one of the primary objectives of the Dallas’ Economic Development Department in order to improve Downtown’s “ground floor” (The City of Dallas & Downtown Dallas Inc., 2016).

Chapter 4

4.B Downtown Dallas The Institute’s research began with pilot studies to advance walkability within the Downtown Improvement District (DID). Downtown Improvement District (DID) was established in 1992 and was renewed in 2001 and 2006. The Downtown Improvement District (DID) is a special assessment area created at the request of the property owners, consisting of approximately 1,777 properties, in the district (Dallas-OED, Downtown Improvement District (DID), 2016b). The DID has specific goals, such as marketing the area, providing additional security, landscaping and lighting, street cleaning, and cultural or recreational improvements. The map 1 shows the location of the project in the City of Dallas.

Map 2: Study Area Streets

The research team used a methodology developed from two benchmark studies related to walkability: “Creating and Validating GIS Measures of Urban Design for Health Research”, Purciel et al.

(2009) and “Do Better Urban Design Qualities Lead to More Walking in Salt Lake City, Utah?”, Ameli et al. (2015), both of which evaluate why and how to create more walkable cities.

Map 1: Location of Study Area in the City of Dallas

Data collection covers a total of 402 street segments’ block faces (the field variables, other indicators and GIS variables on each side of a street). The selected street segments for this pilot study are shown in Map 2.

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Data Collection

Data Collection Within the study area there is a vibrant mix of uses consisting of a booming residential neighborhood in the southern portion of the study area, a transit hub and a lunchtime mainstay at the northern and western portions servicing corporate workers and out-of-town visitors, and Union Station and institutional buildings in the south and east for federal and local governmental entities. Pedestrian activity within downtown can inuence overall perception of the area as a better place to live, can promote healthier lifestyles and can help to create a higher level of social interaction. This study was conducted to show areas of higher and lower pedestrian activity and evaluate the qualities that can make one street more attractive and walkable than another.

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Chapter 5

5 Data Collection Within the study area there is a vibrant mix of uses consisting of a booming residential neighborhood in the southern portion of the study area, a transit hub and a lunchtime mainstay at the northern and western portions servicing corporate workers and out-of-town visitors, and Union Station and institutional buildings in the south and east for federal and local governmental entities. Pedestrian activity within downtown can influence overall perception of the area as a better place to live, can promote healthier lifestyles and can help to create a higher level of social interaction. This study was conducted to show areas of higher and lower pedestrian activity and evaluate the qualities that can make one street more attractive and walkable than another.

time period was selected to avoid rainy days when pedestrian activity was likely to be reduced.

A research team of graduate students from the Institute of Urban Studies (IUS) in the College of Architecture, Planning and Public Affairs at the University of Texas at Arlington gathered primary data for this study. All data collection was conducted by graduate student counters. First, a counter was positioned in the middle of each street segment for pedestrian counting, then the counter walked the entire length of each street segment evaluating street level attributes for buildings to same side of the street along the block face.

Data was collected in the summer of 2016 from the end of May to mid-August. For each street segment, all pilot study initial data collection (including pedestrian counts) were conducted from 3 pm to 7 pm. The pedestrian activity outcome variable explained in the pilot study is the number of walking people encountered within 30 minutes for a given street segment. Therefore, pedestrian counts were taken half an hour per segment during peak walking hours, from 5 pm to 7 pm, in Downtown Dallas. Pedestrian activity measured during the first four weekdays and count dates does not cover Fridays, Saturdays and Sundays because the first four weekdays are a representative sampling of activity for a typical day. The count

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Figure 1: Study Area Block Faces

The data for the built environment attributes comes from the study conducted in Downtown Dallas during same time period as the pedestrian counts were taken. The collected built environment attributes focused on elements that have been illustrated to influence walkability in other cities. This portion of the data collection consists of a number of specific measurable attributes for each area. The built environment attributes study took approximately 4 hours per segment for initial data collection. Detailed urban design variables were measured for both sides of every segment within the study area boundary. A total of 402 street segments were covered in terms of

Chapter 5

five urban design qualities and about 30 metrics. Pedestrian activity on the first four weekdays during peak hours was measured as well.

For each street segment, all metrics covering the five urban design variables and control variables were measured. The study team mapped additional secondary indicators including the D variables (e.g. density, diversity, design, destination accessibility, distance to transit and demographic) as well as employment concentration and park proximity using Arc GIS software. Noise level data was measured with an additional phone application by collecting urban design variables in the field.

Figure 2: Study Area Block Face Coding

a. Interviews

In this study, we did not have a designed interview methodology to evaluate the perception of the residents and users of the study area regarding walkability. However, in the process of data collection, several residents and pedestrians approached the researchers, discuss the project, and expressed their ideas about the walkability level and walking challenges within Downtown Dallas, so we considered them for defining control variables. The main issue, which most of the interviewees pointed out, was the presence of a great number of homeless people in the area. Since a homeless shelter is located close proximity to portions of the study area, a considerable number of homeless people walk around the area soliciting money from residents, workers and tourists. The most interviewees stated that they believed it is not safe and convenient to walk or exercise in streets that there are many homeless people are an encouraging factor for walking since they are four-season users of the streets and she feels safer in a street with several beggars than in an empty street. Another issue that interviewees expressed as an effective factor of walkability in the area was the existence of a network of underground tunnels, the Dallas Pedestrian Network. They think that in the mostly hot summer days in Dallas, employees of the offices towers prefer to use these tunnels to reach to the food courts instead of using sidewalks, decreasing the number pedestrians at street level.

One interviewee who was an artist from Columbia University believed that the main obstacle for walking in this area is the unattractiveness of many downtown streets. He stated that “in short, as a Dallas native having had the joy of living elsewhere (New York. Chicago.

New Orleans) I can say with ashamed that we are too far behind in ‘many’ modes for my twenty-something spirit. I am glad, however, to have ran into Hamid and learn of his pursuits alongside with UTA’s curriculum.” He believes that the arts-street performances or art structures- could help to get more attention to streets, which could positively affect mood and quality of the street level environment.

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CHAPTER

6

Data and Variables a. Field Variables i. Imageability ii. Enclosure iii. Human Scale iv. Transparency v. Complexity vi. Control Variables

b. GIS Variables i. Design ii. Density iii. Diversity iv. Destination Accessibility v. Distance to Transit vi. Demographics vii. Employment Concentration viii. Park Proximity

Data and Variables A research team from the Institute of Urban Studies (IUS) in the College of Architecture, Planning and Public Affairs at the University of Texas at Arlington compiled the primary data for this study during summer 2016. A total of 402 street segments located within the study area in Downtown Dallas was measured. For each street segment (for example see in Figure 6.1), researchers measured all urban design features, which consist of the ďŹ ve urban design qualities, D variables and other indicators as well as counted pedestrian activity. While the research by Ameli et al. (2015) did not include the noise level variable of the Imageability metric, it was included in this study as well.

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Chapter 6

6 A research team from the Institute of Urban Studies (IUS) in the College of Architecture, Planning and Public Affairs at the University of Texas at Arlington compiled the primary data for this study during summer 2016. A total of 402 street segments located within the study area in Downtown Dallas was measured. For each street segment (for example see in Figure 6.1), researchers measured all ďŹ eld variables, which consist of the ďŹ ve urban design attributes, D variables and other indicators as well as counted pedestrian activity. While the research

by Ameli et al. (2015) did not include the noise level variable of the Imageability metric, it was included in this study as well.

After initial observational data collection was completed, secondary D variables were collected using ArcGIS software. The derivative GIS data was computed from a variety of sources. Data for parcel area, building area and building use were collected from the Dallas County Appraisal District data. Census Block 2010 data provides information for population and household in each census block. In addition to this, road network data were compiled from the City of Dallas website and rail station location data from the North Central Texas Council of Governments (NCTCOG) to analyze transit distance from the center of each block face on the street segment.

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Figure 6.1: An example of block faces on each segment (R= your side, L= opposite side)

Chapter 6

6.A Field Variables Over the past few years, a variety of elements has been used to measure the quality of the walking environment. Although the number of pedestrian counts on the street is a significant instrument to demonstrate pedestrian activity, physical features may tell us much about the quality of the walking environment. Recent studies provide important insights into specific characteristics of the urban design qualities that are correlated with pedestrian activity and into the limitations of this pilot study. Although each study used slightly different criteria and methods for analyzing relevant data/variables, there is substantial overlap in the different studies (Ewing R. , Handy, Brownson, Clemente, & Winston, 2005; Ewing R. , Handy, Brownson, Clemente, & Winston, 2006; Saelens & Handy, 2008; Ewing & Handy, 2009; Purciel, et al., 2009; Ameli, Hamidi, Garfinkel-Castro, & Ewing, 2015).

Each of these studies found different comparisons and conclusions by measuring pedestrian activity and the characteristic of the built environment. Ewing et al. (2005, 2006) identified five urban design qualities associated with walkability: imageability, enclosure, human scale, transparency, and complexity. Table 6.1 presents the definitions used to operationalize these qualities.

Urban Design Qualities IMAGEABILITY

Definition Imageability is the quality of a place that makes it distinct, recognizable and memorable. A place has high imageability when specific physical elements and their arrangement capture attention, evoke feelings and create a lasting impression.

ENCLOSURE

Enclosure refers to the degree to which streets and other public spaces are visually defined by buildings, walls, trees and other vertical elements. Spaces where the height of vertical elements is proportionally related to the width of the space between them have a room‐like quality.

HUMAN SCALE

Human scale refers to a size, texture, and articulation of physical elements that match the size and proportions of humans and, equally important, correspond to the speed at which humans walk. Building details, pavement texture, street trees, and street furniture are all physical elements contributing to human scale.

TRANSPARENCY

Transparency refers to the degree to which people can see or perceive what lies beyond the edge of a street and, more specifically, the degree to which people can see or perceive human activity beyond the edge of a street. Physical elements that influence transparency include walls, windows, doors, fences, landscaping and openings into mid‐block spaces.

COMPLEXITY

Complexity refers to the visual richness of a place. The complexity of a place depends on the variety of the physical environment, specifically the numbers and types of buildings, architectural diversity and ornamentation, landscape elements, street furniture, signage and human activity.

For each urban design quality and other control variables collected Table 6.1: Definition of Urban Design Qualities in the field, physical features contributing most to their quality are listed in order of priority. Table 6.2 presents the descriptions used to Source: Ewing & Handy (2009) operationalize these indicators. The section below identifies the consensus of each urban design quality that is discussed in more details.

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Urban Design Qualities

Physical Feature The number of courtyards, plazas, and parks—both sides of the street within the study area

Chapter 6

The number of major landscape features—both sides of the street beyond the study area The proportion of historic buildings—both sides of the street within the study area

IMAGEABILITY

The number of buildings with identifiers—both sides of the street within the study area The number of buildings with non‐rectangular shapes—both sides of the street within the study area

The number of courtyards, plazas, or parks are that people encountered within the study area.

Major landscape features are any prominent landscape views such as bodies of water, or man‐made features that incorporate the surrounding natural environment.

The proportion of the street fronted by buildings that is fronted by buildings that are historic.

Architecture that can be determined to have originated from the World War II era or before will be considered as historic.

The buildings whose uses can be identified by building features, such a steeple, and signs that can be easily read.

The buildings have non‐rectangular shapes that, from any angle, are not a simple rectangle.

The proportion of sky—straight ahead beyond the study area The proportion of sky—across street beyond the study area

A place as having outdoor dining has unfolded chairs and open umbrellas even if there are no people currently utilizing it.

The amount of noise made by traffic, pedestrians, and any other.

At any time during the walk people were able to see far to their right, left and ahead.

The street wall is portions of the block that are occupied by continuous facades or walls adjacent to the sidewalk within the same side of the study area.

The street wall is portions of the block that are occupied by continuous facades or walls adjacent to the sidewalk within opposite side of the study area.

The proportion of field of vision beyond the street is the sky.

The proportion of field of vision across the street is the sky.

The number of long sight lines—both sides of the street beyond the study area (from above)

At any time during the walk people were able to see far from above to their right, left and ahead.

The presence of outdoor dining—same side of the street within the study area The noise level—both sides of the street within the study area The number of long sight lines—both sides of the street beyond the study area The proportion of street wall—same side of the street within the study area

ENCLOSURE

Description

The proportion of street wall—opposite side of the street within the study area

The proportion of the surface area of the first floor (street level) of buildings front along the sidewalk made up of windows.

The average building height—same side of the street within the study area The average height of buildings that front the sidewalk are measured in feet.

A small planter is any potted arrangement of shrubs or flowers that are less than 10 square feet at The number of small planters—same side of the street within the study area the base.

The number of pieces of street furniture and other street items—same side of the street within the The presence of street furniture consists of benches, lamp posts and other street items including study area newspaper boxes, parking meters, etc.

The proportion of the surface area of the first floor (street level) of buildings front along the sidewalk The proportion of windows at the street level—same side of the street within the study area made up of windows.

The street wall is portions of the block that are occupied by continuous facades or walls adjacent to The proportion of street wall—same side of the street beyond the study area (*from above) the sidewalk beyond the study area.

The proportion of windows at the street level—same side of the street within the study area

HUMAN SCALE

TRANSPARENCY

The proportion of active uses—same side of the street within the study area The number of buildings—both sides of the street beyond the study area The number of basic building colors—both sides of the street beyond the study area

COMPLEXITY

The number of accent colors—both sides of the street beyond the study area The presence of outdoor dining—same side of the street within the study area (*from above) The number of pieces of public art—both sides of the street within the study area The number of walking pedestrians—same side of the street within the study area The number of active patios—both sides of street within the study area

OTHER INDICATORS

The width of the sidewalk (feet) — same side of street within the study area The number of homeless people—same side of street within the study area The proportion of covered sidewalk—same side of street within the study area

Table 6.2: Summary of Urban Design Indicators

28 | Downtown Dallas Walkability Study

Active uses fronting the sidewalk are defined as shops, restaurants, public parks, and other uses.

Buildings are located either on the street within your study area or buildings that are outside the study area.

Basic building colors are the primary colors of buildings that have been counted on the number of buildings beyond the study area.

Accent colors are used on building trim, street furniture, awnings, and signs that contrast with basic building colors.

A place as having outdoor dining from above has unfolded chairs and open umbrellas even if there are no people currently utilizing it.

Public art is monuments, sculptures, murals, and any other artistic display that has free access.

The number of walking pedestrians are people encountered on one walk through the study area.

The active patio is an outdoor facility that has unfolded chairs and open umbrellas, not any dining facility.

Street width is the total width from building face to sidewalk face on the street.

The existence of homeless people living in neighborhoods is an obstacle to consistent physical activity among residents.

The street canopy is the shade that is vital for pedestrians in warm to hot climate environments.

Chapter 6

i. Imageability

ii. Enclosure

Imageability as a quality of a physical environment that makes it recognizable, distinct, remarkable, vividly identified, powerfully structured and memorable. A highly imaginable place contains specific physical elements, distinct parts and arrangements recognizable to anyone who has visited or lived there. A place with high imageability recalls a strong image and feelings in an observer and creates a long-term impression. Key principles of imageability include landmarks that create visual termination points, orientation points and points of diversity in the urban context (Ewing & Handy, 2009).

Places that rate high on other urban design qualities (enclosure, human scale, transparency, and complexity) are likely to rate high on imageability as well. of the street within the study area.

Enclosure refers to streets and outdoor spaces that are defined and shaped by vertical elements and the width of spaces, which interfere with viewers’ lines of sight. An outdoor space and street are rated favorably for enclosure when they have a distinct and well-defined silhouette. In the urban context, the enclosure is shaped by lining the street or buildings, identified as the street walls of the outdoor room, with continuous building faces of roughly equal height. Enclosure is lessened by breaks in the continuity of the street wall and in the vertical elements. Breaks in continuity create dead spaces, such as vacant lots and parking lots that can erode enclosure.

Based on literature and the conceptualized definition of imageability, the following features are counted in this study: • • • • • • •

The number of courtyards, plazas, and parks—both sides of the street within the study area; The number of major landscape features—both sides of the street beyond the study area; The proportion of historic buildings—both sides of the street within the study area; The number of buildings with identifiers—both sides of the street within the study area; The number of buildings with non-rectangular shapes—both sides of the street within the study area; The presence of outdoor dining—same side of the street within the study area; The noise level—both sides of the street within the study area.

Based on literature and the conceptualized definition of enclosure, the following features that contribute to the consciousness of enclosure are counted in this study: • • • • •

The number of long sight lines—both sides of the street beyond the study area; The proportion of street wall—same side of the street within the study area; The proportion of street wall—opposite side of the street within the study area; The proportion of sky—straight ahead beyond the study area; The proportion of sky—across street beyond the study area.

iii. Human Scale Human scale identifies the importance of the width of buildings as well as the height. High rise buildings and wide streets can discourage pedestrians to walk, while the shade of leaves and branches offers the smooth pedestrian experience of a smaller space within

Downtown Dallas Walkability Study | 29

Chapter 6 the larger volume. Furthermore, personal interaction distances have a critical role in designing for the human scale because, for pedestrians, short distances are much more recognizable and create social interaction. In addition to these elements, human scale is related to the amount of street furniture and other street items.

The elements that contribute significantly to human scale are: • The number of long sight lines—both sides of the street beyond the study area; • The proportion of windows at the street level—same side of the street within the study area; • Average building height—same side of the street within the study area.

• The number of small planters—same side of the street within the study area; • The number of pieces of street furniture and other street items— same side of the street within the study area.

iv. Transparency Transparency refers to a tangible condition associated with an inherent quality of substance as in a glass wall in terms of a percentage of the facade area. Transparency is a strategic urban design element because this is where the human activity occurs between indoors and outdoors. In this study, only three human activity variables have been used to illustrate the perception of transparency.

• • •

The proportion of windows at the street level—same side of the street within the study area; The proportion of street wall—same side of the street beyond the study area (*from above); The proportion of active uses—same side of the street within the study area.

30 | Downtown Dallas Walkability Study

v. Complexity Complexity offers a number of prominent elements that impress a viewer in the moment. A high level of complexity provides elements that may be few, similar, predictable and unordered. Complexity makes reference to an interesting walking network that creates the psychological effect of making the walking distance seem shorter.

The presence of complexity is based on building shapes, materials, colors, architecture and ornamentation Additionally, a well-defined complexity describes the presence of a mixture of commercial, residential and civic uses in close proximity to each other. Six variable are used to investigate the perception of complexity. In order of significance, they are listed: • The number of buildings—both sides of the street beyond the study area; • The number of basic building colors—both sides of the street beyond the study area; • The number of accent colors—both sides of the street beyond the study area; • The presence of outdoor dining—same side of the street within the study area (*from above); • The number of pieces of public art—both sides of the street within the study area; • The number of walking pedestrians—same side of the street within the study area.

Figures 6.2 to 6.6 shows the example of static images from the field, illustrating variation in urban design qualities. The pair of pictures represents the low- and high- rated street segments from Downtown Dallas sample of each urban design variable.

Chapter 6

Figure 6.2a. An example of imageability with high quality.

Figure 6.3a. An example of enclosure with high quality.

Figure 6.2b. An example of imageability with low quality.

Figure 6.3b. An example of enclosure with low quality.

Downtown Dallas Walkability Study | 31

Chapter 6 Figure 6.4a. An example of human scale with high quality.

Figure 6.5a. An example of transparency with high quality.

Figure 6.4b. An example of human scale with low quality.

Figure 6.5b. An example of transparency with low quality.

32 | Downtown Dallas Walkability Study

Chapter 6

vi. Control Variable

Figure 6.6a. An example of complexity with high quality.

The methodology that is applied for this study was initially designed for measuring walkability in New York City, New York and in Salt Lake City, Utah. Since the City of Dallas has a different urban context and a different climate, other factors may be effective in inuencing walking activity in this city and should be considered to achieve accurate ďŹ ndings about walkability. Therefore the research team applied different sources in order for identifying these factors. First of all, through a meeting with planners of the City of Dallas, the current issues of Downtown Dallas and requirements of the City of Dallas were identiďŹ ed. Secondly, the research team visited the study area and did data collection rehearsal, then checked the data with the supervisor of the project, Dr. Shima Hamidi, who had experience of conducting the same research methodology in Salt Lake City, Utah.

By doing this, the supervisor made sure that the researchers had understood the methodology and all of them had the same standpoint regarding the variables. Meanwhile, during this rehearsal, researchers analyzed the area and suggested some control variables to the supervisor. After discussing the suggested variables, some of them were selected.

Four other indicators, the number of active patios (both sides of street within the study area), width of the sidewalk-feet- (same side of street within the study area), the number of homeless people (same side of street within the study area) and proportion of covered sidewalk (same side of street within the study area) were used for each block face. Variables are indicated at the end of the summary of urban design indicators.

Figure 6.6b. An example of complexity with low quality.

- Active Patio The client asked to consider the number of active patios as a measuring variable. Active patios bring more residents in the streets and

Downtown Dallas Walkability Study | 33

Chapter 6 make the area more welcoming and vibrant. Additionally, street activities like outdoor dining improve the insights of security and sociability and ‘eyes on the street’. Since the methodology had already considered the existence of outdoor dining, the new variable defined by the number. It also just considers the active patio, not any dining facility.

- Sidewalk The width of the sidewalk itself is, of course, essential to pedestrian activity and has significant implications for streetscape design (Southworth, 2005). A wide sidewalk enhances the environment occupied by pedestrians. It provides enough space for pedestrians to walk at their chosen pace, stand, sits, socialize, or merely enjoy their surroundings. Conversely, narrow sidewalks prevent pedestrians from walking comfortably and safely in the urban area. This study presents a sidewalk pavement width (unit: feet) for making more pedestrian friendly and walk-inspiring sidewalk pavements in the urban area.

- Homeless People Most interviewees pointed out that the existence of homeless people affected the safety of the area and consequently influence walking activities in the area. However, some of them considered this factor as discouraging for walking while some others believed that it’s an encouraging effect. Hence this variable was defined to measure this issue. Meanwhile, findings of a study by Bennett et al. (2007) show that living in the neighborhoods with low senses of security is an obstacle to consistent physical activity among residents, particularly women, residing in urban low-income housings. People may decline their outdoor activities because they feel unsafe there (McGinn, Evenson, Herring, & Huston, 2008).

- Street Canopy(Covered Sidewalk) Comfortable outdoor conditions encourage walking and help to cre

34 | Downtown Dallas Walkability Study

ate a vibrant and successful community and street activity is closely connected to outdoor climate situations. Accordingly, details like shaded walkway can affect pedestrian behavior and choices considerably. They might encourage or discourage residents from walking on a specific side of the road (Maco & Mcpherson, 2003).

Though trees are the eventual environmental shade provider, with proved different advantages to the urban environment (Laverne & Lewis, 1996; Nowak, Crane, & Stevens, 2006; Maco & Mcpherson, 2003). Some other tools can provide shade, by unlimited design answers, (built structures or green elements) depending on creativity and numerous specific causes, like feasibility, economical and local requirements constraints, among others.

Consequently, in settings with warm to hot situations, the street canopy should be considered at the urban scale and noticed as a public necessity in terms of environmental value as well as a walkability factor (Almeida, 2008). Due to the fact that Dallas is located in a hot and dry area, the role of the shaded sidewalk is significant in walking activities. This factor was emphasized by the users as well.

- Pedestrian Activity In this study, the number of people encountered over a 30 minute period in peak hours for each street segment block face was used as the dependent or outcome variable. Pedestrian activity was measured during the first four weekdays and the count schedule does not cover Fridays, Saturdays, and Sundays because count dates were selected to promote a representative sampling of activity for a typical weekday. Excessively high- or low- temperature days were removed from the count schedule as well. For all locations, a weekly weather forecast was checked to acquire accurate pedestrian counts. If an inclement weather-rain or high winds- is forecasted, all field counts were canceled for any days during the count months. The research team counted the number of pedestrians from the end of May to mid-August 2016.

Chapter 6

The number of pedestrians encountered over a 30-minute period for a given block face was recorded by a researcher standing at the middle of the street segment. A mechanical counter was used to precisely record the number of all visible pedestrians consisting of those who walking, running, sitting and standing. The pedestrian activity was counted during the hours of peak pedestrian activity to standardize pedestrian counts for each street segment block face.

The pedestrian counts were, speciďŹ cally, conducted during an evening two hour period (5:00 pm-7:00 pm hours), at the work quitting time.

Downtown Dallas Walkability Study | 35

Chapter 6

6.B GIS Indicators The urban design features for this report was collected by the IUS research team during summer 2016. The D variables have been developed through performing analysis on raw data using geographic information systems (GIS). These data have been acquired from a variety of sources.

Data for parcels area, building area and building use were gathered from the Dallas County Appraisal District. Census Block 2010_SF1a provides information on population in each census block for 2010. The 2010 Census: SF 1a - P & H table provides information on average household size for 2010 in each census block. Both data have been acquired from the National Historical Geographic Information System (NHGIS). Road network information from the City of Dallas website and rail station location data from the North Central Texas Council of Governments (NCTCOG) have been used for network analysis to calculate transit distance from the center of each block face.

A list of GIS variables with their descriptions, as well as their sources, is shown in Table 1: GIS Data Variables and Sources.

36 | Downtown Dallas Walkability Study

Data Type

Description

Source(s)

Parcel Data

Tax Parcel with land area, building area, Building Use

Dallas County Appraisal District

Road Network

Street Network

North Central Texas Council of Government (NCTCOG)

Transit Stations

Passenger Rail Stations

North Central Texas Council of Government (NCTCOG)

Census Block 2010_SF1a

2010 Census Block Total Population

National Historical Geographic Information System (NHGIS)

2010 Census: SF 1a ‐ P & H Table

2010 Census Block Average Household Size

National Historical Geographic Information System (NHGIS)

Parks

Number of parks

City of Dallas GIS Services

Employment Concentration

Number of employment

Longitudinal Employer ‐ Household Dynamics (LEHD)

Table 1: GIS Data Variables and Sources

Chapter 6

I. Design

III. Diversity

Three metrics for design variables are Buffer Intersection Density (INTDEN) and Buffer Proportion Four Way Intersections (PCT4WY) and Block Length (BLKLNGH). Buffer intersection density is measured as the number of intersections within a quarter mile buffer from each block face divided by area of the buffer. Four Way Intersections (PCT4WY) is the proportion of four way intersections in each quarter mile buffer from each block face. Block Length (BLKLNGH) for each segment has been calculated through GIS length measurement (Ameli, S. H., Hamidi, S., et al, 2015).

Buffer Mix Use (MIX) and Block Face Mix Use (BLKMIX) form the variable matrix for diversity. Buffer Mix Use (MIX) is measured based on the number of different land uses and the degree they have been balanced based on parcel land area dedicated to each use within the specified quarter mile buffer. Block Face Mix Use (BLKMIX) is measured in the same way but only for the parcels abutting the street.

II. Density Density is calculated as “as a variable of interest per unit of area” (Hamidi, Shima; Ameli Hassan et al, 2012). For this research, three variables contribute to density. One is Buffer Floor Area Ratio (FAR), computed as total gross building area divided by total area for all parcels within a quarter mile buffer. Another is Block Face Floor Area Ratio of Block Face (BLKFAR) calculated by total gross building area for parcels abutting the street divided by total area of the parcel.

The third variable is Buffer Population Density (POPDEN) which considers the population of all census blocks whose centroids are within a quarter mile buffer for each block face divided by the total area of residential lots whose centroids are within the determined buffer (Ameli, S. H., Hamidi, S., et al, 2015).

Entropy as a measure of diversity- which determines mix of uses in a quarter mile buffer around each block face- is calculated with the following formula: Entropy =(-(Residential Share × LN (Residential Share) + Retail Share × LN (Retail Share) + office Share × LN (Office Share))/ LN (3). (Ameli, S. H., Hamidi, S., et al, 2015)

IV. Destination Accessibility This variable is represented by Walk Scores (WLKSCR) and Block Face Proportion of Retail (BLKRET). Walk Scores (WLKSCR) has for each block face has been developed through Walk Score.com, which is a platform which provides walkability rating for a specific address on a scale of 0 to 100. This platform rates each address based on number of stores and amenities within a one mile radius. (Rauterkus, S., Y., G. Thrall, et al, 2010). The amenities considered are drug stores, restaurants, bars, coffee shops, theatres, schools, libraries, book stores, hardware stores, music stores, clothing shops, parks, grocery stores and coffee shops (Carr, L. J., S. I. Dunsiger, and B. H. Marcus, 2011).

For this study, the address for each block face center points retrieved using Google Map were used in Walk Score platform to get a score for each segment (Ameli, S. H., Hamidi, S., et al, 2015).

Downtown Dallas Walkability Study | 37

Chapter 6

Finally, Block Face Proportion of Retail (BLKRET) consider the proportion of retail frontage along each block face.

V. Distance to Transit This variable is calculated using Network Analyst (ESRI 2010), for which road network and transit stations shape ďŹ les have been employed. To do this analysis, the center point for each segment has been determined as an incident, and passenger rail stations have been determined as facility location. Network Analyst (closest facility) provides the shortest distance for each block face center point to the closest rail station in feet (Ameli, S. H., Hamidi, S., et al, 2015).

VI. Demographics

Figure 1: Sample of Address with walk score information

38 | Downtown Dallas Walkability Study

Source 1: (Walk Score, n.d.)

This variable considers Household Size (HHSIZE). Average household size for each census block was downloaded from National Historical Geographic Information System (NHGIS). Census blocks whose centroids are in the quarter mile buffer were considered for each segment (Ameli, S. H., Hamidi, S., et al, 2015).

Chapter 6

VII. Employment Concentration For Employment Concentration, the data has been extracted from Longitudinal Employer-Household Dynamics (LEHD) which is part of US Census Bureau Center for Economic Studies and produces new information on employment.

(Longitudinal Employer-Household Dynamics, n.d.) For the purpose of this study, the number of employments has been considered in a quarter mile buffer around each block face.

Variables

Metrics

Computations

Buffer oor area ratio (FAR)

Total gross building area divided by total area for all parcels within a quarter mile buffer

Block face oor area ratio of block face (BLKFAR)

Total gross building area for parcels abutting the street divided by total area of the parcel

Buffer population density (POPDEN)

Population of all census blocks whose centroids are within a quarter mile buffer for each block face divided by the total area of residential lots whose centroids are within the buffer

Buffer entropy (MIX)

Number of different land uses and the degree they have been balanced based on parcel land area in a quarter mile buffer

Block face entropy (BLKMIX)

Number of different land uses and the degree to which they are balanced in land area for parcels abutting the street

Buffer intersection density (INTDEN)

Number of intersections within a quarter mile buffer from each block face divided by area of the buffer

Buffer proportion four way intersections (PCT4WY)

Proportion of four way intersections in a quarter mile buffer from each block face

Block length(BLKLNGH)

Length of each block face in feet

Walks core(WLKSCR)

Walk score for the center point of each block face

Block face proportion of retail (BLKRET)

Proportion of retail frontage along each block face

Distance to Transit

Distance to transit (TRANSITDIS)

Distance of each block face center point to the closet rail stations using ESRI Network Analyst

Demographic

Household size(HHSIZE)

Census block average household size calculated within a quarter mile buffer around each block face

Employment Concentration

Number of employment

Census block employment numbers within a quarter mile buffer around each block face

Number of Parks

Number of parks

Number of parks within a quarter mile buffer around each block face

Density

Diversity

VIII. Park Proximity This variable represents the number of parks in a quarter mile buffer for each segment.

Design

Destination Accessibility

Table 8: GIS variables, metrics and their measurements Source: (Ameli, S. H., Hamidi, S., et al, 2015)

Downtown Dallas Walkability Study | 39

DOWNTOWN DALLAS WALKABILITY STUDY

CHAPTER

40 | Downtown Dallas Walkability Study

7

CHAPTER

7

Analysis and Results a. Urban Design Features i. Imageability ii. Enclosure iii. Human Scale iv. Transparency v. Complexity vi. Control Variables

b. GIS Variables i. Density ii. Design iii. Diversity iv. Destination Accessibility v. Distance to Transit vi. Demographics vii. Employment Concentration viii. Park Proximity

Analysis and Results A summary of our data collection is discussed in the ďŹ rst part of this chapter. Later in this chapter, we discussed a summary of GIS data computed for the study area.

Downtown Dallas Walkability Study | 41

Chapter 7

7.A Urban Design Features As it is explained in previous chapter, downtown Dallas walkability data is divided to two categories, field variables and GIS variables.

Field data includes urban design variables and control variables which were collected in evening peak hours, 5PM to 7PM, in downtown Dallas.

I. Imageability As we already discussed in previous chapter, imageability refers to the quality and attractiveness of an area. For this study, we calculated the imageability score for each street block face in the downtown Dallas study area by evaluating specific physical elements and their arrangement, which captures attention and generates an enduring impression. Based on our findings, the north side of Elm Street from N Ervay to N Akard has the highest imageability, with the total score of 12.214. This score is the sum of all the scores calculated for different components of imageability, such as number of plazas and parks, the number of buildings with identifiers or number of non-rectangular buildings, etc. One plaza, 9 buildings which can be easily identified by their signage, along with 3 non rectangular buildings all contribute to attract more pedestrians in this part of Elm St. Looking at the figure 7.1. shows the concentration of the high imageability scores around the downtown core.

The other two segments with the high score of imageability are parallel to this segment of Elm along Commerce and Main St. The imageability score for these segments is 8.6 and 8.21, respectively, which shows a noticeable decrease from the Elm Street segment.

Looking at the components of imageability shows that the major difference between these segments and others with lower imageability score is the number of pedestrians. The reason is the

42 | Downtown Dallas Walkability Study

concentration of office buildings in this part of downtown which increases the number of pedestrians, especially in evening peak hours between 5 and 7pm. At this time, everyone is off the work and heading to their cars. lthis number is even higher for Elm because Elm has a considerable number of parking entrances and exits compare to other parallel streets, so people use Elm to walk to parking lots which adds to the number of pedestrians in this section of downtown.

The other two segments with high imageability score are on Bryan St. The first is the segment between N Ervay and N Akard. This segment has several characteristics of imageability, like different plazas, landscape features, identifiable buildings and outdoor dining, which all make this segment pleasant for walking. The other segment is between Harwood and St. Paul St on Bryan. This segment has a high number of pedestrians as well as a plaza. The important note is the presence of St. Paul station and the office buildings in this segment which adds to the number of pedestrians.

Figure 7-1 Imageability Scores across Downtown Dallas

Walkability Study | 02 Downtown Dallas Dallas Walkability Study | 43

Chapter 7 The lowest imageability score belongs to the segment of Young St. between S Ervay and S St. Paul St. The attained score for each block face of this segment is approximately 1.85. The reason is that this segment not only does not have any components of imageability, but also there is construction on the south side of the street which increases the noise level and influences imageability negatively, and there is a surface parking on the north side of the street, which affects the number of pedestrians in this segment.

Other segments with lower levels of imageability are on Federal St. between N Olive St and N Harwood St. and on Ross St. between Arts Plaza and N Central Express, with imageability scores of 1.91 and 1.94 respectively. The reason for the low imageability scores in

Figure 7-2a High Imageability Score

44 | Downtown Dallas Walkability Study

this segment of the Federal St. is the presence of a skywalk which connects the buildings in this area and negatively influences the number of pedestrians. Beside the presence of a surface parking lot, this segment also doesn’t have any components of imageability which can contribute to a higher imageability score. In the case of Ross St. between Arts Plaza and N Central Express, the reason for the low imageability score is the high noise level which is cause by its location next to a major highway in addition to the lack of any building, park or plaza or any other component of imageability.

Figure 7-2b Low Imageability Score

Chapter 7

Table 7.1a and 7.1b show our findings related to imageability in segments with highest and lowest imageability score.

Code Street Name From To 1. number of courtyards, plazas, and parks (both sides, within study area) 2. number of major landscape features (both sides, beyond study area) 3. proportion historic building frontage (both sides, within study area) 4. number of buildings with identifiers (both sides, within study area) 5. number of buildings with non‐rectangular shapes (both sides, within study area)

High Score 1143L 2122L Elm St Commerce St N Ervay St S Ervay St N Akard St S Akard St

3175R Bryan St North St. Paul St N Harwood St

2133R Main St S Akard St S Ervay St

3173L Bryan St N Ervay St N Akard St

1

1

1

2

4

0

1

0

1

2

0.2

0.3

0

0

0

9

4

0

17

4

3

4

0

9

1

6. presence of outdoor dining (your side, within study area)

0

1

0

1

1

7. number of people (your side, within study area) 8.Noise Range Imageability Score

433 4 12.214

203 4 8.601

298 3 8.27

77 3 8.21

94 3 8.02

Table 7-1a Highest Imageability Scores

Downtown Dallas Walkability Study | 45

Chapter 7

Low Score 299L Young St South St. Paul St S Ervay St

299R Young St S Ervay St Evergreen St

3172L Ross St Arts Plaza N Central Express

3181L Federal St N Olive St N Harwood St

0

0

0

0

0

0

0

0

0

0

0

0

0

0

0

1

0

0

0

0

6. presence of outdoor dining (your side, within study area)

0

0

0

0

7. number of people (your side, within study area) 8.Noise Range Imageability Score

7 4 1.86

6 4 1.84

2 3 1.94

4 4 1.91

Code Street Name From To 1. number of courtyards, plazas, and parks (both sides, within study area) 2. number of major landscape features (both sides, beyond study area) 3. proportion historic building frontage (both sides, within study area) 4. number of buildings with identifiers (both sides, within study area) 5. number of buildings with non‐rectangular shapes (both sides, within study area)

Table 7-1b Lowest Imageability Scores

46 | Downtown Dallas Walkability Study

Chapter 7

II. Enclosure As we already discussed in the previous chapter, enclosure represents the degree to which streets and other public spaces are visually defined by vertical elements like buildings, trees, walls and etc. Figure 7.3. shows the concentration of the high scores of enclosure around the downtown core. The highest score for enclosure belongs to Bryan St. between N Olive St and N Harwood St. at 4.23. The segment with the next highest score for enclosure is Pacific St. between N Field St and N Akard St with the score of 4.08.

In both these segments, the proportion of the street wall on both sides is 1, which means that there are no openings and the street is fully enclosed by the walls. The only difference here is that on the Pacific St. segment, we have greater openness to the sky, which decreases the enclosure level in this segment.

Segments with lower enclosure scores are mostly spread on the edges of the study area. Figure 7.3. shows different levels of enclosure, with darker shades indicating higher levels of enclosure and lighter shades indicating lower level enclosure scores. The lowest score for enclosure belongs to S Pearl St between Elm and Pacific St. with the score of -0.526. This segment has two surface parking lots on both sides and no buildings around and no street wall, with full sky visible overhead on the sides which all leads to a higher and lowest level of enclosure. The other block face with the lowest level of enclosure is the north side of Commerce St. between S Harwood and S St. Paul St. with the enclosure score of -0.378. Presence of a park on this segments is the reason for low enclosure score as it gives open view to the surrounding area and sky ahead and lower the level of enclosure in this block face.

Another segment with a high enclosure score is N Olive St. between Live Oak St. and Bryan St., with the average enclosure score of 3.98.

In this segment, almost 90% of the street is enclosed with walls on both sides. Two skywalks which connect the buildings on the both sides contributes to more enclosure in this segment of Olive St. by blocking the sky ahead. On the west side of North St. Paul between San Jacinto and Ross St. and west side of N Akard St between Main and Elm St., although a pedestrian can easily see 3 blocks ahead in both sides, the street is 100% enclosed with walls on both sides, leading to high enclosure score. The enclosure score for these two segments is 3.92.

Downtown Dallas Walkability Study | 47

Figure 7-3 Enclosure Scores across Downtown Dallas

0748 | Dallas Walkability Study | Downtown Dallas

Walkability Study

Chapter 7

The other two segments with the lowest level of enclosure are on the east side of S Harwood between Taylor and Marilla St. and on the north side of Pacific between N Olive and S Pearl St with enclosure scores of -0.255 and -0.165 respectively. The first location includes parking lots and outdoor dining with minimum street wall on both side of the street and a great proportion of sky ahead and on the

Figure 7-4a High Enclosure Score

sides. The latter location has a park on the north side and a surface parking lot on south side. Although there are some buildings visible on the south side of the street, they do not block the sky on the area.

Table 7.2a and 7.2b show our findings related to enclosure in segments with highest and lowest enclosure score.

Figure 7-4b Low Enclosure Score

Downtown Dallas Walkability Study | 49

Chapter 7

Code 249L Street Name N Akard St From Elm St To Main St 1. number of long sight lines (both sides, beyond study 1 area) 2a. proportion street wall (your side, within study 1 2b. proportion street wall (opposite side, within study 1 area) 3a. proportion sky (ahead, beyond study area) 0 3b. proportion sky (across, beyond study area) 0 Enclosure Score 3.92 Table 7-2a Highest Enclosure Scores

50 | Downtown Dallas Walkability Study

High Score Enclosure 362L 376L North St. Paul St N Olive St Ross Ave Bryan St San Jacinto St Live Oak St

376R 3151L 3151R 3176L 3176R N Olive St Pacific St Pacific St Bryan St Bryan St Live Oak St N Akard St N Field St N Olive St N Harwood St Bryan St N Field St N Akard St N Harwood St N Olive St

1

0

0

0

0

0

0

1

0.9

0.8

1

1

1

1

1

0.8

0.9

1

1

1

1

0 0 3.92

0 0 3.97

0 0 3.992

0.1 0 4.088

0.1 0 4.088

0 0 4.23

0 0 4.23

Chapter 7

Low Score Enclosure Code 383L 2124L Street Name S Pearl St Commerce St From Pacific Ave S Harwood St To Elm St South St. Paul St 1. number of long sight lines (both sides, beyond study 3 3 area) 2a. proportion street wall (your side, within study area) 2b. proportion street wall (opposite side, within study area) 3a. proportion sky (ahead, beyond study area) 3b. proportion sky (across, beyond study area) Enclosure Score

289R S Harwood St Taylor St Marilla St

3156R Pacific St N Olive St S Pearl St

3

3

0

0.6

0.5

0

0

0

0

0

0.6 0.6 ‐0.526

0.8 0.6 ‐0.378

0.2 0.9 ‐0.255

0.5 0.5 ‐0.165

Table 7-2b Lowest Enclosure Scores

Downtown Dallas Walkability Study | 51

Chapter 7

III. Human Scale Human scale factors consist of size, texture and other physical elements that match with the size and proportion of people and can influence people’s speed of walking. For this factor, street segments with the highest human scale score are spreading around downtown. Figure 7.5. shows the location of the highest and lowest scores of human scale. Pacific St between N Field St and N Akard St. This segment is only designed for pedestrians who wants to use Akard Station, so all the elements are designed to accommodate light rail users and pedestrians. Different seats and shadings, furniture and trees as well as wide sidewalks and lower building heights has made this segment more human size. Also majority of buildings’ façade is window on both side which contributes to humanizing this segment.

Human Scale score for this segment is 5.589.

The other segment with high human scale score is in east side of N Harwood between Federal and San Jacinto St with the human scale score of 5.274. This block face has several street furniture, seats and tables beside moderate building heights. The proportion of windows on the street level is also an important factor in increasing human scale score in this section. North Block faces of main between between N Akard and Stone PL, and N Field and Exchange Pl also have high human scale scores too, 4.51 and 4.481. This two segments have high proportion of window on street level, buildings with lower height and several street furniture which contribute to humanizing these two block faces. In Marilla St. between S pearl and S Harwood, beside the low height of building which has a strong

52 | Downtown Dallas Walkability Study

influence in making an area more human scaled, there is a plant garden (Ruibal’s Plant of Texas) in northern side of the segment with a wide sidewalk full of flowers, trees and plants which is an important factor in achieving high human scale score, 4.122 for this segment.

In the bottom of the human scale score table, east side of Lamar between Main and Elm St has the lowest score of -1.253. The most important factors which negatively influence human scale score are high height of the building on the block face and openness of the surrounding area. Beside these, this segment only has few street furniture and no small planter which all decreases human scale score for this segment. The other segment with low human scale score is in south side of Young between Market and Lamar St with the score of -0.026. Again, the high height of the street, lack of planters and appropriate number of street furniture, openness of the surrounding area led to low human scale score for this segment. In north side of San Jacinto between N Olive St and N Pearl St, same factors decrease the human scale score of -0.014.

Table 7.3a and 7.3b show our findings related to human scale in segments with highest and lowest Human Scale score.

Figure 7-5 Human Scale Scores across Downtown Dallas

Downtown Dallas Walkability Study | 53

Chapter 7

Figure 7-6a High Human Scale Score

Code Street Name

Figure 7-6b Low Human Scale Score

High Score Human Scale 2189L 360L North St. Paul Marilla St St

2132L1

2133L1

372R

3151L

Main St

Main St

N Harwood St

Pacific St

From

S Pearl St

San Jacinto St

Exchange Pl

To 1. number of long sight lines (both sides, beyond study area) *from above 2. proportion windows at street level (your side, within study area) 3. average building height (your side, within study area) 4. number of small planters (your side, within study area) 5. number of pieces of street furniture and other street items (your side, within study area) Human Scale Score

S Harwood St

Federal St

3

Table 7-3a Highest Human Scale Scores

54 | Downtown Dallas Walkability Study

S Akard St San Jacinto St

N Akard St

N Field St

Stone PL

Federal St

N Field St

1

1

1

1

0

0.4

0.8

0.9

0.8

0.4

0.9

26 57

32 0

198 22

80 12

52 0

37 2

13

37

28

35

78

50

4.122

4.134

4.486

4.51

5.274

5.589

Chapter 7

Low Score Human Scale Code Street Name From To 1. number of long sight lines (both sides, beyond study area) *from above 2. proportion windows at street level (your side, within study area) 3. average building height (your side, within study area) 4. number of small planters (your side, within study area) 5. number of pieces of street furniture and other street items (your side, within study area) Human Scale Score

131R N Lamar St Main St Elm St

194R Young St S Market St S Lamar St

3186L San Jacinto St N Pearl St N Olive St

3

3

3

0.8

0

0.4

921 0

312 0

468 0

6

13

14

‐1.253

‐0.026

‐0.014

Table 7-3b Lowest Human Scale Scores

Downtown Dallas Walkability Study | 55

Chapter 7

IV. Transparency Here the transparency is defined as the degree people can see beyond the edge of the street. Walls, doors, windows, door, landscape features and etc. are influential in degree of transparency. In this study we measured 3 predefined components of transparency to calculate the transparency score for each street segment, proportion of windows on street level, proportion of the street wall and active uses in the block face. A schematic result of Transparency score for each block face in downtown Dallas is shown in the figure 7.7. Looking at this figure shows the concentration of highest transparency scores around the business core of the downtown and also spread across the study area. The highest transparency score belongs to east side of N St. Paul between Wenchell Ln and San Jacinto PL. 90 % of this block face is covered by glass walls of a family center building. Transparency score for this block face is 4.063.

Figure 7-8a High Transparency Score

56 | Downtown Dallas Walkability Study

Other block faces with high transparency score are in South side of Elm between N Lamar and N Griffin St with the transparency score of 3.996 and east side of N Harwood between Federal and Bryan St with the score of 3.941. Although the block face in Elm has 80% of street wall but the wall is fully window with an active use which all increases the transparency score in this block face. The east side of Harwood is also an active use fully covered with street wall with 90% of windows on street level which all contributes to more transparency in this block face.

Block faces with lowest transparency are shown in table 7.4b with transparency score of 1.71. All these block faces are surface parking and do not have three measurements of transparency.

Figure 7-8b Low Transparency Score

Figure 7-7 Transparency Scores across Downtown Dallas

Downtown Dallas Walkability Study | 57

Chapter 7

Table 7.4a and 7.4b show our findings related to transparency in segments with highest and lowest Transparency score.

High Score Transparency Code Street Name From To 1. proportion windows at street level (your side, within study area) 2. proportion street wall (your side, beyond study area) *from above 3. proportion active uses (your side, within study area) Transparency Score Table 7-4a Highest Transparency Scores

58 | Downtown Dallas Walkability Study

371R 1140R N Harwood Elm St St Bryan St N Lamar St

360R2 North St. Paul St Wenchell Ln

Federal St

N Griffin St

San Jacinto PL

0.9

1

1

0.9

0.8

0.9

1 3.941

1 3.996

1 4.063

Chapter 7

Code Street Name

Low Score Transparency 280R S Pearl St

3155R Pacific St N Harwood St

3156R Pacific St

From

Jackson St

To

Commerce St

N Olive St

S Pearl St

0

0

0

0

0

0

0

0

0

0

0 1.71

0 1.71

0 1.71

0 1.71

0 1.71

1. proportion windows at street level (your side, within study area) 2. proportion street wall (your side, beyond study area) *from above 3. proportion active uses (your side, within study area) Transparency Score

N Olive St

383L 383R S Pearl St S Pearl St Pacific Elm St Ave Pacific Elm St Ave

Table 7-4b Lowest Transparency Scores

Downtown Dallas Walkability Study | 59

Chapter 7

V. Complexity As we discussed in the previous chapter, complexity implies the visual richness of an area and it is influenced by the diversity of physical elements such as number of buildings, architectural elements, public art, and etc. In our study area, as it is shown in figure 7.9. the street segments with the highest score of complexity are dispersed across the study area.

this segment contributed to complexity of this block face. The north block face of this segment has complexity score of 13.81. This difference is because of number of pedestrians in each side which is higher in south side. The west side of N Arkard St between Elm and Pacific has complexity score of 13.71. This segment has high number of pedestrians, accent and basic building colors but less number of buildings in compare to the previous block faces.

The highest score achieved for the complexity belongs to the north side of Elm St. between N Ervay and N Arkard with the total score of 19.13. Pedestrians walking in this segment have the view to 20 buildings with 4 basic colors and 11 accent colors which contributes to complexity in this segment. They also have view to the giant eyeball. Although the main face of this art piece is to Main St, but still it adds to the visual attraction of this segment. Number of pedestrian is also an important factor which influences complexity of a segment. This segment, north side of Elm St. between N Ervay and N Arkard, have the highest number of pedestrians too, 433 persons passing during the study hours.

The interesting point is that, as the number of pedestrians in this segment is considerably higher than any other segment in the study area, it led to a significant difference between complexity scores of this segment and the second one in the complexity list. The second highest score for complexity is 14.4 belongs to south side of Bryan St. between N St. Paul and N Harwood St. This segment has also view to several buildings in downtown, variety of accent colors and diversity of basic building colors. In addition high number of pedestrians because of St. Paul Station and office buildings in Figure 7-10a High Complexity Score

60 | Downtown Dallas Walkability Study

Figure 7-9 Complexity Scores across Downtown Dallas

Downtown Dallas Walkability Study | 61

Chapter 7

The lowest score of complexity belongs to east block face of S Austin between Commerce and Main St with complexity score of 4.09. This block face has lowest number of basic building colors and accent colors as well as low number of visible buildings in addition to low number of pedestrians which all lead to low complexity score.

Other block faces with low complexity score are east block face of S Record St between Young and Wood St. with the score of 4.2 and west side of Park Ave. between Cadiz and Corsicana St with the score of 4.21. These two block faces also have low level of accent and basic building colors and also pedestrians. South block face of Live Oaks between N Olive and N Pearl has low complexity score of 4.44. This block face has view to 5 buildings in horizon. It has total number of 9 accent and basic building colors and 13 pedestrians were passing during the study time. The mutual characteristics between all of these is that none of them has any piece of public art or outdoor dining.

Table 7.5a and 7.5b show our ďŹ ndings related to complexity in segments with highest and lowest complexity score.

Figure 7-10b Low Complexity Score

62 | Downtown Dallas Walkability Study

Chapter 7

High Score Complexity Code Street Name From To 1. number of buildings (both sides, beyond study area) 2a.number of basic building colors (both sides, beyond study area) 2b. number of basic accent colors (both sides, beyond study area) 3. presence of outdoor dining (your side, within study area) *from above

3175L Bryan St

3175R Bryan St

N Harwood St North St. Paul St North St. Paul St N Harwood St 11 11

1143L Elm St N Ervay St N Akard St 20

5

3

4

11

11

11

0

0

0

4. number of pieces of public art (both sdies, within study area)

1

1

1

5. number of walking pedestrians (your side, within study area) Complexity Score

263 13.81

298 14.4

433 19.13

Table 7-4b Lowest Transparency Scores

Downtown Dallas Walkability Study | 63

Chapter 7

Low Score Complexity Code 124R Street Name S Austin St From Commerce St To Main St 1. number of buildings (both sides, beyond study area) 6 2a.number of basic building colors (both sides, beyond study 2 area) 2b. number of basic accent colors (both sides, beyond study 4 area) 3. presence of outdoor dining (your side, within study area) 0 *from above 4. number of pieces of public art (both sdies, within study 0 area) 5. number of walking pedestrians (your side, within study 8 area) Complexity Score 4.09 Table 7-5b Lowest Complexity Scores

64 | Downtown Dallas Walkability Study

18R S Record St Young St Wood St 6

290L Park Ave Cadiz St Corsicana St 6

3193R Live Oaks Street N Olive St N Pearl St 5

3

2

1

5

5

8

0

0

0

0

0

0

0

8

13

4.2

4.21

4.44

Chapter 7

VI.Control Variables

This section covers the result of the study for other control variables that has been added to this study based on the usage of the climate, safety and design of sidewalks in Downtown Dallas. The considered variables are, width of sidewalk, number of homeless, number of active patio, and proportion of covered sidewalks.

6.1 Active Patio Most of the considered block faces in the study area does not have active patio. Streets such as Lamar, Griffin, Houston St, Young St, Wood St, Jackson St, Commerce St, Marilla St, Field St, Harwood St, Pearl St, Park Ave, Ross St., Bryan St., Federal St, San Jacinto St, Live Oaks Street does not have patio all along them; however there are some in which patios are active including Main, Pacific, Market, Akard, Saint Paul and Bryan St. Table 7.6 includes the highest number of patios. Moreover, Figure 7.11 show the picture of a block face with patio concentration and Figure 7.12 shows the concentration of patio in the whole study area.

Figure 7-11 Highest Number of Active Patio

09 | Dallas Walkability Study

Low Score High Score

Code

Street Name

From

To

Number Of Active Patios

1130L 1130R 120L 120R 2132L1

Main St Main St N Market St N Market St Main St

N Griffin St S Lamar St Ross Ave Pacific Ave Exchange Pl

N Lamar St N Griffin St Pacific Ave Ross Ave N Field St

0 0 3 3 3

Table 7-6 Highest Numbers of Active Patio

Figure 7-12 Number of Active Patio in the Study Area

Downtown Dallas Walkability Study | 65

Chapter 7 6.2 Width of Sidewalk Considering this variable, two block faces do not have any sidewalk suitable for pedestrian activities. Both are located in Marilla St.; however, there are a number of other sidewalks in which the width is not enough to encourage walkability or parking is part of sidewalk which is not safe for walking pedestrians. However, there are some wide sidewalks in the study area including Elm and North Saint Paul Street.

Table 7.7 lists the high and low scores for this factor.

Low Score

High Score

Code

Street Name

From

To

2187R 2188R 291R 290L 1107L 1141R 256L

Marilla St Marilla St Park Ave Park Ave Wood St Elm St North St. Paul St

South St. Paul St Park Ave Cadiz St Cadiz St Austin St Field St Elm St

Park Ave Harwood St Marilla St Corsicana St Market St Griffin St Main St

Width of sidewalk (feet) 0 0 3 4 46 71 85

Figure 7-13.a Block Face with Width Sidewalk in the Study Area

Table 7-7 Width of Sidewalk, High and Low Score

Figure 7.13.a shows an example of largest side walk and 7.13.b is an example of a low scored value for width of side walk in the study area.

Figure 7-13.b Block Face with Narrow Sidewalk in the Study Area

66 | Downtown Dallas Walkability Study

Dallas Walkability Study | 10

Chapter 7 This study determines block faces in which there are lots of homeless individuals, mostly concentrated around transit stations. N Lamar St which is close to transit station is the most attractive block face for them. Another attractive block face for them would be Pacific St from Lamar to Market and Lamer to Griffin. Table 7.8 shows the block faces with highest number of homeless people in the study area.

High Score

Code

Street Name

From

To

1148L 1149R 133R1 133R2

Pacific St Pacific St N Lamar St N Lamar St

N Lamar St N Lamar St Pacific Ave San Jancinto

N Market St N Griffin St San Jancinto Ross Ave

Table 7-8 Highest Number of Homeless People

Number of homeless people 26 23 20 35

Figure 7.15 shows an example of block face with highest number of homeless people. Moreover, figure 7.16 shows their concentration in the study area.

Figure 7-14 Study Area Width of Sidewalk

6.3 Homeless People One of the issues in central Dallas is the number of homeless people which is contributed to the crime in this area.

“Their presence contributes to the perception that neighborhoods are unsafe; they can be a detriment to investment and revitalization efforts.” (Simek, 2015) Figure 7-15 Example of Block Face with Highest Number of Homeless People

Downtown Dallas Walkability Study | 67

Chapter 7

Table 7.9 list the sidewalks which is fully covered and some others with no trees or buildings covers. Figure 7.17 is an example of high score for covered sidewalks and figure 7.18 shows the proportion of covered sidewalks in the study area.

Low score

High Score

Figure 7-16 Number of Homeless People in the Study Area

6.4 Covered Sidewalk (Street Canopy) One of the elements that might discourage walkability in is lack of covered sidewalk. Covered sidewalk helps pedestrians enjoy their walking activities and encourage them to stay in the place. Coved sidewalks in Downtown Dallas are mostly seen in Bryan, Akard, Saint Paul and Harwood as a result of tall buildings or presence of trees to provide shades. However there are some in which lack of it is evident such as Ross and Pearl Streets.

68 | Downtown Dallas Walkability Study

Code

Street Name

From

To

368R 374L 3173L 3176L 350L 350R 353L 357L 358L 371L 372R 376L

N Harwood St N Olive St Bryan St Bryan St N Akard St N Akard St N Ervay St North St. Paul St North St. Paul St N Harwood St N Harwood St N Olive St

Elm St Pacific Ave N Ervay St N Olive St Pacific Ave Elm St Pacific Ave Pacific Ave Bryan St Federal St San Jacinto St Bryan St

Pacific Ave Elm St N Akard St N Harwood St Elm St Pacific Ave Elm St Elm St Pacific Ave Bryan St Federal St Live Oak St

Table 7-9 Proportion of Covered Sidewalks, High and Low

Proportion of covered sidewalk 0 0 1 1 1 1 1 1 1 1 1 1

Chapter 7

Figure 7-17 Example of High Score on Covered Sidewalk Figure 7-18 Proportion of Covered Sidewalks in the Study Area

Downtown Dallas Walkability Study | 69

Chapter 7

7.B GIS Data Variables GIS data variables has been measured using GIS ARC V10.4 using raw data from a variety of sources. Below, the analysis for each variable has been provided.

I. Density Density is quantified based on three variables, namely Buffer Floor Area Ratio (FAR), Block Face Floor Area Ratio of Block Face (BLKFAR) and Buffer Population Density (POPDEN) which are explained below.

1.1. Buffer Floor Area Ratio (FAR) Based on the result, block face 3172L, located in Ross Street from Arts Plaza to N Central Express, shows the lowest score for FAR. However, the highest score for FAR are in North St. Paul St (360R1) from Federal St to Wenchell Ln (8.73).

Code

Street Name

From

To

Lowest N Central 3172L Ross St Arts Plaza Score Express Highest 360R1 North St. Paul St Federal St Wenchell Ln Score Table 7-10 Buffer Floor Area Ratio (FAR) Highest and Lowest Score

1.2. Block Face Floor Area Ratio (BLKFAR) Considering this variable, 118 block faces have the lowest score of zero; however, there are 4 block faces with highest score (28.56). Table 7-1 provides the lists of block faces with highest scores.

Highest Score

Code

Street Name

From

To

BLK FAR

1130L 1140R 131R 139L

Main St Elm St N Lamar St N Griffin St

N Griffin St N Lamar St Main St Elm St

N Lamar St N Griffin St Elm St Main St

28.560 28.560 28.560 28.560

Table 7-11 Buffer Floor Area Ratio (FAR) Highest and Lowest Score

FAR 0.6700 8.730

Figure 7-21 BLKFAR Highest Scores

Figure 7-20.a Highest FAR Score

Figure 7-20.b Lowest FAR Score

70 | Downtown Dallas Walkability Study

Chapter 7

II. Design Three metrics for design variables are Buffer Intersection Density (INTDEN) and Buffer Proportion Four Way Intersections (PCT4WY) and Block Length (BLKLNGH), analyzed below.

2.1 Buffer Intersection Density (INTDEN) Based on the analyses for this variable, the lowest score is for S Houston St. from Wood St. to Young. In addition, San Jacinto St, from N Griffin St to N Lamar St has the highest score.

Lowest Score Highest Score

Code

StreetName

From

To

INTDEN

11L

S Houston St

Wood St

Young St

182.160

1182L

San Jacinto St

N Griffin St

N Lamar St

448.030

Table 7-13 Highest and Lowest Score for Buffer Intersection Density (INTDEN)

Figure 7-4 Block Face Floor Area Ratio of Block Face (BLKFAR)

1.3. Buffer Population Density ( POPDEN) For this variable, 32 block faces showed a value of zero but the highest value (0.046) belongs to Jackson Street from S Market Street to S Austin St.

Highest Score

Code

StreetName

From

To

POPDEN

1112R

Jackson St

S Market St

S Austin St

0.0465

Table 7-12 Highest Score for Buffer Population Density (POPDEN)

Figure 7-22 Buffer Intersection Density (INTDEN) High score

Downtown Dallas Walkability Study | 71

Chapter 7

2.3 Block Length (BLKLNGH)

Lowest Score Highest Score

Code

StreetName

From

To

BLKLENGTH

12L2

S Houston St

Reunion Turn

Jackson St

32.26

370R

N Harwood St

Live Oak St

Bryan St

1115.64

Table 7-15 Block Length Highest and Lowest Score

Measured through GIS, block length is one of the metric that affects the desire of pedestrian to walk through. Based on the measurement, N Harwood St from Live Oak St to Bryan St has the largest length while S Houston St from Reunion Turn to Jackson St offers the shortest block length

Figure 7-23 Buffer Intersection Density (INTDEN)

2.2 Buffer Proportion Four Way Intersections (PCT4WY) For this metrics, N Harwood from Main St to Elm St shows the highest score while Ross Street from Art Plaza to N Central Express has the lowest score.

Code Lowest Score Highest Score

StreetName

From

To

pct4way 0.330 0.790

3172L

Ross St

Arts Plaza

N Central Express

267R

N Harwood St

Main St

Elm St

Table 7-14 Highest and Lowest Score for Buffer Proportion Four Way Intersections

72 | Downtown Dallas Walkability Study

Figure 7-24 Largest Block in the Study Area

Chapter 7

III. Destination Accessibility This variable is being quantified through Walk Scores (WLKSCR) and Block Face Proportion of Retail (BLKRET).

3.1 Walk Scores (WLKSCR) The below table presents the highest and lowest score for walk score in the study area. The lowest score belongs to Young St from S Houston St to S Record St, while 8 block faces presents the highest score, mostly in Elm Street, Main and Akard Street. The walk score is based on the number of stores and amenities in one mile distance from the center of the location. This supports the importance of amenities such as corner markets, schools, restaurants, public parks and places of worship and pharmacies to encourage walkability among residents, which not only increases social interactions but also supports local businesses (Company 2014).

Code

StreetName

From

To

Walk score

Lowest Score

192R

Young St

S Houston St

S Record St

72

Highest Score

1142L 1142R2 1143R1 2132L2 2133L1 248L 249R 350L

Elm St Elm St Elm St Main St Main St S Akard St N Akard St N Akard St

N Akard St Exchange Pl N Akard St N Akard St S Akard St Main St Main St Pacific Ave

N Field St N Akard St Stone Pl Exchange Pl Stone PL Commerce St Elm St Elm St

98 98 98 98 98 98 98 98

Figure 7-25 Highest Walk score

Table 7-16 Highest and Lowest Block face Walk Score Figure 7-26 Walk Score of the Block Faces in Study Area

Downtown Dallas Walkability Study | 73

Chapter 7 3.2 Block Face Proportion of Retail (BLKRET) For this metrics, N Harwood from Main St to Elm St shows the highest score while Ross Street from Art Plaza to N Central Express has the lowest score.

Proportion of retail in block faces showed variations in numbers. With minimum of 0 and maximum of 1.032, it has a range of 1.03. The highest proportion of retail belongs to S Market St (from Jackson St to Wood St ), N Griffin (from Ross Ave to San Jacinto St) and , N Ervay St (from Pacific Ave to Elm St) .The importance of retail activities in walkability is determined through relating this proportions to walk score of the area.

These mentioned block faces shows high scores for walk score.

Highest Score

Code

StreetName

From

To

BLKRET

115L 142L 353L

S Market St N Griffin St N Ervay St

Jackson St Ross Ave Pacific Ave

Wood St San Jacinto St Elm St

1.01 1.03 1.02

However, S Harwood St from Marilla St to Taylor St has the largest distance to transit with less number of pedestrian in this area (12). These both support the role of transit station in creating a pedestrian-friendly environment.

Lowest Score Highest Score

Code

StreetName

From

To

Distance to transit stations

1148L

Pacific St

N Lamar St

N Market St

45.3230

289L

S Harwood St

Marilla St

Taylor St

3690.8398

Table 7-18 Largest and Shortest Distance to Transit Stations

Table 7-17 Block Face Proportion of Retail Highest Scores

IV. Distance to Transit Development of Dallas Area Rapid Transit’s light and commuter rail system in this city has improved the accessibility all over the region, which affects pedestrians and built environment. Therefore, another important factor for studying walkability in Downtown Dallas is distance to transit, measured through GIS. As the table shows, pacific Street (from Lamar St to Market St) has the shortest distance to transit stations. As an important factor in walkability, Pacific St shows the highest number of pedestrian activity (191 pedestrian counts) which is contributed mostly to the location of rail stations.

74 | Downtown Dallas Walkability Study

Figure 7-26 Block Face Shortest Distance to Transit Stations

Chapter 7

Figure 7-27 Block Face Longest Distance to Transit Stations

Diversity Creating a diverse area in term of mix land use can impact the desire to walk. In this report, diversity is measured through Buffer Mix Use (MIX) and Block Face Mix Use (BLKMIX).

4.1 Buffer Mix Use (MIX) A key fundamental ingredients to encourage walking is mixed land use which is associated with walking (Cervero R, Kockelman K 1997).

Figure 7-28 Distance to Transit for Each Block Face

Downtown Dallas Walkability Study | 75

Chapter 7

Lowest Score

Highest Score

Code

StreetName

From

To

Mix use (Entropy)

193L 192R 17L 17R 193R 192L 2115L 2115R

Young St Young St S Record St S Record St Young St Young St Jackson St Jackson St

S Market St S Houston St Young St Until Middle S Record St S Record St S Harwood St S Pearl St

S Record St S Record St Until Middle Young St S Market St S Houston St S Pearl St S Harwood St

0.02 0.02 0.02 0.02 0.02 0.02 0.99 0.99

Highest Score

Code

StreetName

From

To

Block Face Mixed Use

2125R

Commerce St

S Harwood St

S Pearl St

0.69

Table 7-21 Block Face Mix Use Highest Score

Table 7-19 Highest and Lowest Score for Mixed Use (Entropy)

The mixed use values for this study area has a minimum value of 0.02 to maximum of 0.99 with the range of 0.970. The average land use mix for study area is 0.50. Six block faces shows the lowest values for land use mix while two sides of Jackson Street from S Harwood Street to S Pearl Street have the highest score.

mix Valid N (listwise)

N

Range

Minimum

Maximum

Mean

Std. Deviation

402 402

0.970

0.020

0.990

0.50465

0.280861

Table 7-20 Descriptive Statistics of Mix land Use

4.2 Block Face Mix Use (BLKMIX) This metrics examines the land use mix in a quarter mile buffer from each block face. Commerce Street from S Harwood Street to S Pearl St shows the highest score for this metrics.

76 | Downtown Dallas Walkability Study

Figure 7-29 Block Face Mixed Use (Entropy)

Chapter 7

V. Demographics 5.1 Household Size (HHSIZE) For this variable, Average Household Size for blocks within a quarter mile buffer has been measured. Low values on average household sizes is mostly related to office concertation in the study area.

Code

StreetName

Lowest Score

3167R 3166L 193L 114L 192R 17L 113R 3167L 17R 193R 113L 192L 3168L1 3166R

Ross St Ross St Young St S Market St Young St S Record St S Market St Ross St S Record St Young St S Market St Young St Ross St Ross St

Highest Score

2133R

Main St

From

To

N Olive St N Pearl St N Olive St N Harwood St S Market St S Record St Wood St Young St S Houston St S Record St Young St Mid Record St Mid Market St Young St N Pearl St N Olive St Mid Record St Young St S Record St S Market St Young St Mid Market St S Record St S Houston St N Pearl St Crocket N Harwood St N Olive St S Akard St

S Ervay St

Lowest Score Highest Score

StreetName

From

To

EMPLOYMENT

2190L

Marilla St

S Cesar Chavez Blvd

S Pearl St

1036

360R2

North St. Paul St

Wenchell Ln

San Jacinto PL

39973

Table 7-24 Employment Concentration Highest and Lowest Values

Household Size 0 0 0 0 0 0 0 0 0 0 0 0 0 0

Code

Employment Valid N (listwise)

N

Range

Minimum

Maximum

Mean

Std. Deviation

402 402

38937.000

1036.000

39973.000

24665.9403

9576.43105

Table 7-25 Employment Concentration Descriptive Statistics

25.82

Table 7-22 Highest and Lowest Score for Household Size

VI. Employment Concentration Downtown Dallas is the location high rise office buildings with lots of employment centers. It offers an employment range of 38,937.

In average the study area offers 24,666 jobs. However the value for each block faces is varied. The least number of jobs are in Marilla Street quarter mile buffer and the most number of employments are concentrated in a quarter mile buffer of North St. Paul Street from Wenchell Ln to San Jancinto Pl.

Figure 7-30 Employment Concentration in Study Area

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Chapter 7

VII. Park Proximity The important role of the parks in encouraging walkability is evident.

Parks are location for physical activity and adds the opportunities for leisure activities (Dills, J. E., Rutt, C. D., et al. 2012). This study considers the number of parks in a quarter mile buffer from each block face. Based on that this model determines three block faces to have access to highest number of parks; both sides of Pacific Street from N Ervay St to North St. Paul St and Ross St from N Akard St to N Ervay St. However there are some with no access to parks in a quarter mile buffer which needs to be considered for any further policies.

Code Figure 7-31 Least Value for Employment Concentration

Highest Score

Lowest Score

Figure 7-32 Highest Value for Employment Concentration

78 | Downtown Dallas Walkability Study

StreetName

From

3153R

Pacific St

N Ervay St

3173R

Ross St

3153L

Pacific St

2187R

Marilla St

291R 2188R 291L 2188L 289R 2189R 2189L 289L 290R 290L

Park Ave Marilla St Park Ave Marilla St S Harwood St Marilla St Marilla St S Harwood St Park Ave Park Ave

N Akard St North St. Paul St South St. Paul St Cadiz St Park Ave Marilla St S Harwood St Taylor St S Harwood St S Pearl St Marilla St Corsicana St Cadiz St

2190R

Marilla St

S Pearl St

2187L

Marilla St

Park Ave

2190L

Marilla St

3172L 3171R

Ross St Ross St

S Cesar Chavez Blvd Arts Plaza Routh St

Table 7-26 Highest Score on Parks Proximity

To North St. Paul St N Ervay St N Ervay St

Park Proximity 15 15 15

Park Ave

0

Marilla St S Harwood St Cadiz St Park Ave Marilla St S Pearl St S Harwood St Taylor St Cadiz St Corsicana St S Cesar Chavez Blvd South St. Paul St

0 0 0 0 0 0 0 0 0 0

S Pearl St

0

N Central Arts Plaza

0 0

0 0

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Figure 7-35 Highest Score for Parks Proximity

Figure 7-33 Park Proximity in Study Area

Figure 7-34 Highest Score for Parks Proximity

Figure 7-36 Highest Score for Parks Proximity

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DOWNTOWN DALLAS WALKABILITY STUDY

CHAPTER

80 | Downtown Dallas Walkability Study

8

CHAPTER

8

Recommendations a. b. c. d. e.

Imageability Enclosure Human Scale Transparency Complexity

RECOMMENDATIONS

Based on the ďŹ ndings presented in previous chapters, this study suggests a comprehensive set of modiďŹ cations that range from easy, short-term, long-term, to affordable changes.

These changes will help to improve overall walkability, transportation, and livability in the downtown areas. Recommendations were integrated as a result of gathering both data and the City of Dallas Economy Development inputs. Therefore, it is hoped that all recommendations are going to be taken and implemented in order to have more walkable and livable downtown. As a general taking a look for the recommendation process, downtown streets and segments are going to be tuned or limited for vehicle travels and new conďŹ gurations will be needed to highlight the streets in order to encourage walking, biking, and pedestrian activity in downtown. As it can be seen in the data and overall report so far, many streets and segments are performing in a great way for providing walkable environment. On the other hand, many other streets are not promoting the walkability. At this point, this section is going to respond why some streets are not promoting walkability and what can be done in order to encourage pedestrians. To do this, many assists and helps are going to be taken from the streets and segments as well as from the data that are encouraging walkability.

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Chapter 8

8 Based on the findings presented in previous chapters, this study suggests a comprehensive set of modifications that range from easy, short-term, long-term, to affordable changes. These changes will help to improve overall walkability, transportation, and livability in the downtown areas. Recommendations were integrated as a result of gathering both data and the City of Dallas Economy Development inputs. Therefore, it is hoped that all recommendations are going to be taken and implemented in order to have more walkable and livable downtown. As a general taking a look for the recommendation process, downtown streets and segments are going to be tuned or limited for vehicle travels and new configurations will be needed to highlight the streets in order to encourage walking, biking, and pedestrian activity in downtown. As it can be seen in the data and overall report so far, many streets and segments are performing in a great way for providing walkable environment. On the other hand, many other streets are not promoting the walkability. At this point, this section is going to respond why some streets are not promoting walkability and what can be done in order to encourage pedestrians. To do this, many assists and helps are going to be taken from the streets and segments as well as from the data that are encouraging walkability.

The following sections demonstrate a list of recommendations in terms of both design and policy aspects. Thus, these conceptual and regulatory changes for many streets that are aimed to connect with each other and with the built environment appropriately. By doing this, having more walkable and livable objective that is one of the chief goals of this study will be achieved. In many streets, more than one strategy may be applied to accomplish for reaching more walkable downtown. After suggesting these recommendation, many inputs by related neighborhood communities such as commuters, pedestrians, residents and so on might be included for deciding and adopting process. The recommendations are divided five qualities into as we analyzed walkability study in these variables that are imageability, enclosure, human scale, transparency, and complexity.

82 | Downtown Dallas Walkability Study

i. Imageability a. Main Street Main Street is the historically located in the core of the city of Dallas with many commercial stores, hotels, banks, and residential. Even the core downtown was moved to the east during the time, Main Street remained as an influential profile of the downtown Dallas. In regard to the walkability study, Main Street has a substantial implication as it is two-way road as oppose to Elm Street (east to west direction) and Commerce Street (west to east direction) that will be discussed in a while.

In terms of imageability, Main Street has the highest score in the intersection of Akard Street and Main Street. The reason might be caused by the building of this intersection is served as bank (Chase Bank) and there is a grocery store (CVS). Apart from this location, Main street has overall highest score but a couple spots. To demonstrate it, the half segment of Field Street and Akard Street has the lowest imageability score along with Lamar Street and Market Street. Since imageability quality consists of number of courtyards, plazas, landscape features, identifiers, outdoor dining, and number of people, Main Street attempts to address these subcategories accordingly.

Since having number of outdoor dining places, number of historic

Figure 8-1 Main Street

Chapter 8

footprints, having courtyard, plazas, and many other reasons attract people’s activities, many segments are effectively walkable on Main Street. For the specific recommendation, Table 1 illustrates the broad spectrum recommendations for Main Street. Improvements to crosswalks that include signage to help to distinguish particularly the segment of Ervay and Akard Street as well as Lamar Street and Market Street. In addition to these segments, segment S.Pearl and S. Harwood need to be improved in terms of landscape features.

As it can be seen from the photos and site, these segments do not include enough features. So, site furniture such as bench, trash, trees might be added. Another reason of having low scores of these segments is having construction and having lack of width pedestrian walkways. Therefore, sidewalks should be repaired or extended for comfortable sidewalks. In terms of noise level, it is at the acceptable level for pedestrians as Main Street always has certain level of noise because of vehicles, constructions, festivals, and many other anthropogenic features. In addition, it is observed that pedestrians prefer to walk in places that have intentionally (plant or vegetation for parks) or unintentionally (metered parking spots) buffer zone. So, buffer zones for pedestrians should be taken into account to make pedestrians to walk safely, for instance, segment of N.Harwood Street and N.Pearl Street.

General Recommendations

Segments

Add signage at streets and intersections

2132 R, 2132 L1, 2132 L2, 1128 L, 1128 R1, 1128 R2

Add landscape feature (bench, trash bin, tree)

2136 L, 2136 R

Repair sidewalks

2133 R

Extend sidewalks

2131 L

Create buffer zone

21332133 R

Table 8.1. Recommendations for Main Street on Imageability

b. Elm Street Elm Street is located north parallel of the Main Street and it is only west thoroughfare. Compare to Main Street, Elm Street has lower score in terms of imageability. Overall, the segments between S. St.Paul Street and N.Lamar Street have the highest imageability score for the entire street. The reason of this high score might be caused by business and recreation centers in these segment, such as Comerica Bank, 1700 Pacific, Giant Eyeball, Renaissance Tower, Crowne Plaza, Bank of America Financial Center, and so on… Other segments are representing lower imageability score. Table 2 shows suggested recommendations for Elm Street. Since aforementioned segments include more business and commercial centers, they need to be added courtyards, plazas, and parks. Pocket parks are a great solution for these types of busy and crowded centers as Paley Park example in Manhattan. In addition, even there are many high-rise business centers in Elm Street, there are few landscape elements. So, it can be a great idea to include many features, such as waterways.

General Recommendations

Segments

Add plaza, courtyard, or park

1143 L, 1143 R1,R2

Add landscape feature (waterways)

1141 L, 1141 R

Repaint/Repair curb cuts

1146 L1, L2, 1146 R, 1143 R1, R2, 1142 L, 1142, R1, R2, 1139 L1, L2, 1139 R

Table 8.2. Recommendations for Elm Street on Imageability

c. Commerce Street Commerce Street also includes many landmark structures and other imageability components.Particularly between S. Ervay and S. Akard segment and intersection of S.Griffin Street and Commerce Street have the highest imageability score among other segments. Former segment includes Nieman Marcus department store, Magnolia Hotel, and other commercials. Besides, the segment includes many landscape features and appropriate signage for the pedestrians. The

Downtown Dallas Walkability Study | 83

Chapter 8 latter intersection has Earle Cabell Federal Building and Belo Garden. These two different programmed areas are expected to have many number of people for the entire time intervals. The garden side includes many benches and trees while the building side only has sphere shape stone bumpers. The reason might be the overall purpose of the building as the building has courthouse, US Army Corps of Engineering, US Bankruptcy Court, US District Court Clerk and so on… On the other hand, south face of the segment between S. Ervay and S. Harwood and south face of the segments between S. Houston Street and S. Griffin Street have the lowest imageability scores.

Former segment includes lack of landscape features while the latter one includes very few courtyard. Both lower scored segments need to be improved by some identifiers and landscape features such as landscape view. Since the main reason of having lower score for the former segments might be caused by lack of people and human activities and latter one may be caused by the construction works, these areas need to be attracted. The benches and particularly vegetation make the segments more pedestrian-friendly and they encourage persons to sit and or to get benefit from shadow.

Street/Arts District DART Light Rail station and it creates many imageability characteristics. The same pattern also can be observed in West End DART Light Rail station which is on Pacific Avenue, between N. Lamar and N. Market Street.

In addition to the three main arteria, there are some segments that have lowest and highest score for the imageability. For instance, while Live Oak Street in downtown Dallas boundary has the lowest score, just one parallel north -Bryan Street- has one of the highest scores. The essential reason of this situation is that there is Pearl

ii. Enclosure

General Recommendations

Segments

Add identifiers

1116 L1, L2, 1116 R, 1117 L, 1117 R 1118 L, 1118 R, 1119 L, 1119 R1,R2

Add landscape feature (plaza, park, pleasant view)

1116 R, 1117 R, 1118 R, 1119 R1, R2

Add landscape feature (bench and tree)

2124 R, 2124 L, 2123 L, 2123 R1, R2

Table 8.3. Recommendations for Commerce Street on Imageability

84 | Downtown Dallas Walkability Study

For the specifically at the study scale, the lowest scored segment which is Young Street between S. Ervay and Evergreen Street, there is a construction (south face) and a parking lot (north face) and the segment does not have any landscape features, historic building frontage, identifiers and even number of people are too few (just 6 observed). So, south side of the segment should be improved by many amenities as north face is parking lot and pedestrians are not willing to use this side because of the safety concerns. On the other hand, Elm Street between N. Ervay Street and N. Akard Street has the highest imageability score. Indeed, this segment are providing many features such as landscape features, historic building footprint, identifiers, outdoor dining, number of people and so on… As Jan Gehl highlights the importance of the imageability; in order to generate a remarkable impression life in the space and architectural quality assistance, sense of place is an important characteristic (Gehl, 1987).

a. Main Street Main Street has the overall highest score in terms of enclosure except the half segment of Houston and Market Street. The reason of having lower score in this segment is that there are open space and memorial site in both faces of the street. Even enclosure is lower in this segment, it is not affecting the quality of the space as there are trees and many other sculptural elements for enclosure and there is a monument for the memorial park. There are many design suggestions in regard to enclosure. The best known case was suggested

by Allan Jacobs (1993) is the proportion of building heights to street width should be at least 1:2 and this proportions is acceptable 3:2 to

Chapter 8

1:6. Since the buildings of Main Street and other streets in the downtown are high-rise, buildings are becoming more important and playing more dominant role. In Main Street, high-rise buildings and walls are providing spatial meaning for the pedestrians.

General Recommendations

Segments

Proportionate building heights

1128 L

Proportionate building walls

2131 L

Table 8.4. Recommendations for Main Street on Enclosure

b. Elm Street After having high score for Main Street, Elm Street has also high enclosure scores even it is not as high as Main Street. Since the Elm Street includes many high-rise buildings and commercial centers particularly in between N. Griffin and N. Harwood Street, the effects of enclosure such as feeling like in a room and surrounding effect can be observed easily. In addition, many non-active uses such as parking lots and some vacant and construction sites eliminates the effects of enclosure and it results in a lack of pedestrian activity in these “spots”. So, using vegetation or similar purpose sculptural elements may increase the enclosure effects in these dead spaces.

Particularly, the parking lot in the intersection of N. Market Street and Elm Street (north face), the parking lot in the intersection of N. Austin Street and Elm Street (north face), the parking lot in the intersection of N. Lamar Street and Elm Street (north face), the parking lot in the intersection of N. Griffin and Elm Street (south face), the parking lot in the of N. Olive Street and N. Pearl Street segment on Elm Street (north face) are such examples and they need to be improved.

General Recommendations

Segments

Use vegetation or sculptural element

1138 L, 1139L2, 1141 R, 1146 L2

Proportionate building walls

1139 R

Table 8.5. Recommendations for Elm Street on Enclosure

c. Commerce Street Commerce Street has different pattern in terms of enclosure as the score is not stable or clustering any particular location along with the street. Since the street includes many buildings with different heights and program elements along with the parking lots and open spaces, enclosure score fluctuates. While the segment between S. Ervay Street and S. Akard on Commerce Street has the highest score, the segment S. St. Paul and S. Harwood that is just a couple block distance from the previous segment has the lowest enclosure scores for both faces of the streets. As recommendations, lowest enclosure scored segments mostly parking lots or low-rise buildings should be improved by evergreen trees or other elements to create enclosure effects. Particularly south face of the S. Harwood and S. Pearl Street, both faces of S. Lamar and S. Griffin Street, and S. Market and S. Austin Street are required to add some elements in order to create safer, more defined, and even more memorable implications.

In addition to three main streets in the downtown, there are some other patterns for enclosure. To demonstrate it, N. and S. St. Paul Street has a high enclosure along with the corridor in downtown boundary. The corridor provides a great defined and surrounded sense of place. There are ideal form of trees, well situated walls and fences that are the key elements of the enclosure feelings in this street.

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Chapter 8

General Recommendations

Segments

Use vegetation or sculptural element

2125 R,1119 L, 1119 R1, R2, 1117 R

Proportionate building walls

2123 L,

Table 8.6. Recommendations for Commerce Street on Enclosure

iii. Human Scale a. Main Street Main Street also leads highest scores of human scale out of three main arteries. As human scale is highly related to physical elements that are about size, dimensions, and proportions, Main Street, particularly segment Paul Street and Field Street, has many features for human scale aspects. Since there are many various building usages such as restaurant (Jason’s Deli, Ravenna, and etc…), department store (Dallas Fish Market, Neiman Marcus, and so on…), grocery (CVS), banks (Chase) and many others, there are many tables, chairs, benches, planters and this ambiance provides human interaction more than other locations. Even there are high-rise buildings in the core downtown area, physical elements such as trees and other aforementioned elements provide human scaled places for walking and other activities. For specific recommendation, north face of the segment Griffin and Lamar Street should be improved by adding planters or bike racks.

b. Elm Street Elm Street has comparatively higher score for human scale. The street has highest level in between N. Harwood and N. Field Street, except the segment between N. Paul and N. Ervay Streets. There are literally nothing in terms of creating human scale elements except deciduous tree species that are not enough obviously. In addition, the exits of most parking garages of high-rise buildings that are located on Main Street and Elm Street are located through Elm Street. So, many garage exits do not have any human scale elements. What can be done is that other potential street segments might be used for those purposes.

Rest of the segments of Elm Street are at the quite low human scale score. In order to increase human scale qualities, there are many strategies. First and foremost, street signage for vehicles are designed larger in order to make them visible for drivers. However, these dimension of signs are larger for person’ scale and it bothers individual to have human scale walking environment. As there are many signage for drivers on Elm Street, particularly N. Akard and N. Field and N. Ervay and N. St. Paul Street, people cannot figure the human scale out. So, small signs with small fonts should be adopted in these kinds of segments for pedestrians. In addition, from N. Harwood Street to N. Ervay Street, there are few elements for human scale.

High-rise buildings along with wide cross sections, large fenestrations, and lack of portioning of facades prevent the feeling of ideal human scale even trees and other elements are helping to eliminate it.

General Recommendations

Segments

General Recommendations

Segments

Add street furniture

1130 L, 1130 R, 2131 L, 2134 L

Add small font signage

1142 L, 1144 L, 1144 R

Add bike racks

1130 L, 1130 R, 2131 L, 2134 L

Add vegetation

1145 L, 1144 L

Table 8.7. Recommendations for Main Street on Human Scale

86 | Downtown Dallas Walkability Study

Table 8.8. Recommendations for Elm Street on Human Scale

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c. Commerce Street Commerce Street does not have high score compare to other two main arteries. Surprisingly, Commerce Street is not human scaled in core downtown area –segment S. St. Paul and S. Akard Street- as oppose to other two streets. Actually there are many parking lots as dead places and buildings with lack of windows and openings to promote human scale. Since there are not that much human activity places such as restaurants and stores, the street also is lack of street furniture. Indeed, human feels that he or she gets stuck between buildings because of vertical element effect and huge parking lots as horizontally lost impact. There is another interesting point for Commerce Street and it has highest human scale scores in very ending of street that is between S. Houston and S. Lamar Street. As it can be seen, windows and furniture help people to feel in a comfortable zone in terms of human scale.

In addition to these essential streets, there are some positive and negative patterns about human scale. When we look at the human scale scores, the score is high in the block between Jackson Street (from north), Young Street (from south), S. Pearl Street (from east) and S. Harwood (from west). Apparently, this block provides many elements such as proportions for humans by building and trees. People are invited virtually by the texture and expressions of many physical elements. So, in this case building heights, street trees, width of the sidewalks are welcoming for walking in this block. Another interesting patterns is in “transportation corridor” that is Bryan Street and light rail stations. As it can be seen in this “corridor”, street furniture such as bench, bike rack, human scaled street lights, cantilever train stations, street clocks are helping people to perceive as human scale elements. All in all, it can suggested that existence of first floor windows, landscape furniture such as planter, trash bin, and bench improve the awareness of human scale. On the other hand, long sight lines, high buildings without using vegetation or other elements reduce

high buildings without using vegetation or other elements reduce human scale effects.

General Recommendations

Segments

Add street furniture

2123 R1, R2, 2123 L, 2122 L

Add vegetation

2122 R1, R2, 2122 L

Table 8.9. Recommendations for Commerce Street on Human Scale

iv. Transparency a. Main Street As physical elements affect the transparency that includes walls, windows, doors, landscape features, fences, and other openings, it is a degree of which people can perceive what is more beyond these materials. Transparency scores of Main Street are as high as Elm Street. Since the high-rise buildings are located in between Field Street and Harwood Street, the stores have great openings for the first floor with windows. However, rest of the street segments on Main Street need improvements for transparency. For instance, the north face Lamar Street and Austin Street is needed some openings or windows in order to increase transparency. Besides, blind or closed vehicle parking are generally designated just for cars and outface is generally lack of window or any other transparency elements such as the segment between north face of Harwood and Pearl Street.

General Recommendations

Segments

Redesign parking garage exits

2136 L, 2136 R

Add windows or openings

1128 L

Table 8.10. Recommendations for Main Street on Transparency

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Chapter 8 b. Elm Street Elm Street is providing great opportunity in terms of transparency.

Except Dallas County Records Office Building and El Centro College, the street is fulfilling transparency function. Aforementioned buildings may be improved by openings or extra other efforts such as adding windows in first floor level.

General Recommendations

Segments

Add windows at street level

1139 R, 1139 L1, L2

Table 8.11. Recommendations for Elm Street on Transparency

c. Commerce Street Commerce Street is partially fulfilling the transparency and many other segments even including high-rise business locations. The main problem is that there are overall lack of active uses in this street. The street mainly and particularly east part of the street includes either parking lots, empty buildings (even it has first floor windows openings), or construction sites.

So, these circumstances affects the transparency and walkability eventually. First and foremost, active uses buildings and lots should be added in this street. For instance, between S. Ervay and S. Pearl Street there is not any active uses of buildings except a grocery store (7 Eleven). This vacant impression of one of the main streets in downtown makes the site less walkable even there are many other variables and indicators to have this idea. The west part of the street has another drawback: entrance or exits of parking garages. People do not prefer to walk in these segments as drivers are entering or exiting from the parking lot mostly in uncontrolled manner. In addition, there are many blind spots of these garage enters and exits. On the other hand, many high rise buildings of this side is not pedestrian friendly as either the buildings do not have openings or buildings are lack of

88 | Downtown Dallas Walkability Study

active uses. To demonstrate it, the segments between S. Field and S. Griffin are having these difficulties. As recommendations, enters and exits of parking lots should be redesigned in order to make minimum blind spots for the pedestrians.

There are many interesting patterns for transparency. As Bryan Street has train station and railway, this street provides a great transparency for people. The active uses of buildings, walls and fences of the buildings are appropriate enough for people to walk. Another pattern that needs to be emphasized is west part of the research area relatively has lower score than the east part for transparency. So, in order to generate more walkable downtown, many vacant lots and offices should be functioned in a meaningful way.

General Recommendations

Segments

Redesign parking garage enters and exits

1118 L, 2120 R, 2120 L

Add windows at street level

2120 R

Promote active uses of buildings

2123 R1, R2, 2124 R, 2124 L, 2125 L, 2125 R

Table 8.12. Recommendations for Commerce Street on Transparency

v. Complexity a. Main Street Since complexity is highly related to imageability, the complexity results are more or less similar to the imageability results. Main Street has high complexity scores in core high-rise office buildings. Apart from this location, complexity is fluctuating. However, Main Street is overall in a good situation for complexity by taking account 6 variables that are related to each other. Only subject that can be improved for complexity is that

Chapter 8

colors and accent colors in Main Street. There might be a regulation or major commitment for the street that having more and attractive colors in order to gain attention.

General Recommendations

Segments

Add a policy or a regulation about building colors

2132 L1, L2

Table 8.13. Recommendations for Main Street on Complexity

b. Elm Street The complexity is not at stable level for Elm Street and it varies in different segments. Along with the street, there is lack of public art in this street and few public arts might improve the complexity along with many important buildings such as museums and offices. Another design recommendation for the street is that accent colors of the buildings. Even though the street is providing variety for main building colors, there is a few of accent colors. So, accent colors should be improved in the street as a design regulation or design guideline.

General Recommendations

Segments

Add a policy or a regulation about building colors

1143 L, 1143 R1, R2, 1144 L, 1144 R

Add public arts

1140 R, 1140 L, 1141 L, R

location for designating public arts due to the context of the environment. As it is aforementioned in previous streets, Commerce Street also lacks of building main colors and accent colors and they need to be addressed accordingly.

The other interesting patters are about transportation stations such as Bryan Street. Bryan Street provides a great opportunity for complexity. As the station is used by many people, there are pedestrian activity along with many buildings with ample colors, outdoor dining options, and public arts. On the contrary, Live Oak Street that is just one parallel street of Bryan Street is one of the lowest street segment level of complexity as there is not that much pedestrian activity.

General Recommendations

Segments

Add a policy or a regulation about building colors

1118 L, 1118 R, 2123 L, 2123 R1, R2

Add public arts

1116 L1, 1116 L2, 1116 R, 1117 L, 1117 R

Table 8.15. Recommendations for Commerce Street on Complexity

Table 8.14. Recommendations for Elm Street on Complexity

c. Commerce Street Commerce Street is lesser complex than the other principal streets in downtown and it needs more improvement and design solutions.

Even there are many important and functional buildings on the street, there are few public arts. The segment of S. Houston and S. Austin and the segment of S. Griffin and S. Field might be a good

Figure 8-2 Commerce Street

Downtown Dallas Walkability Study | 89

References

9 References Almeida, M. (2008). Rating “Shade” on Urban Walkability”, Proceedings of .the 9th International Conference for Walking by Walk 21, “Walk with Barcelona – A moving city”, Barcelona, Spain.

Ameli, H. S., Hamidi, S., Garfinkel-Castro, A., & Ewing, R. (2015). Do Better Urban Design Qualities Lead to More Walking in Salt Lake City, Utah?

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