farm to table - texas architecture · farm to table: a fresh food ... kameshwari. “attracting ......

Farm to Table: A Fresh Food Accessibility Study

in Dallas, Texas

Orly Shturman

Fall 2009

CRP 386, Intro to GIS

University of Texas

Farm To Table: A Fresh Food Accessibility Study in Dallas, Texas Orly Shturman, Fall 2009

EXECUTIVE SUMMARY The lack of access to fresh food is a growing social and economic problem in cities that have witnessed the migration of grocery stores leaving the urban areas and relocating in the suburbs. Grocery stores and fresh food markets have not kept up with the demand of a growing population in certain neighborhoods, particularly low-income and minority neighborhoods. This project will focus on the accessibility of fresh food in Dallas, Texas. The locations of fresh food vendors as defined as grocery stores, neighborhood markets, specialty stores and farmers markets. The first part of this project explores the locations of fresh food vendors in relation to income level and racial composition. The second part of this project is to locate marginalized areas and analyze the distribution of fresh food vendors to the population that lives in these marginalized locations. The marginalized areas serve as examples of locations that are in need of fresh food vendors. Additional criteria such as public transportation and highways are introduced to the analysis in order to find a suitable location for a new fresh food vendor. These suitable locations in the marginalized areas serve as potential areas of development by grocery stores or neighborhood markets. Although grocery stores and neighborhood markets have been expanding to the suburbs and leaving the urban areas in need, policy changes need to attract fresh food vendors back into the cities and serve a population in need of access to fresh, healthy food.


INTRODUCTION Over the past fifty years, the grocery store movement has followed the urban flight movement in major cities across the United States. Grocery stores are moving the suburbs and building mega-stores since the land is cheaper and the return on their investment is higher compared to urban settings. As grocery stores are moving to high-income neighborhoods, the urban neighborhoods, which tend to be low-income, are facing a lack of grocery stores and fresh food vendors. The lack of fresh food access has been recognized particularly in low-income and minority neighborhoods. The lack of fresh food access affects the eating, health, and finances of all people and is of specific interest to the low-income population since a large portion of their disposable income is spent on food. A strong relationship exists between low-income areas and minority populations. Low-income individuals and families already have hardships accessing reasonably priced food, but the access of fresh food vendors may also be a challenge. Similarly, according to the U.S. Department of Health and Human Services, 68 census tracts in Dallas County have been found to be medically underserved, which means that the people in that area experience a shortage of personal medical services. Eating healthy is difficult if there is no access to healthy food, and when surrounded by unhealthy food, the problem will eventually lead to health problems and medical need. If certain areas are lacking medical services, those same areas may be lacking the access of fresh food, and in the future, a government department may be tracking underserved fresh food accessibility areas. Dallas, Texas is the third largest city in Texas and the eighth largest in the country. Dallas is primarily located in Dallas County but spills over into neighboring Collin, Denton, Kaufman and Rockwall counties. Over the past ten years, Dallas has experienced urban renewal. Coincidentally, supermarkets have relocated to the suburban areas, which have left the urban, inner-city areas in need. The Dallas City Council in 1990 conducted a study of large (over 20,000 square feet) supermarkets in South Dallas, which is a predominately minority, low-income neighborhood. The Dallas City Council negotiated with several large supermarket chains and offered financial incentives. Some chain grocery stores such as Minyard’s developed some markets in South Dallas.1 On November 2, 2009, the Dallas Morning News reported that Kroger supermarket chain is looking to build 50,000 to 60,000 square foot store close just north of downtown Dallas. The problem arises when Kroger wants to sell alcohol and a middle school is within a 300 feet radius. The Dallas City Council’s economic development committee must decide if it should waive the rule that no alcohol can be sold within 300 feet of a school. According to the article, Kroger has been searching to build in a downtown Dallas location.2

1Pothukuchi,Kameshwari.“Attracting Supermarkets to Inner-City Neighborhoods: Economic Development outside the Box.” Economic Development Quarterly. August 2005. http://edq.sagepub.com/cgi/content/abstract/19/3/232 2http://www.dallasnews.com/sharedcontent/dws/dn/latestnews/stories/110309dnbuskrogercityplace.27911ff67.html


Downtown Dallas may be an area of need, but this project will further explore the other areas in Dallas in need of new fresh food vendors. RESEARCH QUESTION The purpose of this project is to study fresh food accessibility in Dallas, Texas and to investigate if there is a relationship between fresh food access and income level and racial composition in order to understand how to serve the need of underserved and marginalized areas. The project will identify areas that lack access to fresh food and locate suitable parcels, if any, which could feasibly support a new fresh food vendor. The primary research questions of this project are:

• What is the distribution and location of fresh food vendors in Dallas? • What areas are underserved in terms of fresh food accessibility and what is the

relationship to low-income areas? • Where are the low-income and marginalized areas in Dallas? • What is the relationship between the marginalized areas and the racial distribution

within Dallas? • Where are the suitable parcels located within the marginalized areas?

METHODOLOGY Study Area The study area is defined by Dallas city limits within Dallas County. Although Dallas city limits extend to various counties, this project focuses on the city limits within Dallas County. The portion of Dallas city limits that extended into Kaufman County and Denton County was primarily lakes and was eliminated. The small portion of Dallas city limits that extended into Collin County was eliminated since the area was very small. An overwhelming majority of Dallas city limits is within the Dallas County boundaries. Further, when the City of Dallas makes policy decisions, it may need to consult with various county officials when outside of Dallas County. To simplify the data collection and analysis, the study area is all of the Dallas city limits within the Dallas County. Data Collection This report studies the location of fresh food vendors, which are defined as grocery stores, neighborhood markets, specialty markets, and the Dallas Farmers Market. The fresh food vendors have multiple fresh and healthy food options and have sufficient selections of food to make a full meal. Corner stores, convenient stores, and pharmacies were not included since they may have a fruit basket or a limited selection of fresh food to make a meal. I used the Internet to search (google.com) for vendors and individual store’s websites (Kroger.com, Alberstons.com, Tomthumb.com, Target.com, etc.) to find the addresses for the grocery stores, neighborhood markets, specialty markets, and The Dallas Farmers Market identified in this report. The names and addresses for all the fresh food vendors were tracked on an Excel spreadsheet. (See Appendix B)


I defined grocery stores as chain grocers with large stores such as Kroger, Tom Thumb, Whole Foods, and Albertsons. Neighborhood markets included large retail companies that may designate a portion of the store to food such as SuperTarget, Wal-Mart Supercenters. Smaller specialty stores included Sprouts, Eatzi’s, and Asian markets. The Dallas Farmers Market is the only formal farmers market located in Dallas. Another informal market gathers once a month during the summer but that was not included in the analysis since it is seasonal. I found it appropriate to use census block groups for this project since Dallas covers a large geographic area (385 square miles). I downloaded the census block groups from the Tigerline/ESRI website. The demographic data was available by the census block group level. The U.S. Census Bureau Summary File 1 (SF-1) included median income, and the U.S. Census Bureau Summary File 3 (SF-3) included race information and average household size information. SF-1 and SF-3 were downloaded from the U.S. Census Bureau website and consisted of Census 2000 information. The city limits, lakes, parks, highways, and 2005 Land Use information was downloaded from the North Central Texas Council of Governments (NCTCOG). A Dallas Area Rapid Transport (DART) employee provided the bus stop information after I requested the information via e-mail. The Texas shapefile was downloaded from the Tigerline/ESRI website. All the shapefiles are projected in NAD 83 State Plane Texas Central FIPS 4202 (feet). The shapefiles from NCTCOG and DART were already projected in NAD 83 State Plane Texas Central FIPS 4202 (feet). Preparing the Shapefiles Dallas City Limits - The census block groups, lakes, parks, and highways shapefiles were clipped (using the Clip Tool) by the Dallas city limits outline to only included information within the city limits. New respective shapefiles were created. Geocode Store Locations- I created an Address Locator, and then using the Geocoding tool with 80% sensitivity, 55 of the 66 addresses were automatically matched. The remaining 11 addresses were manually located by revising the spelling or changing the “suffix”, “prefix” or “zone” fields. All 66 store locations were successfully located. Joining Demographic Information to Census Block Groups- The SF-1 and SF-3 tables were joined to the census block groups using the common field of STFID. Demographic Data- The race and median income information is classified into quintiles with five classes because I wanted to compare the different distributions. The racial distribution is based on density or the number of White, African Americans, Hispanics or Asians in a census block group over the entire population of the block group. I changed the symbology to quantities in graduated colors and color ramp to visually differentiate the breakdown.


Determining Income Threshold and Marginalized Block Groups- In order the locate the marginalized block groups, an income threshold was set based on Federal Poverty Rates in 2000. The Federal Poverty Rate in 2000 is based on household size, so I needed to obtain the average household size in Dallas. The average household size is included in SF-3 information. The statistical information in the attribute table indicated that the average household size was 3.35 persons. The Federal Poverty Rate in 2000 for three people was $14,150. I ran a query selecting by attributes, in this case, median income under $14,150. The query identified those block groups in which the median income is under $14,150, and defined as the “marginalized block groups”. A new “marginalized block groups” shapefile was created. Hot Spot Analysis A Hot Spot Analysis measures the amount of clustering within a certain area. To prepare for the analysis, I joined (using Joins and Relates) the Store Addresses data to the census block groups, and the attribute table then had the number of stores in each census block group. I selected to analyze on the block groups with at least one store. Using the Hot Spot Analysis Tool, the hot spots were spatially located and assigned a Z-Score. The larger the Z-Scores correspond with the more intense clustering. Suitability Analysis Bus Stops- The bus stop shapefile was clipped by the “marginalized block groups” shapefile to only show the bus stops within those areas. Selecting Vacant Parcels- The 2005 Land Use shapefile was clipped to only include the areas within the “marginalized block groups”. I emailed an employee at the NCTCOG to determine the Land Use Codes, and I received the Land Use Codes via email. I used a query to “select by attribute” to locate only vacant parcels (Land Use Code 300) and then created a new shapefile with only vacant parcels. Criteria and Assigning Weights- The criteria used for the suitability analysis was distance to bus stops and highways. The distance to bus stops was weighed more (70%) since I want to demonstrate a more sustainable model using public transportation. Further, by using bus stops, residents who do not own a car and children under the driving age can access fresh food vendors by walking or using public transportation. The distance to highways was not as important (30%), yet it has some effect since Dallas is a large metropolitan city with many drivers. Since none of the Marginalized Block Groups contained Fresh Food Vendors within the block group (some were located on the boundaries), I wanted to identify possible locations for a new fresh food vendor within the block groups. Within the Spatial Analyst Tool, I indicted that the analysis would use the Marginalized Block Groups Layer as the output; therefore, the suitable parcels would be within the Marginalized Block Groups. The bus stops and highways were converted into rasters, and the rasters were reclassified into ten equal interval classifications and ranked to reflect priority of being close to bus


stops and highways. The assigned weights (70% for distance to bust stops and 30% for distance to highways) were evaluated and another layer was produced. The rasters were then converted back to vector layers and suitable parcels were identified within the Marginalized Block Groups. The vacant parcel layer and suitable area layers were intersected, which produced a “ranked vacant parcels” layer. The parcels were ranked 1 through 3, 1 being the most suitable. Locating Vacant Parcels Large Enough for a New Fresh Food Vendor- Using the Calculate Geometry function on the Attribute Table Options, I created a new field, “acres”, to calculate the area of each suitable vacant parcel. The parcels equal or larger than two acres were identified, and the smaller parcels were eliminated. I chose two acres as the smallest area since a 2-acre parcel could accommodate at 40,000 square foot fresh food vendor and a parking lot. FINDINGS This report includes the following maps:

• Figure 1: Locations of Fresh Food Vendors • Figure 2: A Hot Spot Analysis of Fresh Food Vendor Locations • Figure 3: Median Income Distribution • Figure 4: Average Household Size • Figure 5: Population Densities by Race • Figure 6: Identifying Marginalized Block Groups • Figure 7: Location of Marginalized Block Groups and Populations Densities by

Race • Figure 8: Relationship between Income Distribution and Store Locations • Figure 9: Bus Stops within Marginalized Block Groups • Figure 10: Suitability Analysis of Marginalized Block Groups • Figure 11: Vacant Parcels in Marginalized Block Groups • Figure 12: Suitable Vacant Parcels and Recommended Areas


!

!

!

!

!

!

!!

!

! ! !

!!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!!

!!

!

!

!

!

!

!

!

!

Lakes

Parks

Census Block Groups, 2000

Fresh Food Vendor Locations

Fresh Food Accessibility in Dallas, Texas

0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes, Parks) North Central Texas Council of Governments, (Texas) ESRI/Tigerline, (Store Addresses) Geocoded.

Figure 1: Locations of Fresh Food Vendors

!

!

!

!

!

!

!!

!

! ! !

!!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!!

!!

!

!

!

!

!

!

!

!


0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes) North Central Texas Council of Governments, (Texas) ESRI/Tigerline,(Store Addresses) Geocoded.

A Hot Spot Analysis

Z-Score-1.65 - 1.65 Std. Dev.

1.65 - 2.58 Std. Dev.

Lakes

Census Block Groups, 2000

Fresh Food Vendor Locations

Figure 2: A Hot Spot Analysis of Fresh Food Vendor Locations


0́ 2 4 6 81Miles

Created by Orly Shturman, November 11, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Income by block groups) U.S. Census Data, (Lakes) North Central Texas Council of Governments, (Texas) ESRI/Tigerline.

Lakes

Median Income Per HouseholdPer Census Block Group, 2000

$42,001 - 62,734

$62,735 - 200,001

$33,305 - 42,000$26,177 - 33,304$2,499 - 26,176

Figure 3: Median Income Distribution


0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Avg Household Size by block groups) U.S. Census Data, (Lakes) North Central Texas Council of Governments, (Texas) ESRI/Tigerline.

Lakes

Average Household Size, 20000.00 - 2.452.47 - 3.023.03 - 3.523.53 - 4.064.07 - 6.29

Figure 4: Average Household Size


´

Population Densities by Race (2000)

Hispanic/Total Pop.0.00 - 0.053%0.053 - 0.13%0.13 - 0.32%0.32 - 0.61%0.61 - 0.97%

African American/Total Pop.0.00- 0.016%0.017 - 0.053%0.054 - 0.16%0.16 - 0.54%0.55 - 1.0%

White/Total Pop. 0.00 - 0.18%0.19 - 0.39%0.39 - 0.58%0.58 - 0.81%0.81 - 1.0%

Asian/Total Pop. 0.00 - 0.00093%0.00097 - 0.0047%0.0047 - 0.012%0.012 - 0.029%0.029 - 0.43%

Created by Orly Shturman, December 8, 2009. Sources: (Race by block groups) U.S. Census Data,

(Lakes) North Central Texas Council of Governments.Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, Feet

0 2 4 6 81Miles

! Lakes

Figure 5: Population Densities by Race

!

!

!

!

!

!

!!

!

! ! !

!!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!


0́ 2 4 6 81Miles

Created by Orly Shturman, November 11, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes, Parks) North Central Texas Council of Governments, (Texas) ESRI/Tigerline,(Store Addresses) Geocoded.

Lakes

! Fresh Food Vendor LocationsMarginalized Block GroupsParksCensus Block Groups, 2000

Identifying Marginalized Block Groups

Figure 6: Identifying Marginalized Block Groups


´

Location of Marginalized Block Groups and Population Densities by Race (2000)

Created by Orly Shturman, December 8, 2009. Sources: (Race by block groups) U.S. Census Data,

(Lakes) North Central Texas Council of Governments.Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, Feet

0 2 4 6 81Miles

! Lakes

Hispanic/Total Pop.0.00 - 0.053%0.053 - 0.13%0.13 - 0.32%0.32 - 0.61%0.61 - 0.97%

African American/Total Pop.0.00- 0.016%0.017 - 0.053%0.054 - 0.16%0.16 - 0.54%0.55 - 1.0%

Asian/Total Pop. 0.00 - 0.00093%0.00097 - 0.0047%0.0047 - 0.012%0.012 - 0.029%0.029 - 0.43%

White/Total Pop. 0.00 - 0.18%0.19 - 0.39%0.39 - 0.58%0.58 - 0.81%0.81 - 1.0%

Marginalized Block Groups

Figure 7: Location of Marginalized Block Groups and Population Densities by Race

!

!

!

!

!

!

!!

!

! ! !

!!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

! !

!

!

!

!

!

!

!

!

!!

!!

!

!

!

!

!

!

!

!

!

!

!


0́ 2 4 6 81Miles

Created by Orly Shturman, November 11, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Income by block groups) U.S. Census Data, (Lakes) North Central Texas Council of Governments, (Texas) ESRI/Tigerline, (Store Addresses) Geocoded.

Lakes

Median Income Per HouseholdPer Census Block Group, 2000

$42,001 - 62,734

$62,735 - 200,001

$33,305 - 42,000$26,177 - 33,304

$2,499 - 26,176

! Fresh Food Vendor Locations

Figure 8: Relationship between Income Distribution and Store Locations

")")")")")

")

")")")")") ") ") ")")")") ")")

")")

")") ")")") ")")") ")") ") ")") ")") ")") ")") ")") ")") ")") ")")")")")")") ")") ")")")")")")

")")")")")

") ")")") ")")")")")")") ")")")") ")") ")") ")")") ")")") ")")")")")

")")") ")")")")")")")")")

")")")")") ")") ")") ")")")") ") ")") ")")")")")") ")")") ")") ")") ")") ")")") ")") ")") ")")")")") ")")")") ")")") ") ")")") ")") ") ")")") ")")")") ") ")")")")") ")") ")") ")")")")")") ")") ")")") ")")") ")") ")") ")")") ")")") ")")")") ") ")") ")

")") ")") ")")")") ")") ")")") ") ")")")") ")")") ")")")") ")")")")")")") ")") ")")")

") ")")")")")")") ") ")")") ")")")") ") ")") ") ")") ")")") ")")")") ") ")")") ")") ")") ")") ")")")")") ")") ")") ")") ")")")") ") ")")") ")")") ")")")")") ") ") ")") ") ")")")") ")") ") ") ")")")") ")") ")") ") ")") ")") ") ")")") ")")") ")")")")")")

")")")")")")") ")")")

") ")")

")")")")")")")")")")")

")")")")

!

!

!

!

!

!

!

!

!

! !!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!

!

!

!

!

!

!

!

!

!


0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes, Highways) North Central Texas Council of Governments, (Bus Stops) Dallas Area Rapid Transport, (Store Addresses) Geocoded.

Lakes

IH-30IH-35

! Fresh Food Vendor Locations") Bus Stops

Marginalized Block GroupsParksCensus Block Groups, 2000

Bus Stops within Marginalized Block Groups

Figure 9: Bus Stops within Marginalized Block Groups


0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Highways) North Central Texas Council of Governments, (Store Addresses) Geocoded.

A Suitability Analysis

1- Most Suitable23 - Least Suitable

Suitable Areas by Rank ! Fresh Food Vendor Locations

Lakes

IH-30IH-35Marginalized Block GroupsCensus Block Groups, 2000

Figure 10: Suitability Analysis of Marginalized Block Groups


0́ 2 4 6 81Miles

Created by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes, Highways, Land Use) North Central Texas Council of Governments, (Store Addresses) Geocoded.

Vacant Parcels in Marginalized Block Groups

Vacant Parcels

Lakes

Marginalized Block GroupsCensus Block Groups, 2000

IH-30IH-35


Figure 11: Vacant Parcels in Marginalized Block Groups

!

!

!

!

!

!

!

!

!

! !!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!

!!

!

!

!

!

!

!

!

!

!

!

!!

!

!

!

!

!

!

!

!

!

!

!


´0 2 4 6 81

MilesCreated by Orly Shturman, December 8, 2009. Projected Coordinate System: NAD 83 State Plane Texas Central FIPS 4202, FeetSources: (Block groups) ESRI/Tigerline, (Lakes, Highways, Land Use) North Central Texas Council of Governments, (Store Addresses) Geocoded.

Suitable Vacant Parcels and Recommended Areas

Lakes

Marginalized Block GroupsCensus Block Groups, 2000

Suitable Vacant Parcels (over 2 acres)IH-30IH-35


1

1

2

2

0 0.5 10.25Miles

0 1 20.5Miles

Figure 12: Suitable Vacant Parcels and Recommended Areas

ANALYSIS Distribution and Location of Fresh Food Vendors Figure 1 and Figure 2 show the location of fresh food vendors. Figure 8 shows the majority of the fresh food vendors are concentrated in the northern and central neighborhoods and lacking in the southern and eastern neighborhoods. The Hot Spot Analysis explains that there is some clustering in certain block groups, and only two block groups have a slightly more intense clustering of fresh food vendors. The Hot Spot Analysis explains that while the clustering is not significant, the clusters exist in the northern and central areas of Dallas. Figure 3 illustrates that the northern and northeastern neighborhoods in Dallas are higher income. Relationship of Fresh Food Vendors with Demographic Data Figure 3 and Figure 5 show the median income distribution and racial distribution. While comparing the two layouts, it can be concluded that the northern and northeastern areas have a high White population and the southern and eastern areas have a high African American and Hispanic population. Figure 6 and Figure 7 illustrate the relationship between fresh food vendors and demographic information. Figure 6 shows that only eight fresh food vendors exist among the marginalized block groups and some of the marginalized block groups do not have any fresh food vendors. All of the marginalized block groups are in the central and southern areas of Dallas. (Note: a marginalized block group appears in north Dallas. This small block group was eliminated from the analysis since it is a commercial block, including a fresh food vendor.) Figure 7 emphasizes that the marginalized block groups are mostly in areas with a high African American population. The marginalized block groups are also located around areas with a high Hispanic population. The only marginalized block group with a high White population is in downtown or the Central Business District of Dallas. Identifying Suitable Parcels The purpose of this project was to locate suitable areas in marginalized neighborhoods. The marginalized neighborhoods could also be considered underserved since many lack a fresh food vendor within the block group. The suitability analysis criteria restricted the suitable parcels to be located within the marginalized block groups. I weighed proximity to bus routes heavier than proximity to highways because I wanted to show a more sustainable, environmentally aware model that uses public transportation and allows access to more citizens regardless of age and car ownership. The suitable vacant parcels that were smaller than 2 acres were eliminated, and only those over two acres were recommended as suitable lots. The recommended areas have a high African American population and are around areas of high Hispanic population concentration.


I wanted to find a location large enough for the development of a large grocery or neighborhood store in order to effectively serve the neighborhood. If a smaller specialty or informal farmers market wanted to locate a suitable space, further analysis could be conducted. RESEARCH LIMITATIONS The demographic data used in this project was based on 2000 U.S. Census data, and neighborhoods in Dallas have undergone demographic changes and shifts. The 2000 Census data is outdated; with more accurate data, the demographic composition of Dallas may be different. Similarly, the Land Use information is from 2005 and may be outdated. The vacant parcels that were located may not be currently vacant. Although vacant parcels were located from the Land Use data, I was not able to locate zoning information. The suitable vacant parcels may not be zoned for commercial use or may have to undergo zoning changes. Although I was able to get information on bus routes, the bus stops do not indicate which routes they serve or transfer time. The amount of data I was able to gather from the NCTCOG was limited, and the City of Dallas does not grant public access to GIS data. The data collection for this project was a significant limitation.


CONCLUSIONS AND RECOMMENDATIONS The purpose of this project was to find suitable vacant parcels over two acres to accommodate a new fresh food vendor in a marginalized block group. The analysis recommends two different areas of possible development. Although large vacant parcels were located, further analysis could be done to locate smaller vacant parcels to include a smaller store or informal farmers market. Although the spatial analysis locates suitable parcels, it is difficult to incorporate the culture and attitudes of the residents of the neighborhoods and grocery retailers in the analysis. This project suggests that various policy initiatives may be needed to encourage large chains or grocery retailers to build in low-income, marginalized neighborhoods. Although it is unknown why food retailers do not expand to these neighborhoods, crime and vandalism may be deterrents. Policy recommendations, including financial initiatives through tax credits or zoning changes, may need to be introduced in order to encourage fresh food vendors to build in these neighborhoods. A policy initiative to promote informal farmers markets or community gardens could be beneficial to a community with existing infrastructure. The inequity of fresh food access leads to various health and economic problems including increase in obesity and higher healthcare costs, and introducing fresh food vendors to marginalized areas would allow access to be more equitable.


DATA SOURCES County, Census Block Groups shapefiles ESRI, TIGER/Line Data, 2000 [computer file], http://arcdata.esri.com/data/tiger2000/tiger_county.cfm?sfips=48 Income, Average Household Size, and Race Data Tables ( SF-1 and SF-3) U.S. Census Bureau; Census 2000, Summary File 1; generated using American Factfinder, http://factfinder.census.gov/ U.S. Census Bureau; Census 2000, Summary File 3; generated using American Factfinder, http://factfinder.census.gov/ Highways, Lakes, Parks, City Limits, and 2005 Land Use shapefiles North Central Texas Council of Governments, 2009 [computer file], http://www.dfwmaps.com/clearinghouse/ Locations of Fresh Food Vendors - the locations were geocoded by address. The addresses are found by using google.com and store locator on the respective store websites. All shapefiles projected in NAD 83 State Plane Texas Central FIPS 4202 (in feet) coordinate system. REFERENCES Dallas Morning News, “Kroger plans Cityplace store if it can sell alcohol there”. http://www.dallasnews.com/sharedcontent/dws/dn/latestnews/stories/110309dnbuskrogercityplace.27911ff67.html (Accessed November 2, 2009). Pothukuchi, Kameshwari. “Attracting Supermarkets to Inner-City Neighborhoods: Economic Development Outside the Box”. Economic Development Quarterly. August 2005. http://edq.sagepub.com/cgi/content/abstract/19/3/232 United States Department of Agriculture. “Access to Affordable and Nutritious Food: Measuring and Understanding Food Deserts and Their Consequences”. http://www.ers.usda.gov/Publications/AP/AP036/AP036k.pdf (Accessed October 25, 2009). City of Dallas, “Quick Facts” http://www.dallascityhall.com/info/about.html (Accessed December 7, 2009). U.S. Department of Health and Human Services, “The 2000 HHS Poverty Guidelines”. aspe.hhs.gov/poverty/00poverty.htm (Accessed December 1, 2009).


APPENDIX A

• Displaying census blocks o Obtain data files on block group level for all Dallas City Limits o Download census block groups from ESRI/TIGERLINE for Dallas o Download median income tables (census summary files 3) and race

(census summary files 1) from factfinder.com/US Census Bureau. o Download city limits for Dallas from North Central Texas Council of

Governments (NCTCOG) file and make new layer with only Dallas city limits

o Tools Clip using Dallas city limits and clipping the block groups o Create new shapefile “Dallas_block_groups” o Download lakes, parks and highways shapefiles from NCTCOG to use as

visual references and/or analysis o Tools Clip using Dallas city limits for lakes, parks, and highways. o Create new respective layers o All shapefiles have been projected in the same coordinate system: NAD

1983 State Plane Texas Central FIPS 4202, feet o Since Lake Ray Hubbard is far east and does not contain block groups in

Dallas city limits includes various counties o Edit Tools and delete on Attribute Table to remove those areas to create a

more uniform shapefile of only block groups and remove block groups outside of Dallas County

• Joining demographic tables

o Download tables from U.S. Census/American Factfinder o Join the race and income information from the tables to the block group

layer, Add Data Join Table (Keep all records) STFID o Racial composition of the population, density = # of Whites, African

Americans, Hispanics, Asians in census tract / total population o Change symbology – quantities in graduated colors and sum of population

as value, 5 breaks, quintiles

• Locating Marginalized Block Groups o Define and locate marginalized block groups as those with median income

below $14,150 (Federal Poverty Rate for 3 persons in 2000) o Open attribute table for census block groups o Options Select by attributes Perform a query (median income equal

or less than 14150) o Export Data Create new layer “marginalized_block_groups”

• Locating fresh food vendors?

o Defining fresh food vendors as grocery stores (HEB, Kroger, etc.), neighborhood markets (Sprouts, Wal-Mart supercenters, Target supercenters) and Dallas Farmers Market.


o Using google.com, yellowpages.com and individual stores websites (alberstons.com, Kroger.com, etc.) I created an Excel sheet with the store addresses

o Join table to census block group layer o Create address locator (US zone and address) o Tools Geocode the store addresses in ArcMap o Address match with 80% accuracy and manually match the remaining

addresses o Manually match the unmatched addresses o Create new layer with points locating fresh food vendors

• Hot Spot Analysis

o Store Addresses and block groups layer o On block group layer, Join Join Data Window (join data from another

layer based on spatial location) o New layer “block_groupsjoin” appears with number of vendors per block

group in attribute table o Do not include block groups with zero vendors. Open attribute table

Options Select by attribute, perform query where count is greater than or equal to 1

o Export Data create new layer o Search toolbox, Tools Hot Spot Tool (Getis-Ord Gi*), input feature

class is “block_groupsjoin”, input field is “count” o New layer appears o Change color ramp

• Suitability Analysis

o Add layers: census block groups, marginalized block groups, highways, fresh food vendor locations, bus stops

o Activate Spatial Analyst: Tools Extensions, check Spatial Analyst o View Toolbars Spatial Analyst o Spatial Analyst Options (same as layer) “marginalized_block_groups” o Distance to Bus Routes (closer the better): Spatial Analyst Distance

Straight Line, Distance to bus stops, output: bstop_dist o Reclassify: input: btop_dist, Method: Equal Intervals, Classes: 10 o Change Values, the closer are classified as 1, the further are classified as

10 o Output: bstop_dist_re o Distance to Highways (closer the better): Spatial Analyst Distance

Straight Line, Distance to hw, output: hw_dist o Reclassify: input: bus_stop_dist, Method: Equal Intervals, Classes: 10 o Change Values, the closer are classified as 1, the further are classified as

10 o Output: hw_dist_re o Weighting: Distance from bus stops = 70%, Distance from highways =

30%


o Spatial Analyst Raster Calculator, type [hw_dis_re]*.3 + [bstop_dist_re]*.7, Evaluate

o Data Make Permanent o Rename “calculation” to “weights” o Remove hw_dist_re and bstop_dist_re o Reclassifying weights: Spatial Analyst Reclassify, Input: weights,

Classify, Method: Equal Interval, Classes: 10, Output: weights_re o Converting to Vector Layer: Spatial Analyst Convert Raster to

Features, Input: weights_re, Output: rank o Intersect with Vacant Parcels: Toolbox Analysis Tools Overlay

Intersect, Input: rank and vacant_parcels, output: suitable_vacant_parcels o Change color ramp


APPENDIX B STORE ADDRESSES

Store Address Source

Kroger 5665 E. Mockingbird Lane kroger.com store locator

Kroger 752 Wynnewood Village Sc kroger.com store locator

Kroger 10677 E. Northwest Hwy kroger.com store locator

Kroger 9140 Forest Lane kroger.com store locator

Tom Thumb #9 Highland Park Village tomthumb.com store locator

Tom Thumb 315 S. Hampton St tomthumb.com store locator

Tom Thumb 7117 Inwood Rd tomthumb.com store locator

Tom Thumb 6333 E Mockingbird Ln tomthumb.com store locator

Tom Thumb 5809 E Lovers Ln tomthumb.com store locator

Tom Thumb 4001 Villanova Dr tomthumb.com store locator

Tom Thumb 7700 W Northwest Hwy tomthumb.com store locator

Tom Thumb 6770 Abrams Rd tomthumb.com store locator

Tom Thumb 10455 N Central Expwy tomthumb.com store locator

Tom Thumb 522 Preston Royal Ctr tomthumb.com store locator

Tom Thumb 11920 Preston Road tomthumb.com store locator

Tom Thumb 8698 Skillman St tomthumb.com store locator

Tom Thumb 3757 Forest Ln tomthumb.com store locator

Tom Thumb 14999 Preston Road tomthumb.com store locator

Sprouts Farmers Market 11722 Marsh Lane #317 sprouts.com

SuperTarget 6419 Skillman St target.com

SuperTarget 16731 Coit Road target.com

Wal-Mart Neighborhood Market 2305 North Central Expressway walmart.com

Wal-Mart Neighborhood Market 2275 Gus Thomason Road walmart.com

Wal-Mart Neighborhood Market 12789 Midway Road walmart.com

Wal-Mart Supercenter 7401 Samuell Blvd walmart.com

Wal-Mart Supercenter 1521 North Cockrell Hill Road walmart.com

Wal-Mart Supercenter 9301 Forest Ln walmart.com

Albertsons 320 Casa Linda Plaza albertsons.com

Albertsons 3524 McKinney Ave albertsons.com


Albertsons 7007 Arapaho Road albertsons.com

Albertsons 4349 West Northwest Highway albertsons.com

Albertsons 6464 East Mockingbird Lane albertsons.com

Albertsons 10203 East Northwest Highway albertsons.com

Albertsons 3630 Forest Lane albertsons.com

Whole Foods Market 2118 Abrams Road albertsons.com

Whole Foods Market 11700 Preston Road albertsons.com

Central Market 5750 East Lovers Ln centralmarket.com

Urban Market 1500 Jackson St google.com

Jimmy's Food Store 4901 Bryan St google.com

Shin Chon Oriental Market 11422 Harry Hines Blvd google.com

Jerry's Supermarkets 532 W Jefferson Blvd google.com

Binh Minh Market 4823 Bryan Street google.com

Super Mercado Mexico 5535 Columbia Ave google.com

Newflowers Market 1800 N Henderson Ave google.com

Fiesta Mart 3030 S Lancaster Rd google.com

El Rancho Supermarket 1515 Buckner Blvd google.com

Jerry's Supermarkets 2314 W Illinois Ave google.com

Carnival Food Stores 2223 Singleton Blvd google.com

Tom Thumb 111 Turtle Creek Blvd google.com

Minyard 3230 Martin Luther King Jr Blvd google.com

Carnival Food Stores 6401 Abrams Rd google.com

Jerry's Supermarkets 1719 Singleton Blvd google.com

Save-A-Lot 3021 Martin Luther King Jr. Blvd google.com

Hackney Food 4815 Collins Ave google.com

Fair Park Grocery 2203 Lagow St google.com

Fiesta Mart 611 W Jefferson Blvd google.com

Fiesta Mart 8060 Spring Valley Rd google.com

Fiesta Mart 2951 Buckner Blvd google.com

Fiesta Mart 9727 Webb Chapel Rd google.com

Fiesta Mart 5334 Ross Ave google.com

Fiesta Mart 2225 W Ledbetter Dr google.com


Eatzi's 3403 Oak Lawn Ave google.com

Dallas Farmers Market 1010 S Pearl Expy google.com

Hong Kong Market Place 9780 Walnut St google.com

Thai Oriental Food Store 5616 Sears St google.com

Super Mercado Monterrey 300 E Jefferson Blvd google.com


farm to table - texas architecture · farm to table: a fresh food ... kameshwari. “attracting ......

Documents