This is a slideshow for a GIS project for my an Intro to GIS course I took about a year and a half ago. I this presentation I use various tools such a geocoding, buffers, choropleth maps, and network analysis to get my message across. In the presentation, I am doing market reach and comparing tow burger chains and their possible food delivery prospects.

1. WhatABurger vs InNOut in
Dallas
By: Miles Lilly

2. Where I got my data
● City of Dallas website:
○ https://gis.dallascityhall.com/shapefileDownload.aspx
● TIGER/Line Shapefiles from census.gov
● https://factfinder.census.gov/

6. City Limit
- This shapefile was my swiss army knife
- I used it to clip everything

7. Census data
- I used all Census tracts within Texas option to gather all relevant tables
- These tables include:
- MEDIAN INCOME IN THE PAST 12 MONTHS (IN 2010 INFLATION-ADJUSTED DOLLARS)
- HOUSEHOLD SIZE and TOTAL POPULATION
- NO ONE AGE 14 AND OVER SPEAKS ENGLISH ONLY OR SPEAKS ENGLISH "VERY
WELL"

8. The Tiger Shapefiles I used
● State of Texas
○ Blocks
○ Block groups
○ Census Tracts
○ Primary and Secondary Roads
● 5 Texas Counties because the city of Dallas is within 5 separate counties
○ Area Water
○ Linear Water

9. How I wrangled the Tiger Shapefiles
● Data munging or Data wrangling:
○ Term from Data Science
○ Means to format, clean up, or transform raw data in order to make is easier to analyze
● Texas Shapefiles
○ I clipped them with the “City Limits” Shapefile
● Texas Counties shapefiles:
○ I downloaded shapefiles for Dallas,Collin, Denton, Kaufman and Rockwall counties
○ I merged all 5 into a single shapefile
○ I clipped the merged shapefile using the “City Limits” shapefile

10. The uses of the Roads shapefile
● Geocoding
○ I created an address locator using the Streets shapefile
■ The fields I used are shown on the next slide
○ I then geocoded the addresses for my fast food restaurants using this locator
● Network analysis
○ I build a network dataset using the roads shapefile as well
■ I talk about this at the end

12. How I build the basemap
● I downloaded the following shapefiles from the city of Dallas website:
○ City of Dallas Streets
○ City of Dallas City Limits -
○ City Service Areas
○ Among others
● I imported these into ArcMap
● Note: I only used two of these in my analysis and geoprocessing
○ City Limits
○ Dallas Streets

15. How I build the water features
● Building the area water and linear water shapefiles required several steps:
a. Downloading Tiger area water and linear shapefiles for 5 counties: Dallas, Collin, Denton,
Kaufman and Rockwall
b. I merged all 5 of those shapefiles into a single shapefile
c. I clipped the merged file using the “City of Dallas City Limits” shapefile

16. How I build the Dallas Roads Feature
● I downloaded the “Primary and Secondary” Roads shapefile from the Tiger
shapefile portal
● I clipped it the shape of Dallas using the “Dallas City Limits” shapefile

19. How I made the median income map
● I made sure to select data by Census tract
● I then selected all Census tracts in Texas
● I downloaded table: S1903:MEDIAN INCOME IN THE PAST 12 MONTHS (IN
2010 INFLATION-ADJUSTED DOLLARS)
● Then I imported the table into ArcMap and joined it to the Census Tract Texas
Tiger shapefile using the GEOID10 and the id2 attributes
● I then clipped the joined Tiger shapefile to create a Median income shapefile
● Then I created a choropleth map using the Median Income Attribute

21. Some Thoughts after adding Burgers
Adding Whataburger and InNOut to this map made it more interesting. While both
are more heavily concentrated in North Dallas, InNOut is exclusively in high
median income places.

22. How I made it
1. I went to the two chains websites and copied and pasted the addresses into a
spreadsheet
2. I then created a geolocator using the Streets shapefile from the city of Dallas
3. I then matched the addresses in both spreadsheets
4. This created points
5. I then used to buffer tool to create a 2 mile radius buffer around the
Whataburger and InNOut locations

25. How I made this
1. I downloaded table Table H13 HOUSEHOLD SIZE and a Table B01003
TOTAL POPULATION
2. I joined both of these to the Census tracts shapefile
3. I created a choropleth map of mean households by dividing the Total
Population by Total Number of Households yielding mean household size

28. How I made this
● I downloaded table: S1602 NO ONE AGE 14 AND OVER SPEAKS ENGLISH
ONLY OR SPEAKS ENGLISH "VERY WELL"
● I joined this the the Census tracts shapefile
● Clipped it to the boundaries of the City of Dallas
● Made a choropleth map

29. clipped Buffers Mean HH Size

30. Clipped Buffers Median Inc.

31. Clipped Buffer English Ability
- No one over 14 speaks English very well

32. Extra Stuff: Network Analysis
- I build the network dataset using the Dallas Streets shapefile
- I then created two service areas. One for Whataburger, and one for InNOut
Burger
- I then loaded the locations into the facilities tab of the network analysis
window
- Then I used the network service area properties to set the parameters of the
model

35. WhatABurger tuft
● When one factors in hypothetical food delivery WhataBurger covers more
territory

37. InNOut turf for 5 Mile delivery
● Unfortunately, even with food delivery most of Dallas is left without Double-
Doubles and animal style fries

38. Questions?