Spatial Analysis: Suitability Model¶

Credits¶

Instructor: Rod Sardari, PhD, GISP
rsardari@utdallas.edu
Teaching Assistant: Yalin Yang
yalin.yang@utdallas.edu

Introduction¶

• This exercise guide is designed to help you develop a suitability model for establishing hospital charity care centers and finding the best locations within the Dallas Fort Worth Area.
  • Hospital charity care refers to healthcare services hospitals provide to individuals who cannot pay for medical treatment due to financial hardship.
  • These individuals often lack health insurance coverage and cannot afford the cost of their medical care.
  • Hospital charity care is a way for healthcare institutions to fulfill their social responsibility and provide essential medical services to those in need.

Define Objectives¶

The main objective of this exercise is to find the best location for establishing hospital charity care centers that can provide better services to the target population within the Dallas Fort Worth Area, including:

• Dallas County
• Collin County
• Denton County
• Tarrant County

Measurable Criteria¶

Selecting the right location is crucial for optimizing the allocation of resources and ensuring accessibility to those in need. In this step, we need to gather relevant data, including:

• Demographic data (e.g., population density, income levels).
• Healthcare facilities (existing hospitals, clinics, etc.).
• Accessibility factors (e.g., transit infrastructure).
• Social and economic indicators (e.g., unemployment rates, poverty levels).

Selected Variables:¶

In this exercise, these variables are selected to create the suitability model:

• CDC Health Outcomes
• Stroke among adults
• Cancer (excluding skin cancer) among adults
• Coronary heart disease among adults
• Transportation and Public Transit
• Access to Public Transit Stations
• Economic indicators
• Percentage of Low Wage Workers

Data Prepare¶

Get CDC Census Tract Data¶

1. Download CDC Health Data

   

2. Data for the DFW area is extracted and exported to the GIS geodatabase file.

   • DFW_Health_Out_CT_tab

   

Get GIS Census 2010 Tract Layer¶

• The CDC data is based on the 2010 Census Tract GIS layer.
• You need to download the Census Tract 2010 GIS Layer and join the CDC table to the GIS Census Tract layer.

1. Download and Import the unzipped Shapefile to the geodatabase

2. Import the GIS Census Tract layer to the geodatabase

3. Add US_tract_2010 layer and DFW_Health_Out_CT_tab table

4. Inside CDC Health data table, Check the data type format for CT_ID

5. Open the Census Tract layer US_tract_2010, and check the data type format for GEOID10

6. Transform GEOID10 to a number format

   • GEOID10: Data Type: Text

     

   • Add a new column and copy GEOID as a number format.

     

   • Save

     

   • Use Calculate Field and copy records from GEOID10 to GEOID_Num

     

7. Use the Add Join tool to join CDC data to the GIS layer
   

• The result of data join is available for the DFW area, and unmatched records are removed.

  

8. Export the results of data joins

   

9. Explore the distribution of Health Outcomes by changing symbology and using Graduated Colors

   

Get Transit Stations Data¶

1. GTFS stands for General Transit Feed Specification, a standardized format for public transportation schedules and geographic information.
2. GTFS data is used by transit agencies, app developers, and other organizations to provide information about public transit systems, including buses, trains, trams, subways, and ferries.

GTFS Component	Description	File Structure
Agency Information	General information about the transit agency or organization responsible for providing the service, including agency name, website, and contact information.
Calendar Dates	Information about service availability on specific dates, such as holidays or exceptions to regular schedules.
Routes	Details about transit routes, including route names, unique identifiers, and descriptions.
Shapes	Geometric data that defines the physical paths followed by transit vehicles along their routes. Shapes data is often used to display routes on maps.
Stop Times	When vehicles (e.g., buses or trains) arrive and depart from each stop for each trip. This data includes arrival and departure times and stop sequence information.
Stops	Information about transit stops, including their names, unique identifiers, and geographic coordinates (latitude and longitude).
Trips	Information about specific trips along transit routes, including trip IDs, service IDs, and the order of stops for each trip.

• GTFS data is provided as a collection of Text (.txt) and CSV (Comma-Separated Values) files, which makes it easy to read and process using various software tools and programming languages.
  • Public transit agencies, especially in urban areas, often publish their transit schedules and information in GTFS format.
• Developers use GTFS data to create transit-related applications and services, such as journey planners, real-time transit tracking apps, and route optimization tools.
  • It allows users to access accurate and up-to-date information about public transportation systems, making planning trips and navigating urban areas easier.

Get Dallas Transportation Authority GTFS¶

1. Go to Transit Feeds website

2. Search for a transit agency

3. Select and download GTFS data

• Review the stops.txt file

  

• Review the stop_times.txt file

  

• Review the calendar.txt file

  

Get Fort Worth Transportation Authority GTFS¶

1. Download the FWTA GTFS file (Fort Worth Transportation Authority)

   

Get Denton County Transportation Authority GTFS¶

1. Download the DCTA GTFS file (Denton County Transportation Authority)

   

Use Tableau Prep to Create a Union from GTFS data¶

1. Import all GTFS data from different transist agency and create a union file

   

Geocoding GTFS Stops¶

1. Geocoding DFW GTFS data in ArcGIS using the Display XY Data tool

   

2. Review Stops location in ArcGIS

   

Get Longitudinal Employer-Household Dynamics (LEHD) data¶

• The Longitudinal Employer-Household Dynamics (LEHD) data and OnTheMap are programs and tools provided by the United States Census Bureau to facilitate research and analysis related to employment, labor markets, and commuting patterns.
• They are valuable resources for economists, policymakers, businesses, and researchers interested in understanding the dynamics of the U.S. labor market. Here’s an overview of each:

Longitudinal Employer-Household Dynamics (LEHD) Data¶

• LEHD is a program that collects, maintains, and provides access to various administrative data sources related to employment and commuting. It includes data from state unemployment insurance (UI) programs, the Quarterly Census of Employment and Wages (QCEW), and other sources. The main components of LEHD data are listed below:

1. Quarterly Workforce Indicators (QWI): These provide detailed, quarterly data on employment, job creation and destruction, earnings, and other labor market measures at various geographic levels (e.g., states, counties, and metro areas).
2. LEHD Origin-Destination Employment Statistics (LODES): LODES data offer information about workers’ employment and commuting patterns. It allows researchers to analyze where workers live and work, which is valuable for understanding regional labor markets.
3. Job-to-Job Flows (J2J): J2J data provide insights into job changes and worker transitions in the labor market. It tracks movements between jobs and includes information on hiring, separations, and more.
4. OnTheMap: OnTheMap is a web-based tool and application that allows users to explore LEHD data interactively. It provides access to various reports and mapping features, enabling users to visualize employment and commuting patterns, view regional labor market dynamics, and conduct in-depth research.

Data Download¶

1. Go to OnTheMap: https://onthemap.ces.census.gov/
2. Search: Dallas (Metropolitan Area)

3. Perform Analysis on the Selection Area LEHD Analysis Settings

• Home/Work Area: Select Home

• Analysis Type: Area Profile – All Workers

• Year: 2020

• Job Type: All Jobs

  

4. Export Geographics

• Choose the ShapeFile format

5. Download Files

• Geography (Shapefile)

• File Specifications (Guide File)

  

6. Unzip LEHD OTM files

   

7. Review File Specifications (Guide File)

   

8. Review LEHD Shapefiles

   

9. Add GIS LEHD Shapefiles in ArcGIS

   

10. Review LEHD Attribute Table

    • Id: column represents census block IDs
    • Ce01: Number of low-wage job workers.

    

11. Remove unrelated fields and keep only

    • Id, c000, ce01, ce02, ce03

    

12. Export LEHD data to the geodatabase file

    

Get Hospital GIS Data¶

1. Get Hospitals GIS layer from ArcGIS Hub: Link

   

2. Add Hospitals GIS Data

   

3. Select Hospitals in DFW

   • Use Select by Attribute and select hospitals in Collin, Dallas, Denton, and Tarrant County.
   • SQL Code: COUNTYFIPS = '48085' And COUNTYFIPS = '48113' And COUNTYFIPS = '48121' And COUNTYFIPS = '48439'

   

4. Export the selected hospital in DFW

5. Verify and remove extra Hospitals outside the study area, Delete records using Delete Selection.

   

6. Verify the number of Hospitals in DFW: 154 Hospitals

   

Network Analysis¶

Service Area Buffers using Network Analysis¶

1. Create 3-mile driving buffers from hospitals using Network Analyst.

   

2. Check the Service Area Feature Dataset, Rename the Feature Dataset

   • Feature datasets in ArcGIS Pro
     • A feature dataset is a collection of related feature classes that share a common coordinate system.
     • Feature datasets facilitate the creation of controller datasets (sometimes called extension datasets), such as a parcel fabric, topology, or utility network.
     • More info: Feature datasets in ArcGIS Pro

   

3. Select the Service Area layer in the Table of Contents, Select Import Facilities

   

4. Select Import Facilities: Add Locations, and Verify the imported facilities

   

5. Service Area Travel Settings

   1. Select Service Area Layer
   2. Choose Layer Properties
   3. Change units from Kilometers to Miles

   

6. Define Service Area Parameters, and run

   • Mode: Walking Distance
   • Direction: Towards Facilities
   • Cutoffs: 3
   • Output Geometry: Standard, Overlap, Rings

   

7. Create a copy and Export the Polygon layer and Add Model Inputs in Table of Contents

   

Spatial Join Analysis¶

The Spatial Join tool joins attributes from one feature to another based on the spatial relationship.

• The target features and the joined attributes from the join features are written to the output feature class.
• A spatial join matches rows from the Join Features values to the Target Features values based on their relative spatial locations.

In this exercise, the Hospital_DFW_3mi buffer is the target layer.

• All other GIS layers will be joined to the target layer. The Spatial Join tool will be used to join the following layers to the target layer:

1. CDC Health Data
   • Match Option: INTERSECT -- Merge Rule: MEAN
2. GTFS Transit Stations
   • Match Option: INTERSECT -- Merge Rule: COUNT
3. LEHD Low Wage Workers
   • Match Option: INTERSECT -- Merge Rule: SUM

Create a Choropleth map to verify spatial joins¶

1. Change Symbology and Use Graduate Colors to present the results of Spatial Joins
   1. Example: Service areas by number of transit stations

Suitability Analysis using Business Analysis¶

Once the Spatial Join layer results are ready, we can use the Suitability Analysis tool to run the suitability model.

1. Add the Hospitals_DFW_3mi_SPJ layer to the Table of Contents

   

2. From the Analysis tab $\to$ Choose Business Analysis $\to$ Suitability Analysis

   

3. Make Suitability Analysis Layer

   • From Make Suitability Analysis Layer:
   • Input: Hospitals_DFW_3mi_SPJ
   • Layer Name: Suitability Analysis

   

4. Add Criteria to the suitability layer Once the Suitability Analysis layer is available:

   • Select/Activate it on Table of Contents
   • Choose +Add Criteria

   

5. Select Add Fields from Input Layer

   

6. Add Field Based Suitability Criteria

   

Add Fields from ArcGIS Online Data Browser¶

In addition to the data set from Spatial Joins, you can add other variables from ArcGIS Online Data Browser.

1. Select Add Variables from Data Browser

   

2. Select + Add Variables, Search Poverty

   

3. Select Pop w/Income Below Poverty Level (ACS 5-Yr)) -- Number Format (#), and run

   

Apply Weights to Suitability Model¶

1. From the Suitability Analysis tab, select Suitability Criteria, Change Weight in Suitability Analysis

   

2. Review the results

   

3. Add Additional variables to the suitability model.

   

4. Apply weights to the model,Review the results

   

Additional Sources¶

• It’s Harder for People Living in Poverty to Get Health Care
• Hospital Charity Care: How It Works and Why It Matters
• Suitability Analysis