Case Studies in Geospatial Social Science
About
Case studies bring together the skills from the other courses (finding and collecting data, analysis and visualization) to answer one real social science question from start to finish. Each case study explains the background and the methods, then lets you work through the analysis yourself, in Jupyter notebooks or in QGIS.
| Case study | Question | Tools |
|---|---|---|
| Park Access (intermediate; Python or QGIS) | Who can walk to a public park in Lafayette and West Lafayette, Indiana, and are children and households without a car as well served as everyone else? | Python notebook or QGIS |
| Food Deserts | Where do people have low income and live far from a supermarket? How does the USDA measure this, and can we rebuild its analysis from open data? | Python notebooks |
| Grocery Access (two parts) | How would a team map grocery stores in the field, and how far must people travel to a supermarket along the road network in Lafayette and West Lafayette, Indiana? | QField (demonstration), QGIS |
Start with Park Access: it uses only the Geoprocessing tools from the Data Processing course. Food Deserts and Grocery Access are more advanced. More case studies will be added over time.
Prerequisites
- A free CyberFaCES account to run the notebooks
- A free Census API key for the Expert notebook (see Setup below)
- QGIS installed on your computer, for the park access (QGIS version) and grocery access case studies (see Setup below)
- Basic Python and pandas. The Data Collection course's Census notebooks are good preparation: they cover census tracts, GEOIDs and joining tables to maps.
- For the park access case study: the Data Processing course's Geoprocessing module, in Python or QGIS
- For the grocery access case study: basic familiarity with QGIS, for example from the Foundations course's Getting Started with QGIS module
This course is part of Enabling the Geospatial Turn in the Social Sciences, a set of training modules developed at Purdue University with support from the National Science Foundation.
| Type | Course |
|---|---|
| Level | Expert |
| Length | 6 hours |
| Topics |
python QGIS Community: Spatial Turn |
Modules
-
Park Access in Lafayette (Python)
Module 1 • 1 hour
Who can walk to a public park in Lafayette and West Lafayette, and are children and households without a car as well served? In Python
-
Park Access in Lafayette (QGIS)
Module 2 • 1 hour
Who can walk to a public park in Lafayette and West Lafayette, and are children and households without a car as well served? In QGIS
-
Case Study: Food Deserts
Module 3 • 1 hour
Where do people have low income and live far from a supermarket? Map the USDA Atlas, then rebuild its analysis from open data
-
Grocery Access Part 1: Mapping Stores with QField
Module 4 • 45 minutes
How a team maps grocery stores in the field with QField (demonstration)
-
Grocery Access Part 2: Network Analysis in QGIS
Module 5 • 1 hour
How far people must travel to a supermarket along the road network in Lafayette and West Lafayette, in QGIS
Instructor
Aniket Dev Roy
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