Long Distance Relationships: Using Census Tract Data To Explore The Disconnect Between Food Bank Location and Need
The deliverable of this project is a visualization that shows the access to food banks in Ohio and the need for food banks in Ohio. This visualization was created by overlaying two different sources of data to see emerging trends.
To create the drive time data, first, a list of census tracts with center coordinates were produced. Then python code was run to calculate driving time from that center coordinate to the nearest foodbank. This was achieved by utilizing Open Source Routing Machine. Next, we received SNAP data about food insecurity from the Census. Our final step was overlaying these two data sources in QGIS to produce a meaningful visualization.
- Graphics Work: contains files relating to creating end visualization.
- Original Documents: outlines task and mission of project.
- Python Code: python code for drive time.
- Supporting Data: various data sources used throughout the project.
- Brett Bejcek
- Kyle Voytovich
- Justin Gurtz