Existing tools for measuring food access — including the USDA’s Food Access Research Atlas — suffer from insufficient spatial granularity, binary classifications, and limited integration of health outcome data. This project proposes an alternative methodology using spatial analysis of Google Maps data combined with CDC health outcomes data from the PLACES dataset.
A geographically weighted regression model for New York State demonstrates the relationship between food access and obesity rates at the census tract level.
Outputs#
- Rangarajan, S. (2023). Refining large-scale spatial metrics of food access. Applied Geography, 159, 103084. Link