Electric Vehicle Charging Access Analysis
A GIS and quantitative analysis project by Isaac Seiler examining EV charging infrastructure access, charger density, income, race, and transportation equity.
Overview
This GIS project investigated how race and household income affect Americans' proximity to electric vehicle charging infrastructure.
Working with county-level bivariate maps and a Wayne County, Michigan case study, we tested whether communities with different income levels or racial demographics had meaningfully different access to public battery-electric vehicle chargers.
My role focused on national charging station and income mapping, county-level spatial joins, bivariate symbology, and regression interpretation that translated geographic data into an accessible research poster.
Key Takeaways
- Nationally, neither household income nor racial identity strongly correlated with proximity to EV chargers.
- At the local level in Wayne County, the data also did not show a consistent racial or income disparity in EV charging access.
- The results suggest charger access is shaped by a more complicated mix of region, density, public investment, car culture, and rural-urban geography.
- Future work should examine rural communities, tract-level national data, and how access changes as EV adoption moves beyond early-adopter markets.