GRG 356 Spatial Data Science and Maps Featured Projects – Fall 2025 Here are a set of selected course projects created by students who enrolled in GRG 356 Spatial Data Science and Maps during the Fall 2025 semester. These projects showcase how students apply spatial data science methods — from machine learning and spatial regression to GeoAI and crowdsourced data analysis — to investigate real-world geographic challenges spanning transportation equity, urban energy planning, public health, walkability, and political geography. Browse the abstracts and representative figures below to explore their work. Crowdsourced Data and Geology Abstract Representative Figure The Hidden Cost of Place: How Transportation Shapes Affordability in Austin Abstract Representative Figure Precision: Walkability Assessment with GenAI and LiDAR Abstract Representative Figure Green and Healthy Communities: Urban Greenery and Health Outcomes in the Rio Grande Valley Abstract Representative Figure Is Irreligion Correlated with Increase in Leftism? Evidence from 23,000 Constituency-Years Abstract Representative Figure Building-Level Assessment of Rooftop Solar Photovoltaic Potential in Austin, Texas Abstract Representative Figure
