Students analyze Los Angeles County's urban landscape by investigating spatial relationships between environmental resources and community demographics, examining how park access, forest cover, and pollution levels vary across neighborhoods with different income and education patterns. Working as GIS analysts, they layer census data with environmental features and use Google Street View to ground-truth their findings, building evidence-based arguments about how geography and urban planning shape environmental justice and quality of life across one of America's most diverse counties.

In this spatial investigation, students analyze real San Francisco public health data to uncover correlations between sanitation incidents and underlying socioeconomic factors like income, education, homelessness, and park access. Working as GIS analysts, they combine map observations, demographic data layers, and Google Street View evidence to build nuanced, data-driven arguments about how urban inequality manifests in public health crises.

In this spatial investigation, students analyze NYC's 311 rat sighting data to identify correlations between rodent complaints and urban factors like housing density, income levels, restaurant concentrations, and building conditions. Working as GIS analysts, they combine map observations, demographic data layers, and Google Street View evidence to construct data-driven explanations about how infrastructure, sanitation resources, and socioeconomic patterns shape public health challenges in America's densest city.