The Community Capitals Framework (CCF) offers a structured approach to assessing community strengths and weaknesses across seven forms of capital—natural, cultural, human, social, political, financial, and built. Over the past several years, our team has collected and analyzed data indicators aligned with this framework to evaluate the strengths and weaknesses of cities and counties in the Midwest United States. Drawing on publicly available data, we’ve assessed how various forms of capital, such as built infrastructure, human services, and social networks vary across communities. While these assessments have offered valuable insights at the county and city level, they often mask important disparities within communities themselves. Our current focus shifts to analyzing those same indicators at a finer spatial scale to better understand how access to critical services and assets is distributed within individual communities.

To uncover these internal disparities, we apply spatial analysis techniques using free and open-source software (FOSS) and openly available geospatial data. We begin by analyzing access to key community assets such as parks, healthcare facilities, broadband infrastructure, and educational institutions across a multi-county rural region, identifying differences in regional availability. We then zoom in on selected case study communities to map the neighborhood-level distribution of those same assets, revealing gaps in access that are often hidden by broader county- or city-level aggregates.

Using free and open-source tools we perform proximity analysis, service area analysis, and spatial overlays to identify underserved areas—places where residents may face barriers to opportunity, infrastructure, or essential services. Our case studies illustrate how a place-based, spatial lens grounded in open data tools can guide more equitable rural planning, investment, and community engagement.

This session will highlight our methods, case study findings, and how these insights can inform targeted investment in small rural communities. Our reproducible, open-source workflow is designed for use by researchers, planners, and community stakeholders aiming to apply geospatial analysis in low-resource environments.