A Conceptual Framework for Equity-Centered Geospatial Analytics in Public Service Allocation Across Socioeconomically Diverse Major U.S. Cities

The spatial distribution of public services in major U.S. cities has long been shaped by historical patterns of racial segregation, political geography, and institutional inertia that continue to produce measurable inequities in service access across socioeconomically diverse communities. Despite significant advances in geospatial data science, remote sensing, and spatial analytics, the analytical frameworks governing public service allocation decisions in most large American municipalities remain insufficiently attentive to the equity implications of spatial distribution choices, producing investment patterns that systematically underserve low-income, minority, and historically marginalized neighborhoods while concentrating service quality improvements in already advantaged communities. This paper proposes a conceptual framework for equity-centered geospatial analytics in public service allocation, designed to transform the role of spatial analysis from a descriptive tool for mapping existing service distributions to a prescriptive, equity-oriented decision-support architecture that explicitly centers justice, accessibility, and community need as the primary criteria for public resource allocation. The framework integrates multi-dimensional equity measurement methodologies, spatial accessibility modeling, participatory mapping approaches, and algorithmic fairness principles within a unified analytical architecture applicable to a wide range of public service domains including transit, parks, libraries, health centers, schools, and emergency services. Drawing on environmental justice theory, spatial political economy, critical GIS scholarship, and advances in data-driven urban governance, the framework articulates five interconnected components spanning equity metrics design, spatial data integration, accessibility analysis, prioritization modeling, and monitoring and accountability mechanisms. The paper examines implementation challenges related to data availability, institutional resistance, community engagement, and algorithmic transparency, and proposes research directions that advance both the theoretical grounding and practical applicability of equity-centered geospatial analytics for public service governance in diverse urban contexts.