Uncovering Spatial Patterns of Residential Settlements, Segregation, and Vulnerability of Urban Seniors Using Geospatial Analytics and Modeling Techniques

Abstract

We harnessed the analytical power of geospatial analysis and modeling techniques, pioneering a novel approach to studying the spatial distribution of households with at least one senior aged 65 or over, known as senior households (SHHs). We developed and implemented a spatial modeling approach that disaggregates the senior household counts obtained from the U.S. Census block data to residential land parcels. This innovative method models the senior household count on each land parcel, generating a detailed, reliable synthetic microspatial dataset for urban senior studies. Robust spatial analysis techniques are then applied to examine senior household spatial distribution in the context of segregation and access vulnerability in the study area. Our research, conducted in the urban setting of Colorado Springs, provides a deeper understanding of the senior residential landscape and identifies vulnerability. Our research findings are not just academic but also practical tools for planners, policymakers, and community advocates in the city to understand senior residential settlements, segregation, and social inequality. Our adaptable approach can be applied using similar modeling and analysis techniques for different study areas. The synthetic data and its generation approach are valuable resources for future urban senior research, enabling further examinations of different senior residential neighborhood typologies beyond basic demographic and socioeconomic aggregated indicators. They can assist studies interested in analyzing the influence of local factors and neighborhood effects on active aging among individuals, as well as simulating individual senior choices and spatial behaviors. Furthermore, they serve as a comparison baseline for future attempts to develop synthetic senior population data with socioeconomic and health characteristics.