This project evaluates spatial accessibility to healthcare facilities across seven adjoining neighborhoods in Southern Chicago using a multimodal network analysis and location-allocation modeling. The objective was to identify disparities in access and propose optimal facility locations that promote spatial equity, especially for underserved populations. Three demand weighting scenarios were analyzed: binary low-income status, total population, and a composite equity demand field. Each scenario was evaluated using the "Minimize Impedance" location-allocation method and a multimodal network incorporating walking and driving. Facilities were ranked based on total demand captured. Results show that the existing facilities poorly serve walkable populations and that new optimized sites significantly improve equitable access. This analysis demonstrates the effectiveness of GIS in data-driven facility planning to improve healthcare equity and advance socially just urban development.
Samuel Dadson (Wed,) studied this question.
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