This study integrates spatial resilience with multi-source data to jointly design and optimize the allocation pathways of public healthcare resources. The Average Nearest Neighbor algorithm identifies spatial distribution patterns and agglomeration levels of medical facilities. Standard Deviation Ellipse Analysis captures spatial development trends and directional evolution. DBSCAN reveals spatial clustering characteristics of medical facilities. The 2SFCA algorithm calculates spatial accessibility of healthcare institutions. Particle Swarm Optimization determines optimal spatial locations for medical facility coverage. Experimental results demonstrate that the average spatial accessibility score improved from 0.40×10⁻⁵ to 0.81×10⁻⁵ under this methodology. In Qingshuihe County and Wuchuan County, spatial accessibility scores rose from approximately 0.10×10⁻⁵ to over 0.72×10⁻⁵. The number of medical staff and hospital beds increased to 4.6 personnel and 6.3 beds, respectively. The average time spent seeking medical care decreased to 16 minutes, and the reserve rate for critical care beds rose to 18%. This holds significant implications for the scientific allocation of public medical resources in Hohhot. This project is based on the “Research on the Optimal Allocation of Public Medical Resources in the Urban Area of Hohhot Based on Multi-Source Data and Spatial Resilience Analysis – Planning Path under the Orientation of Healthy Inner Mongolia” (2025116006), a key school-level project of the College Students’ Innovation and Entrepreneurship Training Program of Inner Mongolia University of Technology.
