Crime and Urban Facilities: Spatial Differences and Planning Responses in Changsha

With rapid urbanization, the spatial layout and functional characteristics of urban facilities have a strong correlation with the spatial distribution of criminal activities. Using Changsha City as a case study, this research analyzes 2023 urban crime data, Point of Interest (POI) data, and socioeconomic data. The Multi-scale Geographically Weighted Regression (MGWR) model and clustering analysis are applied to examine how different types of urban facilities influence the spatial heterogeneity of crimes and propose tailored urban planning recommendations and crime prevention strategies. The findings reveal the following: (1) The spatial distribution of crimes in Changsha’s central urban area demonstrates significant spatial heterogeneity. Property crimes dominate in frequency and spatial distribution, primarily clustering around commercial hubs and transport nodes, while violent crimes are more common in scenic areas and open spaces with high pedestrian flow. (2) The impact of built facilities on crime exhibits spatial variability. Facilities such as Financial Services Facilities (FSF) and Shopping facilities (SHF) significantly contribute to property crime in core urban areas, while Scientific, educational, and cultural facilities (SEC) suppress crime in university towns. Scenic spots and facilities (SPF) are associated with violent crimes near scenic site entrances and transport hubs. (3) Facility resource allocation and preventive strategies should be optimized based on dominant factors in different areas to enhance security management efficiency through precise and differentiated planning, fostering sustainable urban safety systems. This study provides insights into the spatial patterns of crime distribution and its dominant factors from the perspective of urban facilities, offering a scientific basis for improving urban crime management and facility planning.