Based on 2018 theft-case data from China Judgments Online, this paper investigates the spatial patterns and formation mechanisms of theft crimes in Kunming’s main urban area. Combining GIS spatial analysis and crime-geography theories, this study adopts Average Nearest Neighbor, Kernel Density Estimation and Buffer analysis to explore crime distribution and driving forces. The results show that theft cases present significant spatial clustering across the study area, with an R value of 0.393 and Z-score of -34.953. Hot-spots are concentrated along major urban roads within mixed “commerce-government-residence” zones dominated by core-service POIs. Dense pedestrian flows, complex social-spatial environments, extended crime-opportunity windows and hot-spot self-reinforcement jointly promote the aggregation of theft incidents. This research highlights that mixed-function neighbourhoods are key zones for security governance. It provides empirical evidence for refined urban anti-theft governance and rational spatial allocation of police and surveillance resources in western Chinese provincial capitals.

Wang Xudan. Spatial Patterns and Formation Mechanisms of Theft Crimes in the Main Urban Area of Kunming. Academic Journal of Humanities & Social Sciences (2026), Vol. 9, Issue 8: 46-52. https://doi.org/10.25236/AJHSS.2026.090807.

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