Spatiotemporal patterns and driving mechanisms of agricultural land crimes in Jiangsu Province, China
Yu Gao
School of Information Technology, Nanjing Police University
DOI: https://doi.org/10.59429/pest.v8i3.15417
Keywords: agricultural land crimes; GeoDetector; spatial analysis
Abstract
Early warning and targeted crackdown on agricultural land crimes are crucial to China's food security and ecological civilization strategies. Revealing the spatial patterns and driving factors of such crimes is essential for governance decisions. Using judicial data from 2015 to 2024 on China Judgments Online for Jiangsu Province, this study employed spatial autocorrelation analysis and the GeoDetector model to explore these patterns and factors. The results indicated that: (1) crimes in Jiangsu exhibited significant spatial agglomeration, with hotspots in the northwestern and southwestern regions and low-risk areas in the central and eastern parts; (2) slope was the primary driving factor, followed by socioeconomic activities and landscape characteristics of farmland and built-up land; and (3) interactions among driving factors showed synergistic enhancement effects. Consequently, prevention measures should account for natural conditions, human activities, and landscape patterns to mitigate these effects and improve governance efficiency.
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