Spatial Characteristics and Influencing Factors of Drug Crime in Yunnan Province

Drug crime is a serious global problem requiring attention. This study focuses on the spatial characteristics and factors influencing drug crimes at the provincial level. Understanding these factors is crucial to combating drug crime and maintaining social stability. In the past, most studies analyzed and discussed drug crimes at the macro and micro scales; however, research on the meso scale is still relatively lacking, and the special geographical location and complex socioeconomic conditions near the border of Myanmar in Yunnan Province had a high incidence of drug crimes, so it was still necessary to study drug crimes at the meso scale in Yunnan Province. This study considers drug crime cases from 129 counties and districts in Yunnan Province and employs Geographic Information System (GIS) statistical analysis, spatial autocorrelation analysis, and a spatial gravity model to examine the spatial difference patterns and spatial correlation network characteristics of drug crime in the province. Additionally, an indicator system for drug crime-influencing factors was constructed, which included economic level, income level, urbanization level, education level, floating population, impact of drug source areas, and terrain complexity. A regression analysis using a Spatial Durbin Model was conducted to analyze the relationship between these factors and drug crimes. First, the drug crime rate in Yunnan Province exhibits a notable spatial variation pattern, wherein clusters of high crime rates are primarily concentrated along the China-Myanmar border. Second, drug crimes in different districts and counties of Yunnan Province exhibit notable spatial correlation and agglomeration patterns on a global scale. Considering the spatial distribution, two main groups with strong spatial correlation networks were identified. The first group includes Kunming's central urban area and its surrounding districts and counties. The second group consists of districts and counties along the Yunnan border. This spatial distribution aligns with the cubic function curve depicting the relationship between distance from Myanmar and the density of drug crime rates. Third, among the influencing factors, the economic level, income level, urbanization level, and drug source area have a significant impact on the drug crime rate in Yunnan Province. Notably, factors related to the source of drugs had the most significant influence, displaying a significant negative correlation. The relationship between the distance from the China-Myanmar border (the source of drugs) and the drug crime rate follows an elongated "inverted S" shaped distribution curve. It demonstrated a significant initial decrease, followed by a slight increase and then a subsequent downward trend. Additionally, the economic level has a significant negative impact on the variation in drug crimes in Yunnan Province, whereas income and urbanization levels have a positive impact. In conclusion, this study focused on the research area of Yunnan Province, which is known for its high incidence of drug crimes, making it a suitable and significant region for this study. It conducted a quantitative analysis of the spatial differentiation characteristics and influencing factors of drug crimes in the Yunnan Province at a provincial mesoscale. Analyzing the exploration of the direction of these influencing factors contributes to the advancement of research on criminal geography.