Spatial Distribution and Influencing Factors of Leisure Agriculture Resources in Southern Jiangsu Region Based on Multi-Source Data

Leisure agriculture has become an essential driver of rural revitalization in China, yet most existing studies focus on provincial or municipal levels and rely on single-method approaches, leaving a gap in understanding spatial distribution patterns and driving mechanisms in highly urbanized metropolitan regions. This study addresses this gap by constructing a comprehensive leisure agriculture database for southern Jiangsu using multi-source data, including POI (Point of Interest), statistical yearbooks, and GIS datasets. Kernel density estimation, nearest neighbor index (NNI), geographic concentration index (GCI), and ordinary least squares (OLS) regression with VIF testing were applied to analyze spatial clustering and influencing factors. Results reveal that leisure agriculture resources exhibit significant clustering with a clear “core–periphery” pattern, concentrated in urban–rural transition zones. Agricultural output value and the number of A-level scenic spots significantly promote clustering, whereas GDP, population, and transportation density show weaker explanatory power. Theoretically, this study integrates multiple spatial statistical methods into a comprehensive analytical framework, enriching the understanding of leisure agriculture evolution under metropolitanization. Practically, it provides empirical evidence to support the optimization of leisure agriculture resource allocation, inform rural revitalization policies, and guide coordinated urban–rural planning in developed regions.