Correlation Analysis of Geological Disaster Density and Soil and Water Conservation Prevention and Control Capacity: A Case Study of Guangdong Province

Abstract

This study investigates the spatial coupling between geohazard susceptibility and soil conservation capacity in Guangdong Province, China, using integrated spatial analysis and machine learning approaches. Through kernel density estimation, hotspot analysis, principal component analysis (PCA), and t-SNE clustering applied to 11,252 geohazard records and nine soil conservation factors, we identify three critical mechanisms: (1) Topographic steepness (LS factor) constitutes the primary control on geohazard distribution (r = 0.162, p < 0.001), with high-risk clusters concentrated in northeastern mountainous regions (Meizhou-Huizhou-Heyuan); (2) Vegetation coverage (C_mean) mediates rainfall impacts, exhibiting significant risk reduction (r = −0.099, p < 0.001) despite counterintuitive negative correlations with mean rainfall erosivity; (3) Soil conservation effectiveness depends on topographic context, reducing geohazard density in moderate slopes (Cluster 0: 527.04) but proving insufficient in extreme terrain (Cluster 2: LS = 20.587). The emerging role of rainfall variability (R_slope, r = 0.183) highlights climate change impacts.