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

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Názov: Correlation Analysis of Geological Disaster Density and Soil and Water Conservation Prevention and Control Capacity: A Case Study of Guangdong Province.
Autori: Lu, Yaping, Fu, Jingcheng, Tang, Li
Zdroj: Water (20734441); Sep2025, Vol. 17 Issue 17, p2527, 20p
Predmety: SOIL conservation, CLIMATE change, PROVINCES, SLOPES (Soil mechanics), GROUND vegetation cover, NATURAL disasters, MACHINE learning, GEOGRAPHIC spatial analysis
Geografický termín: GUANGDONG Sheng (China), CHINA
Abstrakt: 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. [ABSTRACT FROM AUTHOR]
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Databáza: Biomedical Index
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Abstrakt: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. [ABSTRACT FROM AUTHOR]
ISSN:20734441
DOI:10.3390/w17172527