Abstract: Slope factor screening and susceptibility assessment play a significant role in reducing landslide disaster risks, optimizing land use, protecting ecological environments, advancing scientific research, and enhancing governmental disaster management capabilities. This study first constructs a landslide susceptibility database considering two aspects: terrain and basic geological factors, as well as hydrological environment, surface cover, and socioeconomic factors. Then, utilizing GIS technology, it employs principal component analysis, grey relational analysis, geographic detector methods, and the coefficient of variations to diagnose the critical factors influencing landslide susceptibility in the Xiaojiang River Basin. In addition, it uses the weighted overlay tool in spatial analysis to conduct a comprehensive assessment of landslide susceptibility in the study area. The results indicate that the area proportions of extremely high, high, moderate, low, and extremely low susceptibility zones in the study area are 9.91:21.90:29.76:26.00:12.43, respectively. Verification was conducted on 176 different grades of landslide types in the study area, and 75.76% of the total number of large and mega-sized landslides are distributed within the high and extremely high susceptibility zones, which together cover 31.81% of the basin’s total area. Small and medium-sized landslides are entirely distributed in the moderate, low, and extremely low susceptibility zones, with few large and mega-sized landslides found in the low and extremely low susceptibility areas. The evaluation of landslide susceptibility using 15 critical factors, selected by the grey relational analysis model and the geographic detector method, agrees with the real-world conditions. This confirms the accuracy of the methods and can provide a scientific basis for landslide susceptibility assessment in the study area.

Key words: landslide susceptibility, factor screening, Geographic Information System, Xiaojiang River basin