Journal of Guangxi Normal University(Natural Science Edition) ›› 2026, Vol. 44 ›› Issue (5): 151-167.doi: 10.16088/j.issn.1001-6600.2025091701

• Ecology and Environmental Science Research • Previous Articles     Next Articles

Evaluation of landslide susceptibility and analysis of disaster-causing factor detection in Guilin City, China

Jia Yanhong1,2,3*, Li Xinjing3, Tang Shiyu3   

  1. 1. Guangxi Key Laboratory of Environmental Processes and Remediation in Ecologically Fragile Regions (Guangxi Normal University), Guilin Guangxi 541006, China;
    2. Key Laboratoryof National Geographic Census and Monitoring, Ministry of Natural Resources (Wuhan University), Wuhan Hubei 430070, China;
    3. College of Environment and Resources, Guangxi Normal University, Guilin Guangxi 541006, China
  • Received:2025-09-17 Revised:2025-11-15 Online:2026-09-05 Published:2026-07-24

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Abstract: Scientifically precise spatial distribution maps of landslide susceptibility provide an important basis for landslide disaster prevention and control, as well as the construction and planning of social infrastructure. Based on 752 sets of historical landslide data, this study comprehensively applied an information value model using frequency ratios and an AHP-GIS model to conduct a landslide susceptibility assessment, ultimately producing a 30 m-resolution landslide susceptibility zoning map for Guilin City. Furthermore,with the help of geographical detector, an explanatory power analysis was conducted on ten evaluation factors: distance to faults, precipitation, slope, elevation, population distribution, lithology, aspect,normalized difference vegetation index (NDVI), distance to water systems, and distance to roads, to assess their influence on landslide susceptibility in Guilin City. The research results indicate that:1) The spatial distribution of landslide susceptibility in Guilin exhibits a pattern of higher susceptibility in the south and lower in the north; 2) The overall level of landslide susceptibility in the city is relatively high, with extremely high and high susceptibility areas accounting for over 50% of the total; 3) Single-factor detection analysis shows that lithology has the most significant impact on landslide susceptibility, while the interaction of factors exhibits nonlinear enhancement and two-factor enhancement relationships. Among these, the interaction between lithology and precipitation has the strongest explanatory power (14.91%). The models used in this study effectively assess landslide susceptibility and improve analytical accuracy. The combined application of multiple models not only avoids the one-sidedness of a single evaluation method but also provides a methodological reference for landslide disaster assessment and prevention in other regions.

Key words: landslide, susceptibility, causative factors, information model, geodetector, Guilin City, China

CLC Number:  P642.22
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