JWAJournal of World Architecture2208-34802208-3499Bio-Byword Scientific Publishing Pty. Ltd.10.26689/jwa.v9i1.9808ArticleStudy on the Evaluation Methodology of Landslide Susceptibility Based on Spatial-scale Analysishttps://artdesignp.com/journal/JWA/9/1/10.26689/jwa.v9i1.9808LinZijing,TangJian,DaiYiling,LuoBing,ChenAnqi2025912025-03-07Landslides are significant natural geological hazards. Landslide susceptibility evaluation involves the quantitative assessment and prediction of potential landslide locations and their probabilities. Research has explored susceptibility assessment methods based on spatial-scale analysis. This evaluation integrates two models—global and local scale—using a CNN model and a PSO-CNN coupled model. Key aspects include selecting evaluation factors and optimizing model parameters for landslide susceptibility at different scales. A major focus of current landslide research is utilizing prediction results to enhance prevention and control measures.

Ministry of Land and Resources, 2020, China Land Resources Bulletin, China.

China Geo-Environmental Inspection Institute, 2020, National Geological Hazards Bulletin.

Zhu J, Zhang L, Zhou X, 2014, Time Scale Characterisation of Regional Landslide Susceptibility Assessment. China Soil and Water Conservation, 2014: 18–21+ 69.

Zhang S, 2019, Three-Dimensional Seismic Slope Stability Assessment With the Application of Scoops3D and GIS: A Case Study in Atsuma, Hokkaido. Geoenvironmental Disasters, 6(1): 43–46.

Xu J, Sun D, Wang Y, 2020, Landslide Susceptibility Zoning of Fengjie County Based on GIS and Improved Hierarchical Analysis. Journal of Chongqing Normal University (Natural Science Edition), 37: 36–44 + 2 + 142.

Wu CR, Jiao YM, and Wang JL, 2021, Evaluation of Landslide Susceptibility in Shuangbai County Based on the Coupled Frequency Ratio-Logistic Regression Model. Journal of Natural Hazards, 30: 213–224.

Zhu Q, Zhang M, Ding Y, 2021, A Fuzzy Logic Analysis Method for Regional Landslide Sensitivity Constrained by Spatial Characteristics of Environmental Factors. Journal of Wuhan University (Information Science Edition), 46: 1431–1440.

Tian N, Lan H, Wu Y, 2020, Performance Comparison of Artificial Neural Network and Decision Tree Model in Landslide Susceptibility Analysis. Journal of Geo-Information Science, 22: 2304–2316.