Evaluation of landslide susceptibility in the gentle hill-valley areas based on the interpretable random forest-recursive feature elimination model

This study aims to evaluate landslide susceptibility and explain the internal mechanism of gentle hill-valley through SHAP partial interpretation and PDP partial dependency map based on the random forest-recursive feature elimination model to provide references for geological disaster prevention and control. We used the optimized random forest algorithm to analyze the landslide susceptibility of the specific hill-valley areas and established a landslide susceptibility evaluation model. The recursive feature elimination algorithm was used to eliminate noise factors. Sixteen factors of four types, including terrain, geology, environmental conditions, and human activities, were selected to build a landslide hazard factor database for the Hechuan district. Then we combined 754 historical landslide sites in the Hechuan district with the factor database to derive a landslide susceptibility zoning map for the study area, and the factor importance was ranked using the random forest algorithm. Finally, a partial depen