Abstract: [Purposes] Landslides are widely distributed,frequent,and highly destructive geological disasters,and evaluating their susceptibility is crucial for disaster early warning and risk management.This paper proposes a WOA-BP landslide susceptibility evaluation model that incorporates DInSAR surface deformation features to address the limitations of traditional methods that only rely on static factors and neglect surface deformation characteristics. [Methods] Using Dejiang county,Guizhou province as the study area,the DInSAR technology based on Sentinel-1A satellite ascending data is employed to extract surface deformation features,combined with historical landslide data and 10 static factors,to evaluate landslide susceptibility. [Findings] The results show that compared to BP,LSTM,SVM,and RF models,the WOA-BP model's AUC value improves to 0.800,and its prediction accuracy increases by at least 10.19%. [Conclusions] The proposed model,which includes surface deformation features,effectively corrects nearly 30.9 percentage points of misclassified areas,significantly improving the reliability of landslide susceptibility evaluation and providing a new method for accurate landslide susceptibility assessment．

Key words: DInSAR technology, surface deformation features, WOA-BP model, landslide susceptibility evaluation