Abstract: To address the issues of outdated landslide inventories and the lack of dynamic factors in the landslide susceptibility assessment process,this study takes Midu county,Yunnan province,as a case study.Surface deformation information from ascending and descending orbits was retrieved using the SBAS-InSAR technique.Combined with high-resolution optical imagery and slope data,landslides were identified to update the existing landslide inventory.In addition,based on 13 static conditioning factors such as slope and aspect,surface deformation rate was introduced as a dynamic factor,and a PSO-SVM model was employed to conduct landslide susceptibility assessment.The results indicate that:①The monitoring results from ascending and descending orbit in the study area exhibit significant differences both in deformation rates and in the spatial extent of deformation.These discrepancies are primarily attributed to variations in satellite orbit geometry as well as local topographic characteristics;②Integrating ascending and descending orbit datasets effectively overcomes the limitations of single-orbit observations,thereby improving the comprehensiveness and accuracy of landslide identification;③Incorporating dynamic factors yields higher assessment accuracy,with AUC,precision,recall,and F1-score reaching 0.886,0.847,0.851,and 0.855,respectively.This approach provides valuable reference for landslide prevention and early warning in Midu county.

Key words: landslide susceptibility assessment, SBAS-InSAR, PSO-SVM model, Midu county