<p>The upper reaches of the Jinsha River are located in the area of rapid uplift of the Tibetan Plateau, which has strong geological structure activities, huge relief of terrain, complex climate characteristics and frequent landslides. Therefore, the susceptibility mapping of landslide disaster in the upper reaches of Jinsha River is of great practical significance to ensure the safety of local people’s property and the safe development of hydraulic resources. However, the landslides in the study area are mainly large to giant landslides, which have a great effect on the change of the original geomorphic features after the occurrence of landslides. The landslide susceptibility mapping based on the geomorphic features after the occurrence of landslides will inevitably reduce the reliability of the evaluation results. In order to deal with landslide disaster more effectively, this study proposed a landslide susceptibility mapping method based on geomorphic restoration. Firstly, high-resolution remote sensing images and field investigation are used to obtain geomorphic feature data, and the damaged geomorphic features are restored and reconstructed. Then, the influence factor system of landslide susceptibility mapping, which includes 14 influencing factors such as lithology, is established, and the landslide susceptibility model is established by using support vector machine (SVM) model. The results show that the classification of slope units based on geomorphic recovery method is more reasonable, and the landslide susceptibility model has higher prediction accuracy. In conclusion, geomorphic restoration plays a key role in accurately mapping landslide susceptibility, and can provide valuable reference for regional disaster prevention and mitigation.</p>