Abstract: The identification of potential landslide areas is central to current geological disaster prevention efforts, and deformation monitoring is the most direct and effective way to achieve this. Compared to traditional monitoring methods, SBAS-InSAR technology offers clear advantages in monitoring large-scale deformation in mountainous regions with complex topography. Frequent landslides along the Khunjerab to Jaglot section of the Karakoram Highway(KKH)in the China-Pakistan Economic Corridor seriously threaten the highway's safe operation and local residents' livelihoods. Therefore, accurate identification of potential landslide areas is crucial for effective disaster prevention and mitigation. This paper utilized SBAS-InSAR technology and Sentinel-1A data to obtain surface deformation in the Line of Sight(LOS)direction. The deformation in LOS was then converted to the deformation along the slope direction by analyzing the spatial geometric relationship between the radar line of sight and the slope surface. After verifying the reliability of the SBAS-InSAR deformation results, kernel density analysis was performed on the deformation points, using the deformation rate in the slope direction as the weight, to identify potential landslide areas. Results indicate that potential landslide areas are primarily located in the main river valleys along the China-Pakistan Highway, with the Khunjerab to Sost and Jaglot to Gilgit sections being the most affected, while tributary valleys are less impacted. Statistical analysis of the potential landslide areas and disaster distribution shows that while the potential landslide area covers only 31.2% of the total area, it accounts for 66.4% of the total number of disaster points, indicating high reliability in the identification results.