Under the background of global climate warming, permafrost degradation is intensifying, surface stability is continuously weakening, and consequently, landslides and other geological hazards are occurring with increasing frequency. Due to the incompleteness of the landslide database in the permafrost degradation areas of Northeast China, systematic research on surface deformation monitoring and landslide identification in this region remains relatively insufficient. In this study, the integrated area comprising Sunwu County and the Red Frontier Farm in Aihui District was selected as the study area. Using SBAS‑InSAR technology, 61 scenes of Sentinel‑1B data acquired from October 2018 to October 2020 were processed to obtain surface deformation results over the study area, and landslide identification was then carried out in combination with optical remote sensing imagery. The results show that SBAS technology demonstrates high feasibility for landslide monitoring and identification in mountainous areas within the permafrost region of Northeast China, and its integration with optical remote sensing enables precise delineation of landslide boundaries. By combining SBAS‑InSAR with optical remote sensing, a total of 119 landslides were identified, among which the maximum annual deformation rate reached 45 mm/a. The joint application of these two techniques significantly improves the accuracy of landslide hazard identification in permafrost regions, offering a new approach for disaster detection and prevention in such areas.
 

Landslide identification; SBAS-InSAR; Optical remote sensing; Permafrost regions