<p>Earthquakes in mountainous areas can cause numerous co-seismic landslides and significantly impact slope stability over time, and the slopes affected could evolve into slow-moving landslides. Both co-seismic landslides and slow-moving landslides may result in severe destruction at different time scales. These two types of landslides exhibit differences in the occurrence mechanism; as such, these two types of landslides cannot be detected and monitored with an identical method. Most studies emphasize either identifying co-seismic landslides or monitoring ground deformations of slow-moving landslides. In this study, a method combining change detection and advanced differential interferometric synthetic aperture radar (A-DInSAR) is proposed, which allows for the identification of co-seismic landslides and slow-moving landslides simultaneously. The change detection method employed to recognize co-seismic landslides is based on the combined use of SAR data and optical imagery due to the drastic ground surface changes of co-seismic landslides, and the A-DInSAR method is adopted to identify earthquake-induced slow-moving landslides by analyzing ground deformations before and after the earthquake. A case study of the 18 November 2017 Mw 6.4 Nyingchi earthquake in Tibet, southwest China, is undertaken to illustrate the effectiveness of this approach, and the resulting true positive ratio of the co-seismic landslides obtained is 0.95. The results show that the combined use of SAR data and optical imagery yields a more accurate identification of co-seismic landslides, compared with solely using SAR data or optical imagery. Furthermore, 58 slow-moving landslides are identified by comparing the time-series ground deformations before and after the earthquake. The results indicate that satellite imagery could provide effective identification of earthquake-induced landslides, which is essential for hazard risk assessment.</p>