Abstract
Every year slope hazards and landslides cause significant damage in the mountainous areas of Iran, including the eastern Alamut region in Qazvin province. Recently, radar data has been widely used to detect ground surface movements, slope slow motions, and active landslides. In the present study, using the Sentinel 1A satellite descending data in the period from 2018 to 2020, with the Small Baseline Subset (SBaS-InSAR) and also with the digital elevation model (DEM) difference methods, slope motions and Earth surface displacements have been extracted to provide the important goal of detecting new and active landslides and updating the landslide map to predict landslide risk. Results show that in the SBaS model, which was validated with GPS data, field visits and Google Earth images, accuracy was relatively good (AUC = 0.78), and the average annual movement during this period was estimated at -48.6 to 40.2 mm and fourteen landslide zones in the region, are identified among which some of the previous landslides are still active. To detect the landslide that occurred in Khobkuh on April 3rd, 2020, DEM difference model estimated the surface changes between -1.62 to 2.75 meters and differential interferometry model estimated the displacement rate in this area from -25 to 70 mm. These methods have many advantages for estimating the Earth surface displacement, subsidence and landslides, determining vulnerable areas in mountainous areas and reducing financial and human losses.
