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Abstract Loess landslides in mountainous regions of the Ili Valley have resulted in numerous casualties as well as huge economic losses. However, the characteristics and driving mechanisms of surface deformation related to loess landslides in mountainous areas remain unclear, thus limiting our ability to identify, monitor, and warn populations of potential catastrophic events. This study was conducted in a typical mountainous area of the Ili Valley, where landslides have been documented by field investigations, unmanned aerial vehicle images, and light detection and ranging data. With ascending and descending Sentinel‑1 time series synthetic aperture radar images, acquired using the small baselines subset method, surface deformation was observed for the period from October 2014 to October 2021, and loess landslides were concurrently mapped to delineate hazardous areas. Using the methods of this study, we were able to identify 74.4% of previously documented landslides. Additionally, we observed a seasonal time-series of deformation that had a time delay of less than one month and was responsive to rainfall. Our analysis of the characteristics and driving mechanisms of creeping landslides in the Ili Valley led to the compilation of a new inventory of active slopes that will offer valuable guidance for land managers tasked with implementing disaster prevention measures.
Fan et al. (Sat,) studied this question.