Refined InSAR method for mapping and classification of active landslides in a high mountain region: Deqin County, southern Tibet Plateau, China

The mapping and classification of active landslides in high mountainous regions provide crucial information about the location and types of geohazards. Additionally, this process plays a vital role in ensuring the safety of the geological environments in mountainous towns. In this study, we presented a refined InSAR approach for mapping and classifying active landslide hazards in Deqin County, Tibetan Plateau, China. The study area is characterized by a high altitude and extremely rugged terrain. Consequently, conventional InSAR methods are limited in precisely estimating landslide deformation owing to severe atmospheric delays. To this end, we first propose a block-based linear model to correct tropospheric artifacts. This model considers the spatial variability of the atmosphere and provides an opportunity to accurately estimate heterogeneous atmospheric delays over high mountainous areas without any external data. Compared with the traditional global-window linear model and the GACOS approach, the new method demonstrated outstanding performance in reducing atmospheric artifacts. Second, based on the knowledge mapping of landslide types, we proposed a semi-automatic procedure to map and classify landslides using InSAR-derived displacements and auxiliary data (i.e., C-index and high-resolution optical images). Our results obtained from ascending and descending Sentinel-1 images revealed, for the first time, that there were 317 active landslides in Deqin County between May 2017 and June 2021. Among these, 10.7% were associated with slide activity, 7.9% with fall deformation, and the majority (81.4%) with flow movement. These results were cross-verified and evaluated using an a priori inventory map obtained from the visual interpretation of optical images and geological field surveys. This study demonstrates that InSAR can accurately map and classify active landslides over difficult mountainous terrains, provided the associated phase errors are effectively restrained.