How applicable are DEMs created from Sentinel-1 for estimating the volume of landslides?

In this study, we explore the potential of Sentinel-1 synthetic aperture radar (SAR) data to create multi-temporal digital elevation models (DEMs) and their applicability to estimate the volume of landslides. Therefore, we develop a semi-automated and transferable workflow implemented within a Python package. We analyse the challenges related to radar interferometry for DEM gener-ation for selected large landslides with different characteristics in Austria and Norway. The quality of the DEMs is evaluated in comparison with reference data, and the proposed workflow is assessed in terms of reliability, performance, reproducibility, and transferability. The preliminary results are promising, however, the quality of the DEMs varies between the study areas. Hence, further re-search is necessary to enhance DEM quality to provide accurate and reliable landslide volume esti-mations. The findings contribute to increasing our knowledge of the applicability of Sentinel-1 DEMs for natural hazard research, particularly for landslide volume estimation.