Landslide mapping and analysis are essential aspects of hazard and risk analysis. Landslides can block rivers and create landslide-dammed lakes, which pose a significant risk for downstream areas. In this research, we used an object-based image analysis approach to map geomorphological features and related changes and assess the applicability of Sentinel-1 data for the fast creation of post-event digital elevation models (DEMs) for landslide volume estimation. We investigated the Hítardalur landslide, which occurred on the 7 July 2018 in western Iceland, along with the geomorphological changes induced by this landslide, using optical and synthetic aperture radar data from Sentinel-2 and Sentinel-1. The results show that there were no considerable changes in the landslide area between 2018 and 2019. However, the landslide-dammed lake area shrunk between 2018 and 2019. Moreover, the Hítará river diverted its course as a result of the landslide. The DEMs, generated by ascending and descending flight directions and three orbits, and the subsequent volume estimation revealed that-without further post-processing-the results need to be interpreted with care since several factors influence the DEM generation from Sentinel-1 imagery.
CITATION STYLE
Dabiri, Z., Hölbling, D., Abad, L., Helgason, J. K., Sæmundsson, P., & Tiede, D. (2020). Assessment of landslide-induced geomorphological changes in Hítardalur Valley, Iceland, using sentinel-1 and sentinel-2 data. Applied Sciences (Switzerland), 10(17). https://doi.org/10.3390/app10175848
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