期刊
APPLIED SCIENCES-BASEL
卷 10, 期 17, 页码 -出版社
MDPI
DOI: 10.3390/app10175848
关键词
object-based image analysis; Sentinel-1; Sentinel-2; digital elevation model; InSAR; landslide; landslide-dammed lake; river; Iceland
类别
资金
- Austrian Science Fund (FWF) [FWF-P29461-N29, DKW1237-N23]
- Austrian Academy of Sciences (OAW) through the project RiCoLa (Detection and analysis of landslide-induced river course changes and lake formation)
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 Hitardalur 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 Hitara 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.
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