Assessment of Landslide-Induced Geomorphological Changes in Hítardalur Valley, Iceland, Using Sentinel-1 and Sentinel-2 Data

• Published in: Applied Sciences
• Main Authors: Dabiri, Zahra, Hölbling, Daniel, Abad, Lorena, Helgason, Jón Kristinn, Saemundsson, Thorsteinn, Tiede, Dirk
• Other Authors: Líf- og umhverfisvísindadeild (HÍ), Faculty of Life and Environmental Sciences (UI), Verkfræði- og náttúruvísindasvið (HÍ), School of Engineering and Natural Sciences (UI), Háskóli Íslands, University of Iceland
• Format: Article in Journal/Newspaper
• Language: English
• Published: MDPI AG 2020
• Subjects: Digital elevation model; Iceland; InSAR; Landslide; Landslide dammed lake; Object based image analysis; River; Sentinel-1; Sentinel-2; Skriðuföll; Áhættugreining; Fjarkönnun; Dammed Lake; Hítará; Hítardalur
• Online Access: https://hdl.handle.net/20.500.11815/2213; https://doi.org/10.3390/app10175848

Publisher's version (útgefin grein) 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. This research has been supported by the Austrian Science Fund (FWF) through the project MORPH (Mapping, monitoring and modelling the spatio-temporal dynamics of land surface morphology; FWF-P29461-N29) and the Doctoral Collage GIScience (DKW1237-N23), as well as by the Austrian Academy of Sciences (?AW) through the project RiCoLa (Detection and analysis of landslide-induced river course changes and lake formation). Peer Reviewed