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• W2901778855 abstract "Abstract The 2008 Wenchuan earthquake in Sichuan, China, dramatically changed the terrain surface by inducing large numbers of landslides. Due to the lack of adequate pre- and post-earthquake Digital Elevation Models, the landslide volume estimation was done either using empirical area-volume relationships over large areas or by field surveys in a few catchments with debris flow threats. The trend of the change of volume of loose materials in the earthquake affected area over the decade since the earthquake remains largely unknown. In this study we were able to address this issue using nine DEMs taken at different years and from different sensors to study the change in loose material volume caused by co-seismic and post-seismic landslides over a period of 9 years. The area around the towns of Yingxiu and Longchi, for which also multi-temporal landslide inventories were available, was selected for this study. Methods to register the DEMs and minimize their vertically bias were applied. The quality of the DEMs was assessed through GCPs and terrain representation. As could be expected, high resolution DEMs showed more realistic volume estimates than the low resolution ones. The analysis showed that the frequency and magnitude of the landslide volume dynamics decreases significantly after the early post-seismic period, and in the last years human activities became a more dominate factor than mass movements. The post-seismic material loss from 2008 to 2014 was close to the gained volume of the co-seismic landslides, and the depletion of the materials was mostly at the toes of the co-seismic landslides. The analysis was done based on gain and loss calculated from the DEMs, and actual volumes could not be calculated due to unknown failure surface depths of the landslides." @default.
• W2901778855 created "2018-11-29" @default.
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• W2901778855 date "2019-01-01" @default.
• W2901778855 modified "2023-10-14" @default.
• W2901778855 title "Analysing post-earthquake mass movement volume dynamics with multi-source DEMs" @default.
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• W2901778855 doi "https://doi.org/10.1016/j.enggeo.2018.11.010" @default.
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