Understanding the Slow Motion of the Wangjiashan Landslide in the Baihetan Reservoir Area (China) from Space-Borne Radar Observations
Author(s): |
Mingtang Wu
Xiaoyu Yi Jiawei Dun Jianyuan Yang Wei Cai Guoqiang Zhang |
---|---|
Medium: | journal article |
Language(s): | English |
Published in: | Advances in Civil Engineering, January 2022, v. 2022 |
Page(s): | 1-14 |
DOI: | 10.1155/2022/1766038 |
Abstract: |
The analysis of landslide evolution using archived optical remote-sensing images is common, but it is often limited by the acquisition frequency, cloud cover, and resolution. With the development of space-borne radar observation technology, small baseline subset interferometric synthetic aperture radar (SAR) technology provides a new technical approach for detecting landslide deformation before disasters. The Sentinel-1A SAR datasets (20170219–20210330) were used to study the time-series deformation characteristics of the Wangjiashan landslide in the Baihetan Reservoir area before its impoundment. The time-series results show that the Wangjiashan landslide was in an initial deformation state in the prior four years, and the deformation first occurred in the middle part and then expanded to the landslide toe and crown retrogressive movement characteristics. Combined with an analysis of field deformation signs, these findings suggest that the upper landslide mass formed a local sliding surface, which caused serious deformation of the road. An analysis of historical rainfall data revealed that the Wangjiashan landslide is sensitive to rainfall, and the deformation is not only significantly correlated with cumulative rainfall but also influenced by concentrated heavy rainfall. The research in this study provides a basis for the monitoring, early warning, and risk management of the Wangjiashan landslide during the impoundment period. This work also provides a useful reference for investigations using space-borne SAR Earth observations in geological disaster prevention and control. |
Copyright: | © Mingtang Wu et al. et al. |
License: | This creative work has been published under the Creative Commons Attribution 4.0 International (CC-BY 4.0) license which allows copying, and redistribution as well as adaptation of the original work provided appropriate credit is given to the original author and the conditions of the license are met. |
10.64 MB
- About this
data sheet - Reference-ID
10678984 - Published on:
18/06/2022 - Last updated on:
10/11/2022