Landslide mapping, monitoring and early warning by using optical remote sensing, InSAR and ground-based sensors: case study of the Qingpo landslide (Wenchuan, China)
- Chengdu University of Technology, Chengdu, China (weihuageo@gmail.com)
Studies of landslide evolution that improve the knowledge of ground movements are essential to understand the mechanism of deformation for landslide-prone territories to mitigate the associated risk. The large Qingpo landslide, with a volume of about 200,0000 m3, is located in a mega ancient landslide (with a width of 1300 m and a height difference about 400 meters), and a pylon is just located on the boundary of Qingpo landslide. How to accurately judge the historical evolution process, current evolution stage and the future evolution trend of the large landslides is very important for landslide and pylon monitoring and early warning. In this study, on the basis of a detailed on-site investigation, a total of 114 Sentinel-1A Images over five years with Level-1 Single Look Complex (SLC) mode and Interferometric Wide (IW) acquisition mode were downloaded from Copernicus Open Access Hub and were preprocessed by time series InSAR model, which allow us to produce deformation time series and mean deformation velocity maps. An automatic monitoring and warning scheme was designed, 10 sets of ground-based sensors, containing self-adapting crack meter, rain gauge, strain gauge and dip meter were installed, followed by real-time monitoring within one month. Ultimately, the temporal and spatial evolution characteristics of the landslide were comprehensively analyzed through on-site deformation investigation, long-term deformation monitoring by InSAR and ground-based real-time monitoring. The applicability of long-term remote sensing monitoring and real-time monitoring methods and how to use them together have also been verified. This study may can also provide a typical case for the comprehensive use of multi-source data.
How to cite: Zhao, W., Xie, M., and Ju, N.: Landslide mapping, monitoring and early warning by using optical remote sensing, InSAR and ground-based sensors: case study of the Qingpo landslide (Wenchuan, China), EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-3770, https://doi.org/10.5194/egusphere-egu2020-3770, 2020