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- Title
光学遥感与InSAR 结合的金沙江白格滑坡 上下游滑坡隐患早期识别.
- Authors
陆会燕; 李为乐; 许强; 董秀军; 代聪; 王栋
- Abstract
On October 11 and November 3, 2018, two large-scale landslides occurred in the upstream of the Jinsha River near the Baige Village, Polo Town, Jiangda County, Tibet Autonomous Region. Al- though the drainage was carried out by manual intervention, it still caused severe losses to the residents and transportation facilities in the downstream. Whether there are similar large-scale potential landslides in the upstream and downstream of the Jinsha River has become the social focus issue after the Baige Landslide di- saster occurred. Firstly, high-resolution optical satellite images are used to interpret and qualitatively evalu- ate the potential landslide hazards in the upstream of the Baige Landslide within 30 km and the downstream of the Baige Landslide within 100 km. A total of 51 potential landslides are identified, of which 10 potential landslides in the downstream of the Baige Landslide within 70-100 km have the risk of blocking the river. On this basis, the ALOS PALSAR-1 and Sentinel-1A radar satellite data are collected in the key area (70- 100 km downstream of the Baige Landslide) with the risk of river blockage. The quantitative detection and analysis of the potential surface deformation of landslides are carried out by using the small baseline subsets interferometric synthetic aperture radar (SBAS-InSAR). Seven potential landslides are detected to have sig- nificant deformation, of which three are at higher risk of river blockage. The research results have been sub- mitted to the Ministry of Emergency Management, Sichuan Natural Resources Department, China Rail- way Second Academy Engineering Group Co. Ltd. and other departments and units, providing a reference for the prevention and control of geological hazards in the upstream and downstream of the Baige Landslide and the route selection of Sichuan-Tibet railway.
- Subjects
SICHUAN Sheng (China); EMERGENCY management; LANDSLIDES; DEFORMATION potential; DEFORMATION of surfaces; OPTICAL remote sensing; REMOTE-sensing images; SYNTHETIC aperture radar
- Publication
Geomatics & Information Science of Wuhan University, 2019, Vol 44, Issue 9, p1342
- ISSN
1671-8860
- Publication type
Article
- DOI
10.13203/j.whugis20190086