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Monitoring and analysis of Woda landslide stability (China) combined with InSAR, GNSS and meteorological data.

Authors :
Li, Bingquan
Jiang, Wenliang
Li, Yongsheng
Luo, Yi
Qian, Haitao
Wang, Yanchao
Jiao, Qisong
Zhang, Qingyun
Zhou, Zihan
Zhang, Jingfa
Source :
Natural Hazards & Earth System Sciences Discussions; 4/13/2021, p1-23, 23p
Publication Year :
2021

Abstract

Detecting the slow motions of high and distant landslides in remote mountain areas has always been a problem. This paper takes the Woda landslide along the Jinsha River as an example to monitor landslide movement. Although some parts of the landslide body have been found to have moved in recent years, the timing and magnitude of motion have not been systematically monitored or interpreted. Here, we apply the SBAS time series strategy using 65-scene Sentinel-1A/B satellite InSAR images and study the spatial distribution and temporal behaviour of landslide movements between July 4, 2018, and August 29, 2020. Our research results show that the cumulative deformation on the left side of the landslide body with concentrated deformation was approximately 200 mm during the 2-year observation period. By calculating the relationship between the InSAR time series and the precipitation around the landslide, it is found that the landslide deformation is closely related to rainfall. GNSS technology is also deployed on the landslide mass and effectively complements InSAR technology. Simultaneously, based on the results of field surveys and hydrological data analysing the landslide's spatial deformation characteristics and deformation factors, the landslide deformation can also be inferred to be related to precipitation. The method used in this paper can be used for early recognition and early warning of high and remote landslides. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
21959269
Database :
Complementary Index
Journal :
Natural Hazards & Earth System Sciences Discussions
Publication Type :
Academic Journal
Accession number :
149874749
Full Text :
https://doi.org/10.5194/nhess-2021-101