Abstract
The Pusa landslide, in Guizhou, China, occurred on 28 August 2017, caused 26 deaths with 9 missing. However, few studies about the pre-event surface deformation are provided because of the complex landslide formation and failure mechanism. To retrieve the precursory signal of this landslide, we recovered pre-event deformation with multi-sensor synthetic aperture radar (SAR) imagery. First, we delineated the boundary and source area of the Pusa landslide based on the coherence and SAR intensity maps. Second, we detected the line-of-sight (LOS) deformation rate and time series before the Pusa landslide with ALOS/PALSAR-2 and Sentinel-1A/B SAR imagery data, where we found that the onset of the deformation is four months before landslide event. Finally, we conceptualized the failure mechanism of the Pusa landslide as the joint effects of rainfall and mining activity. This research provides new insights into the failure mechanism and early warning of rock avalanches.
Highlights
On 28 August 2017, the long-runout collapse initiated by the ridge-top rockslide in Pusa Village, Zhangjiawan Town, Guizhou Province, China, buried residential areas and caused 26 deaths with 9 missing [1]
As Pusa village is usually covered by dense vegetation, interferometric synthetic aperture radar (InSAR) coherence often gets lost in summer for both C-band and L-band Synthetic aperture radar (SAR) images
The Pusa landslide was fully analyzed with SAR imagery in terms of the boundary and source area delineation, pre-event deformation monitoring, and triggering factors’ explanation
Summary
On 28 August 2017, the long-runout collapse initiated by the ridge-top rockslide in Pusa Village, Zhangjiawan Town, Guizhou Province, China, buried residential areas and caused 26 deaths with 9 missing [1]. This catastrophic disaster is a typical rock avalanche caused by combined effects of natural and anthropogenic factors in the Yunnan–Guizhou Plateau and its surrounding areas, China, which is the largest karst mountain area in China, and even in the world, occupying around 6.2 × 105 km2 [2]. Synthetic aperture radar (SAR) intensity and coherence maps have been widely used to study the landslide disasters owing to the area being free from clouds. Dai et al [7] combined interferograms and their corresponding coherence maps to identify the source region and boundary of the landslide
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