Abstract
Kaiyang landslides in southwest China have brought heavy damages to lives and properties due to years of underground phosphate mining. However, affected by karst geomorphology including dense vegetation, complex topography, few in situ measurements were conducted to investigate the potentially unstable slopes and derive the kinematic process. In this study, 19 L-band ALOS/PALSAR-2 images are selected, and both phase-stacking and distributed scatterers (DS) InSAR methods are employed to identify the unstable slopes and to derive the spatiotemporal evolution of Kaiyang landslides. At first, we calculate the annual deformation rate and investigate the unstable slopes in a wide range of Kaiyang County through the phase-stacking method. Then, the typical landslides suffering apparent deformation are taken as the region of interest (ROI), and the effects of spatial and temporal decorrelation are suppressed by the process of phase enhancement and point-target optimization. The influence of trigger factors on the Kaiyang landslides is assessed subsequently by the logistic model and precipitation data. Finally, the previous and current failure processes of Kaiyang landslides are analyzed according to the deformation process. The results reveal that the continuous underground phosphate mining leads to the ongoing expansion of the Kaiyang landslides. It can not only reactivate the previous landslide, but also accelerate the deformation of the slope under the action of strong precipitation. Furthermore, the technical route presented in this research can provide valuable guidance for the monitoring and mitigation of mining-induced landslides in the karst mountain areas.
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Acknowledgements
We would like to thank Japan Aerospace Exploration Agency (JAXA) for providing the ALOS/PALSAR-2 datasets. And the 30 m shuttle radar topography mission (SRTM) digital elevation model (DEM) is downloaded from the website https://e4ftl01.cr.usgs.gov/MEASURES/. The geological map is acquired from the National Geological Data Museum of China (http://www.ngac.org.cn/ and re-digitization), and the optical image of Map-World is downloaded from the National Platform for Common Geospatial Information Services of China (https://www.tianditu.gov.cn/).
Funding
This work is funded by the Natural Science Foundation of China (Grants Nos. 41929001 and 41874005). This study also was supported by Chang'an University High Performance Computing Platform.
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Chen, H., Zhao, C., Li, B. et al. Monitoring spatiotemporal evolution of Kaiyang landslides induced by phosphate mining using distributed scatterers InSAR technique. Landslides 20, 695–706 (2023). https://doi.org/10.1007/s10346-022-01986-5
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DOI: https://doi.org/10.1007/s10346-022-01986-5