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Identification and monitoring landslides in Longitudinal Range-Gorge Region with InSAR fusion integrated visibility analysis

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Abstract

In high mountain canyon regions, SAR geometric distortion in imaging side may have an inevitable impact on InSAR deformation information, so the effective deformation information acquisition is critical for landslide identification and deformation mechanisms analysis. The landslide deformation around the reservoir of Gushui Hydropower Station located in upstream of the Lancang River has been focused on in the study. Using SAR satellite parameters and topographic information, the visibility analysis of deformation in radar line-of-sight (LOS) direction has been carried out, and a method to obtain LOS effective deformation information based on the visibility analysis has been proposed. The small baseline subsets (SBAS) technique is used to process the L-band and C-band SAR data, and the area affected by the geometric distortion in the InSAR result is masked to obtain the deformation information of the effective deformation region. The landslide identification analysis in the reservoir area has been carried out based on the effective deformation information in LOS direction. Thirteen landslides have been identified, and ten of them are new ones. A new large unstable area (New Zhenggang landslide) has been found near the Zhenggang landslide. The geological survey and displacement time series of the Zhenggang landslide reveals that it is in pull-type landslide mode, that is, due to the local instability of the leading edge of a landslide, the support of the trailing edge may be weakened, which may result in the landslide gradually developing backwards and upwards, and finally becoming a large landslide. The impact of peak rainfall and cumulative rainfall during the rainy season on landslide deformation has been verified in this paper. It indicates that the cumulative precipitation is the dominant factor causing the deformation of the landslide, and it shows that the landslide begins the deformation acceleration period about 12 days after the peak precipitation. The results have shown that the proposed visibility analysis method for extracting the effective deformation information of InSAR results can significantly improve landslide identification and analysis in complex terrain.

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Acknowledgments

The PALSAR dataset was provided by the Japan Aerospace Exploration Agency (JAXA). The Sentinel-1 datasets were freely provided by the European Space Agency (ESA) through the Sentinels Scientific Data Hub. The one-arc-second SRTM DEM was freely downloaded from the website http://e4ftl01.cr.usgs.gov/MODV6_Dal_D/SRTM/SRTMGL1.003/2000.02.11/. Precipitation data was freely downloaded from the website https://data.mma.cn/. We thank Prof. Liming Jiang of the Chinese Academy of Sciences for his kind helps in revising our manuscript. The authors would like to express heartfelt thanks to the editors and three anonymous reviewers for their valuable suggestions.

Funding

This study was jointly supported by the Second Tibetan Plateau Scientific Expedition and Research (STEP) Program (Grant No. 2019QZKK0905), the Key Research Program of the Chinese Academy of Sciences (Grant No. KFZD-SW-428 and QYZDB-SSW-DQC027), the Open Foundation of State Key Laboratory of Geohazard Prevention and Geoenvironment Protection (Grant No. SKLGP2020K012), and the National Natural Science Foundation of China (Grant No. 41161062 and 41861051).

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Authors and Affiliations

  1. College of Land and Resources Engineering, Kunming University of Science and Technology, Kunming, 650093, China

    Rui Guo, Sumin LI, Ya’nan Chen & Xiangxin Li

  2. State Key Laboratory of Geodesy and Earth’s Dynamics, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China

    Rui Guo

  3. University of Chinese Academy of Sciences, Beijing, China

    Rui Guo

  4. Surveying and Mapping Geo-Informatics Technology Research Center on Plateau Mountains of Yunnan Higher Education, Kunming, 650093, China

    Sumin LI, Xiangxin Li & Liwei Yuan

  5. Key Laboratory of Intelligent Mine Geospatial Information Integration and Innovation, China Nonferrous Metals Industry Association, 650093, Kunming, China

    Sumin LI, Xiangxin Li & Liwei Yuan

  6. College of Public Safety and Emergency Management, Kunming University of Science and Technology, 650093, Kunming, China

    Liwei Yuan

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  1. Rui Guo
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Contributions

R.G and S M.L conceived the manuscript; R.G interpreted the results and drafted the manuscript; Y N.C and R.G conducted experiments and obtained the results; L W.Y and R.G conducted the field surveys; R.G and S M.L contributed to the discussion of the results. X X.L assisted in language editing. All authors reviewed and approved the manuscript.

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Correspondence to Sumin LI.

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Guo, R., LI, S., Chen, Y. et al. Identification and monitoring landslides in Longitudinal Range-Gorge Region with InSAR fusion integrated visibility analysis. Landslides 18, 551–568 (2021). https://doi.org/10.1007/s10346-020-01475-7

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  • DOI: https://doi.org/10.1007/s10346-020-01475-7

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