Abstract
Interferometric Synthetic Aperture Radar (InSAR) has been increasingly used in landslide detection over wide areas. However, atmospheric delays, phase unwrapping errors, and noise, which behave like deformation signals in InSAR deformation results, pose a challenge for semi-automatic and automatic landslide detection. C-index can assistant in landslide interpretation by assessing the rationality of InSAR deformation and filtering out non-real landslide deformation signals. Yet, few studies have analyzed its applicability in identifying landslide from InSAR results. In this study, we develop a method that uses C-index to assist in landslide detection using InSAR. We validate our method in a selected region of the Jinsha River basin, China. We first using multi-temporal InSAR (MT-InSAR) to obtain the deformation rate of the study area. Sixty-nine and 47 suspicious slope deformation areas are extracted from the ascending and descending deformation results, respectively. Next, C-index is used to automatically exclude 28 and 12 false deformation areas from the ascending and descending InSAR results, respectively. Remarkably, all the excluded false deformation areas do not correspond to landslides, suggesting the reliability of the proposed method. Finally, by visually interpreting the optical images of the remaining deformation results, we successfully detect 54 landslides. Among these, 9 landslides can be detected by both the ascending and descending Sentinel-1 data, and 15 landslides are located on the riverbanks, posing a potential risk of river blockage in the event of failure. The presented landslide detection method effectively filters out false deformation areas, ultimately enhancing the efficiency and accuracy of landslide detection over wide areas using InSAR.
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Data are available from the authors upon reasonable request.
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Acknowledgements
This research was supported by the Projects of the Ministry of Natural Resources of the People's Republic of China (Grant No. 121106000000180039-2201), the China Geological Survey Projects (Grant No. DD20211364), the National Natural Science Foundation of China (Grant No. 42174039) and the Natural Science Foundation of Hunan Province (Grant No. 2021JJ30807). This research was also supported in part by the Scientific Research Innovation Project for Graduate Students of Hunan Province (Grant No. CX20220170) and the Fundamental Research Funds for the Central Universities of Central South University (Grant No. 2022ZZTS0082). We sincerely thank the editors and reviewers for their insightful and constructive comments and suggestions, which greatly improved this study. We acknowledge the GMT open-source software. We would like to thank the European Space Agency (ESA) for providing the Sentinel-1 SAR images.
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Xiong, Z., Zhang, M., Ma, J. et al. InSAR-based landslide detection method with the assistance of C-index. Landslides 20, 2709–2723 (2023). https://doi.org/10.1007/s10346-023-02120-9
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DOI: https://doi.org/10.1007/s10346-023-02120-9