Long-Term Monitoring of Landslide Activity in a Debris Flow Gully Using SBAS-InSAR: A Case Study of Shawan Gully, China
Shawan Gully historically experienced recurrent debris flow events, resulting in significant losses of life and property. The Nuole and Huajiaoshu landslides are two major high-elevation landslides in Shawan Gully, serving as primary sources of debris flow material. To monitor landslides movements,...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2025-04-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/9/1580 |
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| Summary: | Shawan Gully historically experienced recurrent debris flow events, resulting in significant losses of life and property. The Nuole and Huajiaoshu landslides are two major high-elevation landslides in Shawan Gully, serving as primary sources of debris flow material. To monitor landslides movements, this study used interferometric synthetic aperture radar (InSAR) and Sentinel-1 SAR imagery acquired between 2014 and 2023 to analyze surface deformation in Shawan Gully. Prior to InSAR processing, we assessed the InSAR measurement suitability of the involved SAR images in detail based on geometric distortion and monitoring sensitivity. Compared to conventional SBAS-InSAR results without preprocessing, the suitability-refined datasets show improvements in interferometric phase quality (1.55 rad to 1.41 rad) and estimation accuracy (1.45 mm to 1.18 mm). By processing ascending, descending, and cross-track Sentinel-1 SAR images, we obtained multi-directional surface displacements in Shawan Gully. The results reveal significant deformation in the NL1 region of Nuole landslide, while the northern scarp and the foot of the slope exhibited different movement characteristics, indicating spatially variable deformation mechanisms. The study also revealed that the Nuole landslide exhibits a high sensitivity to rainfall-induced instability, with rainfall significantly changing its original movement trend. |
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| ISSN: | 2072-4292 |