Application of multi-source remote sensing technologies in identification and evolution mechanism analysis of creep landslides: a case study of Shibatai landslide in Wenchuan earthquake area
Slow-moving landslides pose significant long-term hazards in seismically active mountainous regions. However, their subtle deformation patterns and complex internal structures present challenges for accurate identification and monitoring using conventional methods. This study integrates remote sensi...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Frontiers Media S.A.
2025-02-01
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| Series: | Frontiers in Earth Science |
| Subjects: | |
| Online Access: | https://www.frontiersin.org/articles/10.3389/feart.2025.1498028/full |
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| Summary: | Slow-moving landslides pose significant long-term hazards in seismically active mountainous regions. However, their subtle deformation patterns and complex internal structures present challenges for accurate identification and monitoring using conventional methods. This study integrates remote sensing technologies, including InSAR, DIC, LiDAR, and UAV photogrammetry, to comprehensively analyze the Shibatai creep landslide in the Wenchuan earthquake-affected area. Results reveal that the landslide exhibits a four-stage evolution process, from initial gravity-induced creep to earthquake disturbance, rainfall influence, and multi-level sliding formation. The study identifies six secondary sliding bodies within the landslide, with the most intense deformation occurring at their boundaries. Notably, DIC and UAV technologies demonstrated superior performance in detecting significant deformation features, aligning closely with field observations. The research proposes a multi-scale, multi-technology combination strategy for landslide investigation, emphasizing the complementary nature of different remote sensing techniques. Furthermore, the study highlights the importance of focusing on main deformation areas, particularly at the boundaries of secondary blocks, for efficient field verification and monitoring. These findings provide valuable insights for refining landslide identification processes, optimizing monitoring strategies, and enhancing risk assessment in post-earthquake environments. |
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| ISSN: | 2296-6463 |