Characteristics and failure mechanisms of rear reservoir-induced landslide-a case study of Shuiyunshan landslide in Xinshao, China

Bulletin of Engineering Geology and the Environment, Год журнала: 2025, Номер 84(4)

Опубликована: Март 27, 2025

Язык: Английский

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Measuring hydrological alterations and landscape patterns for sustainable development through ecosystem connectivity in Hastinapur Wildlife Sanctuary, India

Journal of Environmental Sciences, Год журнала: 2025, Номер unknown

Опубликована: Март 1, 2025

Язык: Английский

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Integration of interpretable machine learning and MT-InSAR for dynamic enhancement of landslide susceptibility in the Three Gorges Reservoir Area

Journal of Rock Mechanics and Geotechnical Engineering, Год журнала: 2025, Номер unknown

Опубликована: Май 1, 2025

Язык: Английский

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Enhancing 4‐D Landslide Monitoring and Block Interaction Analysis With a Novel Kalman‐Filter‐Based InSAR Approach

Journal of Geophysical Research Earth Surface, Год журнала: 2024, Номер 129(11)

Опубликована: Окт. 31, 2024

Abstract In recent years, Synthetic Aperture Radar Interferometry (InSAR) has become widely utilized for slow‐moving landslide monitoring due to its high resolution, accuracy, and extensive coverage. By integrating data from various orbits/platforms sources, one‐dimensional (1‐D) line‐of‐sight (LOS) InSAR measurements can be explored infer three‐dimensional (3‐D) movements. However, inconsistencies in observation times among different orbits sources pose challenges accurately capturing dynamic 3‐D movements over time (referred as 4‐D). this study, we propose a novel method, termed KFI‐4D that incorporates spatiotemporal constraints into the traditional Kalman filter. This enhancement transforms underdetermined problem of 4‐D movement acquisition parameter estimation problem, enabling precise The method was evaluated using both synthetic sets real Hooskanaden landslide, demonstrating an improvement exceeding 50% root mean square errors (RMSEs) compared conventional methods. Additionally, high‐resolution characteristics InSAR‐derived allow analysis strain invariants, providing insights block interactions dynamics. Our findings reveal invariants effectively indicate distribution activity blocks slip surfaces well their response triggers. Notably, abnormal signals identified prior catastrophic event at suggest potential early warning landslides. future integration advanced satellites, such NISAR, ALOS4 PALSAR3, Sentinel‐1C, is expected further enhance method's capabilities, improving temporal resolution monitoring.

Язык: Английский

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Failure and reinforcement of reservoir landslides: Insights from centrifuge modeling and numerical modeling

Engineering Geology, Год журнала: 2024, Номер 343, С. 107806 - 107806

Опубликована: Ноя. 16, 2024

Язык: Английский

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