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Bulletin of Engineering Geology and the Environment

Erschienen in:

01.06.2024 | Original Paper

Landslide identification and deformation monitoring analysis in Xining City based on the time series InSAR of Sentinel-1A with ascending and descending orbits

verfasst von: Li He, Xiantan Wu, Zhengwei He, Dongjian Xue, Wenqian Bai, Guichuan Kang, Xin Chen, Yuxiang Zhang

Erschienen in: Bulletin of Engineering Geology and the Environment | Ausgabe 6/2024

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Abstract

Landslide hazards are a common occurrence on the Loess Plateau of China, and the use of time-series interferometric synthetic aperture radar (InSAR) can effectively identify potential landslides and monitor their deformation, thus allowing to mitigate the risks associated with such hazards. In this study, we used Sentinel-1A ascending and descending orbit images to identify 74 significantly deformed areas in Xining city, of which 35 were confirmed as active landslides, using two time-series InSAR algorithms: small baseline subset (SBAS) and permanent scatterer (PS). Compared to PS, SBAS yielded a higher point density and more continuous deformation rate results in space. Our correlation analysis indicated a high correlation between the deformation rate results obtained from SBAS and PS algorithms, demonstrating their high consistency. Furthermore, by comparing the monitoring results of SBAS and PS algorithms with the GNSS monitoring data, we observed that the cumulative landslide deformation detected by PS algorithms was more consistent with the GNSS monitoring data. Finally, we analyzed the relationship between landslide deformation and the main influencing factors, which showed that the combined effect of precipitation, fault, slope, and engineered rock formations was the primary cause of landslide activity in the region during the study period. In conclusion, time-series InSAR algorithm is a valuable tool for identifying and monitoring loess landslides, and provides a scientific basis for regional disaster prevention and control.

Vorheriger Artikel Damage constitutive model for soft rocks and its experimental verification on silty mudstone considering cyclic rock‒water interactions

Nächster Artikel Landslides triggered by the 30th June 2012 Ms6.6 Hejing earthquake, Xinjiang province, China

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Titel: Landslide identification and deformation monitoring analysis in Xining City based on the time series InSAR of Sentinel-1A with ascending and descending orbits
verfasst von: Li He
Xiantan Wu
Zhengwei He
Dongjian Xue
Wenqian Bai
Guichuan Kang
Xin Chen
Yuxiang Zhang
Publikationsdatum: 01.06.2024
Verlag: Springer Berlin Heidelberg
Erschienen in: Bulletin of Engineering Geology and the Environment / Ausgabe 6/2024
Print ISSN: 1435-9529
Elektronische ISSN: 1435-9537
DOI: https://doi.org/10.1007/s10064-024-03708-8

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