Abstract
The potential of multi-interferometric approach applied to the Sentinel-1 acquisitions for the analysis of slope instabilities is presented and discussed through two different landslides of very different nature. In the first case, Sentinel-1 data, systematically acquired with short revisiting time and promptly processed allows for the quick identification of the acceleration suffered by the Carpineta landslide, a large, active earth slide in the Northern Apennines (Tuscany Region, Italy). In the second case, a post-event analyses of Sentinel-1 data permitted the identification of a clear precursory deformation signal for the Xinmo landslide (Mao County, Sichuan Province, China), a large rock avalanche occurred in the early morning of 24 June 2017. Results suggest that advances in satellite sensors, increase of computing capacity and refinement of data screening tools can contribute to the design of a new paradigm in satellite-based monitoring systems. Sentinel-1 data, systematically acquired over large areas with short revisiting time, could be used not only as a tool for mapping unstable areas, but also for landslide monitoring, at least for some typologies of sliding phenomena.
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Acknowledgements
The monitoring system presented in this paper has been founded and supported by the Regional government of Tuscany. The authors also acknowledge TRE ALTAMIRA for having processed the Sentinel-1 data for the Tuscany Region and for the Xinmo landslide.
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Raspini, F., Intrieri, E., Festa, D., Casagli, N. (2021). Landslide Mapping and Monitoring with Satellite Interferometry. In: Casagli, N., Tofani, V., Sassa, K., Bobrowsky, P.T., Takara, K. (eds) Understanding and Reducing Landslide Disaster Risk. WLF 2020. ICL Contribution to Landslide Disaster Risk Reduction. Springer, Cham. https://doi.org/10.1007/978-3-030-60311-3_16
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