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.

Landslide mapping and monitoring with satellite interferometry / Raspini F.; Intrieri E.; Festa D.; Casagli N.. - STAMPA. - (2021), pp. 149-154. [10.1007/978-3-030-60311-3_16]

Landslide mapping and monitoring with satellite interferometry

Raspini F.;Intrieri E.;Festa D.;Casagli N.
2021

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.
2021
978-3-030-60310-6
978-3-030-60311-3
Understanding and Reducing Landslide Disaster Risk - Vol.3
149
154
Raspini F.; Intrieri E.; Festa D.; Casagli N.
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Utilizza questo identificatore per citare o creare un link a questa risorsa: https://hdl.handle.net/2158/1235097
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