Landslides caught on seismic networks and satellite radars

<p>We present a procedure to detect landslide events by analyzing in-sequence data acquired from regional broadband seismic networks and spaceborne radar imagery. The combined used of these techniques is meant to exploit their complementary elements and mitigate their limitations when used sin...

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Main Authors: A. Manconi, A. C. Mondini
Format: Article
Language:English
Published: Copernicus Publications 2022-05-01
Series:Natural Hazards and Earth System Sciences
Online Access:https://nhess.copernicus.org/articles/22/1655/2022/nhess-22-1655-2022.pdf
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author A. Manconi
A. Manconi
A. C. Mondini
author_facet A. Manconi
A. Manconi
A. C. Mondini
author_sort A. Manconi
collection DOAJ
description <p>We present a procedure to detect landslide events by analyzing in-sequence data acquired from regional broadband seismic networks and spaceborne radar imagery. The combined used of these techniques is meant to exploit their complementary elements and mitigate their limitations when used singularly. To test the method, we consider a series of six slope failures associated to the Piz Cengalo rock avalanche that recently occurred in the Swiss Alps, a region where we can benefit from high spatial density and quality of seismic data, as well as from the high spatial and temporal resolution of the European Space Agency (ESA) Copernicus Sentinel-1 radar satellites. The operational implementation of the proposed approach, in combination with the future increase in availability of seismic and satellite data, can offer a new and efficient solution to build and/or expand landslide catalogues based on quantitative measurements and, thus, help in hazard assessments and the definition of early warning systems at regional scales.</p>
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spelling doaj.art-f11f8a23ec8e48b990b7dac43a8d04bb2022-12-22T02:11:10ZengCopernicus PublicationsNatural Hazards and Earth System Sciences1561-86331684-99812022-05-01221655166410.5194/nhess-22-1655-2022Landslides caught on seismic networks and satellite radarsA. Manconi0A. Manconi1A. C. Mondini2Department of Earth Sciences, Engineering Geology, ETH Zurich, Zurich, Switzerlandnow at: CERC, WSL Institute for Snow and Avalanche Research SLF, Davos, SwitzerlandNational Research Council, Istituto di Ricerca per la Protezione Idrogeologica, Perugia, Italy<p>We present a procedure to detect landslide events by analyzing in-sequence data acquired from regional broadband seismic networks and spaceborne radar imagery. The combined used of these techniques is meant to exploit their complementary elements and mitigate their limitations when used singularly. To test the method, we consider a series of six slope failures associated to the Piz Cengalo rock avalanche that recently occurred in the Swiss Alps, a region where we can benefit from high spatial density and quality of seismic data, as well as from the high spatial and temporal resolution of the European Space Agency (ESA) Copernicus Sentinel-1 radar satellites. The operational implementation of the proposed approach, in combination with the future increase in availability of seismic and satellite data, can offer a new and efficient solution to build and/or expand landslide catalogues based on quantitative measurements and, thus, help in hazard assessments and the definition of early warning systems at regional scales.</p>https://nhess.copernicus.org/articles/22/1655/2022/nhess-22-1655-2022.pdf
spellingShingle A. Manconi
A. Manconi
A. C. Mondini
Landslides caught on seismic networks and satellite radars
Natural Hazards and Earth System Sciences
title Landslides caught on seismic networks and satellite radars
title_full Landslides caught on seismic networks and satellite radars
title_fullStr Landslides caught on seismic networks and satellite radars
title_full_unstemmed Landslides caught on seismic networks and satellite radars
title_short Landslides caught on seismic networks and satellite radars
title_sort landslides caught on seismic networks and satellite radars
url https://nhess.copernicus.org/articles/22/1655/2022/nhess-22-1655-2022.pdf
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AT acmondini landslidescaughtonseismicnetworksandsatelliteradars