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A global archive of coseismic DInSAR products obtained through unsupervised sentinel-1 data processing

Articolo
Data di Pubblicazione:
2020
Abstract:
We present an automatic and unsupervised tool for the systematic generation of Sentinel-1 (S1) differential synthetic aperture radar interferometry (DInSAR) coseismic products. In particular, the tool first retrieves the location, depth, and magnitude of every seismic event from interoperable online earthquake catalogs (e.g., the United States Geological Survey (USGS) and the Italian National Institute of Geophysics and Volcanology (INGV) and then, for significant (with respect to a set of selected thresholds) earthquakes, it automatically triggers the downloading of S1 data and their interferometric processing over the area affected by the earthquake. The automatic system we developed has also been implemented within a Cloud-Computing (CC) environment, specifically the Amazon Web Services, with the aim of creating a global database of DInSAR S1 coseismic products, which consist of displacement maps and the associated wrapped interferograms and spatial coherences. This information will progressively be made freely available through the European Plate Observing System (EPOS) Research Infrastructure, thus providing the scientific community with a large catalog of DInSAR data that can be helpful for investigating the dynamics of surface deformation in the seismic zones around the Earth. The developed tool can also support national and local authorities during seismic crises by quickly providing information on the surface deformation induced by earthquakes.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
[object Object; [object Object; [object Object; [object Object; [object Object
Elenco autori:
MONTERROSO TOBAR, MARIO FERNANDO; Lanari, Riccardo; Casu, Francesco; Manunta, Michele; Bonano, Manuela; Onorato, Giovanni; Zinno, Ivana; DE LUCA, Claudio
Autori di Ateneo:
BONANO MANUELA
CASU FRANCESCO
DE LUCA CLAUDIO
LANARI RICCARDO
MANUNTA MICHELE
ONORATO GIOVANNI
ZINNO IVANA
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/422806
Pubblicato in:
REMOTE SENSING (BASEL)
Journal
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