Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the key methods to investigate, with centimeters to millimeters accuracy, the Earth surface displacements, as those occurred during natural and man-made hazards.Nowadays, with the increasing of SAR data availability provided by Sentinel-1 (S1) constellation of Copernicus European Program, the radar Earth Observation (EO) scenario is moving from the historical analysis to operational functionalities. Indeed, the S1 mission, by using the Terrain Observation by Progressive Scans (TOPS) technique, has been designed with the specific aim of natural hazards monitoring via SAR Interferometry guaranteeing a very large coverage of the illuminated scene (250km of swath). These characteristics sum up with the free & open access data policy, the global scale acquisition plan and the high system reliability thus providing a set of peculiarities that make S1 a game changer in the context of operational EO scenario.By taking benefit of the S1 characteristics, an unsupervised and cloud-based tool for the automatic generation of co-seismic ground displacement maps has been recently proposed. The tool is triggered by the significant (i.e. bigger than a defined magnitude) seismic events reported in the online catalogues of the United States Geological Survey (USGS) and the National Institute of Geophysics and Volcanology of Italy (INGV). The system permits to generate not only the co-seismic displacement maps but also the pre- and post- seismic ones, up to 30 days after the monitored event.Although it was conceived to generate displacement maps relevant to the upcoming earthquakes, as an operational service for the Civil Protection departments, the implemented tool has also been applied to the study of historical events imaged by the S1 data. This allowed us to generate a global data-base of DInSAR-based co-seismic displacement maps.Accordingly, the implementation of such data-base will be presented, with particular emphasis on the exploited computing infrastructure solutions (namely the AWS Cloud Computing environment), the used algorithmic strategies and the achieved interferometric results.Moreover, the whole data-base of DInSAR products will be made available through the European Plate Observing System (EPOS) Research Infrastructure, thus making them freely and openly accessible to the European and international solid Earth community.The implemented global data-base will be helpful for investigating the dynamics of surface deformation in the seismic zones around the Earth. Indeed, it will contribute to the study of global tectonic earthquake activity through the integration of DInSAR information with other geophysical parameters.This work has been partially supported by the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement, the EPOS-IP and EPOS-SP projects of the European Union Horizon 2020 R&I program (grant agreement 676564 and 871121) and the I-AMICA (PONa3_00363) project.
Global data-base of co-seismic interferograms generated via unsupervised Sentinel-1 DInSAR processing
Bonano Manuela;De Luca Claudio;De Novellis Vincenzo;Lanari Riccardo;Manunta Michele;Manzo Mariarosaria;Onorato Giovanni;Valerio Emanuela;Zinno Ivana;Casu Francesco
2020
Abstract
Differential Synthetic Aperture Radar Interferometry (DInSAR) is one of the key methods to investigate, with centimeters to millimeters accuracy, the Earth surface displacements, as those occurred during natural and man-made hazards.Nowadays, with the increasing of SAR data availability provided by Sentinel-1 (S1) constellation of Copernicus European Program, the radar Earth Observation (EO) scenario is moving from the historical analysis to operational functionalities. Indeed, the S1 mission, by using the Terrain Observation by Progressive Scans (TOPS) technique, has been designed with the specific aim of natural hazards monitoring via SAR Interferometry guaranteeing a very large coverage of the illuminated scene (250km of swath). These characteristics sum up with the free & open access data policy, the global scale acquisition plan and the high system reliability thus providing a set of peculiarities that make S1 a game changer in the context of operational EO scenario.By taking benefit of the S1 characteristics, an unsupervised and cloud-based tool for the automatic generation of co-seismic ground displacement maps has been recently proposed. The tool is triggered by the significant (i.e. bigger than a defined magnitude) seismic events reported in the online catalogues of the United States Geological Survey (USGS) and the National Institute of Geophysics and Volcanology of Italy (INGV). The system permits to generate not only the co-seismic displacement maps but also the pre- and post- seismic ones, up to 30 days after the monitored event.Although it was conceived to generate displacement maps relevant to the upcoming earthquakes, as an operational service for the Civil Protection departments, the implemented tool has also been applied to the study of historical events imaged by the S1 data. This allowed us to generate a global data-base of DInSAR-based co-seismic displacement maps.Accordingly, the implementation of such data-base will be presented, with particular emphasis on the exploited computing infrastructure solutions (namely the AWS Cloud Computing environment), the used algorithmic strategies and the achieved interferometric results.Moreover, the whole data-base of DInSAR products will be made available through the European Plate Observing System (EPOS) Research Infrastructure, thus making them freely and openly accessible to the European and international solid Earth community.The implemented global data-base will be helpful for investigating the dynamics of surface deformation in the seismic zones around the Earth. Indeed, it will contribute to the study of global tectonic earthquake activity through the integration of DInSAR information with other geophysical parameters.This work has been partially supported by the 2019-2021 IREA-CNR and Italian Civil Protection Department agreement, the EPOS-IP and EPOS-SP projects of the European Union Horizon 2020 R&I program (grant agreement 676564 and 871121) and the I-AMICA (PONa3_00363) project.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.