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Título: | InSAR-Based Mapping to Support Decision-Making after an Earthquake |
Autor: | Béjar Pizarro, Marta; Álvarez Gómez, José Antonio; Staller, Alejandra; Luna, Marco P.; Pérez López, Raúl; Montserrat, Oriol; Chunga, Kervin; Lima Abásolo, Aracely; Galve, Jorge Pedro; Martínez-Díaz, J. J. CSIC ORCID ; Mateos Ruiz, Rosa María; Herrera García, Gerardo | Palabras clave: | InSAR Sentinel-1 GPS Ecuador earthquake stress changes Active faults volcanoes decision-making |
Fecha de publicación: | 7-jun-2018 | Editor: | Multidisciplinary Digital Publishing Institute | Citación: | Remote sensing (2018), vol.10, n.899, 24 p. | Resumen: | It has long been recognized that earthquakes change the stress in the upper crust around the fault rupture and can influence the behaviour of neighbouring faults and volcanoes. Rapid estimates of these stress changes can provide the authorities managing the post-disaster situation with valuable data to identify and monitor potential threads and to update the estimates of seismic and volcanic hazard in a region. Here we propose a methodology to evaluate the potential influence of an earthquake on nearby faults and volcanoes and create easy-to-understand maps for decision-making support after large earthquakes. We apply this methodology to the Mw 7.8, 2016 Ecuador earthquake. Using Sentinel-1 Interferometric Synthetic Aperture Radar (InSAR) and continuous GPS data, we measure the coseismic ground deformation and estimate the distribution of slip over the fault rupture. We also build an alternative source model using the Global Centroid Moment Tensor (CMT) solution. Then we use these models to evaluate changes of static stress on the surrounding faults and volcanoes and produce maps of potentially activated faults and volcanoes. We found, in general, good agreement between our maps and the seismic and volcanic events that occurred after the Pedernales earthquake. We discuss the potential and limitations of the methodology. | Versión del editor: | https://www.mdpi.com/2072-4292/10/6/899 | URI: | http://hdl.handle.net/10261/277212 | DOI: | http://dx.doi.org/10.3390/rs10060899 | ISSN: | 2072-4292 |
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insar_based_mapping_2018.pdf | Artículo | 8,92 MB | Adobe PDF | Visualizar/Abrir |
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