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Article

Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP)

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Departamento de Geodinámica, Universidad de Granada, Avda. del Hospicio, s/n, 18010 Granada, Spain
2
Instituto Andaluz de Geofísica (IAG), Universidad de Granada, Calle Profesor Clavera, 12, 18071 Granada, Spain
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Instituto Andaluz de Ciencias de la Tierra (IACT), CISC-UGR, Av. de las Palmeras, 4, 18100 Armilla, Spain
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GIM n.v., Philipssite 5 Bus 27, 3001 Leuven, Belgium
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Istituto per il rilevamento elettromagnetico dell’ambiente, Consiglio Nazionale delle Ricerche, Via Diocleziano, 328, 80124 Napoli, Italy
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Geohazards InSAR laboratory and Modeling group (InSARlab), Geoscience research department, Geological Survey of Spain (IGME), Alenza 1, 28003 Madrid, Spain
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National Research Council of Italy, Research Institute for Geo-Hydrological Protection (CNR-IRPI), Strada delle Cacce, 73, 10135 Torino, Italy
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Centre Tecnològic y Telecomunicacions de Catalunya, Parc Mediterrani de la Tecnologia, Avinguda Carl Friedrich Gauss, 7, 08860 Castelldefels, Spain
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European Space Agency, Science, Applications and Future Technologies Department, Directorate of Earth Observation Programmes, ESRIN, Via Galileo Galilei snc, I-00044 Frascati, Italy
*
Author to whom correspondence should be addressed.
Remote Sens. 2017, 9(12), 1291; https://0-doi-org.brum.beds.ac.uk/10.3390/rs9121291
Received: 27 September 2017 / Revised: 28 November 2017 / Accepted: 7 December 2017 / Published: 11 December 2017
(This article belongs to the Special Issue Radar Interferometry for Geohazards)
The analysis of remote sensing data to assess geohazards is being improved by web-based platforms and collaborative projects, such as the Geohazard Exploitation Platform (GEP) of the European Space Agency (ESA). This paper presents the evaluation of a surface velocity map that is generated by this platform. The map was produced through an unsupervised Multi-temporal InSAR (MTI) analysis applying the Parallel-SBAS (P-SBAS) algorithm to 25 ENVISAT satellite images from the South of Spain that were acquired between 2003 and 2008. This analysis was carried out using a service implemented in the GEP called “SBAS InSAR”. Thanks to the map that was generated by the SBAS InSAR service, we identified processes not documented so far; provided new monitoring data in places affected by known ground instabilities; defined the area affected by these instabilities; and, studied a case where GEP could have been able to help in the forecast of a slope movement reactivation. This amply demonstrates the reliability and usefulness of the GEP, and shows how web-based platforms may enhance the capacity to identify, monitor, and assess hazards that are associated to geological processes. View Full-Text
Keywords: DInSAR; GEP; SBAS; landslides; human-induced subsidence; hazard identification DInSAR; GEP; SBAS; landslides; human-induced subsidence; hazard identification
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MDPI and ACS Style

Galve, J.P.; Pérez-Peña, J.V.; Azañón, J.M.; Closson, D.; Caló, F.; Reyes-Carmona, C.; Jabaloy, A.; Ruano, P.; Mateos, R.M.; Notti, D.; Herrera, G.; Béjar-Pizarro, M.; Monserrat, O.; Bally, P. Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP). Remote Sens. 2017, 9, 1291. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9121291

AMA Style

Galve JP, Pérez-Peña JV, Azañón JM, Closson D, Caló F, Reyes-Carmona C, Jabaloy A, Ruano P, Mateos RM, Notti D, Herrera G, Béjar-Pizarro M, Monserrat O, Bally P. Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP). Remote Sensing. 2017; 9(12):1291. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9121291

Chicago/Turabian Style

Galve, Jorge P., José V. Pérez-Peña, José M. Azañón, Damien Closson, Fabiana Caló, Cristina Reyes-Carmona, Antonio Jabaloy, Patricia Ruano, Rosa M. Mateos, Davide Notti, Gerardo Herrera, Marta Béjar-Pizarro, Oriol Monserrat, and Philippe Bally. 2017. "Evaluation of the SBAS InSAR Service of the European Space Agency’s Geohazard Exploitation Platform (GEP)" Remote Sensing 9, no. 12: 1291. https://0-doi-org.brum.beds.ac.uk/10.3390/rs9121291

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