Exploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidence

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dc.contributorIngeniería del Terreno y sus Estructuras (InTerEs)es_ES
dc.contributor.authorBonì, Roberta-
dc.contributor.authorMeisina, Claudia-
dc.contributor.authorCigna, Francesca-
dc.contributor.authorHerrera García, Gerardo-
dc.contributor.authorNotti, Davide-
dc.contributor.authorBricker, Stephanie-
dc.contributor.authorMcCormack, Harry-
dc.contributor.authorTomás, Roberto-
dc.contributor.authorBéjar Pizarro, Marta-
dc.contributor.authorMulas de la Peña, Joaquín-
dc.contributor.authorEzquerro Martín, Pablo-
dc.contributor.otherUniversidad de Alicante. Departamento de Ingeniería Civiles_ES
dc.identifier.citationBonì R, Meisina C, Cigna F, Herrera G, Notti D, Bricker S, McCormack H, Tomás R, Béjar-Pizarro M, Mulas J, Ezquerro P. Exploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidence. Geosciences. 2017; 7(2):25. doi:10.3390/geosciences7020025es_ES
dc.description.abstractIn the last two decades, advanced differential interferometric synthetic aperture radar (A-DInSAR) techniques have experienced significant developments, which are mainly related to (i) the progress of satellite SAR data acquired by new missions, such as COSMO-SkyMed and ESA’s Sentinel-1 constellations; and (ii) the development of novel processing algorithms. The improvements in A-DInSAR ground deformation time series need appropriate methodologies to analyse extremely large datasets which consist of huge amounts of measuring points and associated deformation histories with high temporal resolution. This work demonstrates A-DInSAR time series exploitation as valuable tool to support different problems in engineering geology such as detection, characterization and modelling of land subsidence mechanisms. The capabilities and suitability of A-DInSAR time series from an end-user point of view are presented and discussed through the analysis carried out for three test sites in Europe: the Oltrepo Pavese (Po Plain in Italy), the Alto Guadalentín (Spain) and the London Basin (United Kingdom). Principal component analysis has been performed for the datasets available for the three case histories, in order to extract the great potential contained in the A-DInSAR time series.es_ES
dc.description.sponsorshipPart of this work was supported by the Spanish Ministry of Economy and Competitiveness and EU FEDER funds under projects TIN2014-55413- C2-2-P and ESP2013-47780-C2-2-R.es_ES
dc.rights© 2017 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).es_ES
dc.subjectA-DInSAR time serieses_ES
dc.subjectLand subsidencees_ES
dc.subjectGroundwater level changees_ES
dc.subjectPrincipal component analysis (PCA)es_ES
dc.subject.otherIngeniería del Terrenoes_ES
dc.titleExploitation of Satellite A-DInSAR Time Series for Detection, Characterization and Modelling of Land Subsidencees_ES
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