Landslide-Induced Damage Probability Estimation Coupling InSAR and Field Survey Data by Fragility Curves

Por favor, use este identificador para citar o enlazar este ítem: http://hdl.handle.net/10045/93392
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Campo DCValorIdioma
dc.contributorIngeniería del Terreno y sus Estructuras (InTerEs)es_ES
dc.contributor.authorDel Soldato, Matteo-
dc.contributor.authorSolari, Lorenzo-
dc.contributor.authorPoggi, Francesco-
dc.contributor.authorRaspini, Federico-
dc.contributor.authorTomás, Roberto-
dc.contributor.authorFanti, Riccardo-
dc.contributor.authorCasagli, Nicola-
dc.contributor.otherUniversidad de Alicante. Departamento de Ingeniería Civiles_ES
dc.date.accessioned2019-06-26T06:48:39Z-
dc.date.available2019-06-26T06:48:39Z-
dc.date.issued2019-06-22-
dc.identifier.citationDel Soldato M, Solari L, Poggi F, Raspini F, Tomás R, Fanti R, Casagli N. Landslide-Induced Damage Probability Estimation Coupling InSAR and Field Survey Data by Fragility Curves. Remote Sensing. 2019; 11(12):1486. doi:10.3390/rs11121486es_ES
dc.identifier.issn2072-4292-
dc.identifier.urihttp://hdl.handle.net/10045/93392-
dc.description.abstractLandslides are considered to be one of the main natural geohazards causing relevant economic damages and social effects worldwide. Italy is one of the countries worldwide most affected by landslides; in the Region of Tuscany alone, more than 100,000 phenomena are known and mapped. The possibility to recognize, investigate, and monitor these phenomena play a key role to avoid further occurrences and consequences. The number of applications of Advanced Differential Interferometric Synthetic Aperture Radar (A-DInSAR) analysis for landslides monitoring and mapping greatly increased in the last decades thanks to the technological advances and the development of advanced processing algorithms. In this work, landslide-induced damage on structures recognized and classified by field survey and velocity of displacement re-projected along the steepest slope were combined in order to extract fragility curves for the hamlets of Patigno and Coloretta, in the Zeri municipality (Tuscany, northern Italy). Images using ERS1/2, ENVISAT, COSMO-SkyMed (CSK) and Sentinel-1 SAR (Synthetic Aperture Radar) were employed to investigate an approximate 25 years of deformation affecting both hamlets. Three field surveys were conducted for recognizing, identifying, and classifying the landslide-induced damage on structures and infrastructures. At the end, the damage probability maps were designed by means of the use of the fragility curves between Sentinel-1 velocities and recorded levels of damage. The results were conceived to be useful for the local authorities and civil protection authorities to improve the land managing and, more generally, for planning mitigation strategies.es_ES
dc.description.sponsorshipThis work has been carried out within the project founded and supported by the Regional government of Tuscany, under the agreement “Monitoring ground deformation in the Tuscany Region with satellite radar data”. Roberto Tomás was supported by the Spanish Ministry of Economy, Industry and Competitiveness (MINECO), the State Agency of Research (AEI) and European Funds for Regional Development (FEDER), under projects TEC2017-85244-C2-1-P and PRX17/00439.es_ES
dc.languageenges_ES
dc.publisherMDPIes_ES
dc.rights© 2019 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-DInSARes_ES
dc.subjectLandslidees_ES
dc.subjectFragility curveses_ES
dc.subjectSAR dataes_ES
dc.subjectSentinel-1es_ES
dc.subjectDamagees_ES
dc.subjectTuscanyes_ES
dc.subject.otherIngeniería del Terrenoes_ES
dc.titleLandslide-Induced Damage Probability Estimation Coupling InSAR and Field Survey Data by Fragility Curveses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.peerreviewedsies_ES
dc.identifier.doi10.3390/rs11121486-
dc.relation.publisherversionhttps://doi.org/10.3390/rs11121486es_ES
dc.identifier.cvIDA9875888-
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
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