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dc.contributorEscuela de Ingenierias Industrial, Informática y Aeroespaciales_ES
dc.contributor.authorGarcía Gutiérrez, Adrián 
dc.contributor.authorGonzalo de Grado, Jesús 
dc.contributor.authorRubio Sierra, Carlos 
dc.contributor.authorCorvino, María Michela
dc.contributor.otherIngenieria Aeroespaciales_ES
dc.date2024-04-30
dc.date.accessioned2024-05-06T07:16:23Z
dc.date.available2024-05-06T07:16:23Z
dc.identifier.citationGarcía-Gutiérrez, A.; Gonzalo, J.; Rubio, C.; Corvino, M.M.. (2024). Estimating Landfill Landslide Probability Using SAR Satellite Products: A Novel Approach. Remote Sensing, 16(9):1618. https://doi.org/ 10.1016/j.aprim.2018.05.013es_ES
dc.identifier.issn2072-4292
dc.identifier.urihttps://hdl.handle.net/10612/20325
dc.description.abstract[EN] This article presents a methodology for evaluating the susceptibility of landfill areas to develop landslides by analyzing Synthetic Aperture Radar (SAR) satellite products. The deformation velocity of the landfills is computed through the Persistent Scatterer Method on SAR imagery. These data, combined with a deformation model based on the shallow water equations (SWE), form the foundation for a Monte Carlo experiment that extrapolates the current state of the landfill into the future. The results of this simulation are then employed to determine the probability of a landslide occurrence. In order to validate the methodology effectiveness, a case study is conducted on a landfill in Zaldibar, Spain, revealing its effectiveness in estimating the probability of landfill landslides. This innovative approach emerges as an asset in large landfill management, acting as a proactive tool for identifying high-risk sites and preventing potential landslides, ultimately safeguarding human life and the environment. By providing insights into landslide probabilities, this study enhances decision-making processes and facilitates the development of intervention strategies in the domain of landfill risk assessment and management.es_ES
dc.languageenges_ES
dc.publisherMDPIes_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internacional*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.subjectAeronáuticaes_ES
dc.subjectIngeniería aeroespaciales_ES
dc.subject.otherSARes_ES
dc.subject.otherLandslidees_ES
dc.subject.otherLandfilles_ES
dc.subject.otherMonitoringes_ES
dc.subject.otherSatellitees_ES
dc.titleEstimating Landfill Landslide Probability Using SAR Satellite Products: A Novel Approaches_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.identifier.doihttps://doi.org/10.3390/rs16091618
dc.description.peerreviewedSIes_ES
dc.relation.projectIDContract No. 4000138806/22/I-DT-bgh (EOP—Future EO Open Call for Proposals)es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
dc.journal.titleRemote Sensinges_ES
dc.volume.number16es_ES
dc.issue.number9es_ES
dc.page.initial1es_ES
dc.page.final19es_ES
dc.type.hasVersioninfo:eu-repo/semantics/publishedVersiones_ES
dc.subject.unesco3301 Ingeniería y Tecnología Aeronáuticases_ES
dc.description.projectEuropean Space Agencyes_ES


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Attribution-NonCommercial-NoDerivatives 4.0 Internacional
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