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dc.contributor.authorSacala, Pietro
dc.contributor.authorToimil Silva, Alexandra
dc.contributor.authorÁlvarez Cuesta, Moisés 
dc.contributor.authorManno, Giorgio
dc.contributor.authorCiraolo, Giuseppe
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2025-01-30T10:46:13Z
dc.date.available2025-01-30T10:46:13Z
dc.date.issued2024-09-27
dc.identifier.issn2045-2322
dc.identifier.otherPID2021-126506OB-100es_ES
dc.identifier.urihttps://hdl.handle.net/10902/35246
dc.description.abstractCoastal zones are dynamic interfaces shaped by the interplay of Land Cover (LC) and Land Use (LU), influenced by both natural processes and anthropogenic activities. Grasping the historical shifts in land is essential for safeguarding coastal benefits such as defense mechanisms, biodiversity conservation, and recreational spaces, alongside enhancing their management. LC and LU products offer a valuable option for monitoring urban development, vegetation coverage, and dry-beach areas. Herein, we present the first study of the spatiotemporal evolution of LC specifically tailored for coastal zones, using the coast of Sicily as an illustration. We used classified satellite imagery from Landsat and Sentinel missions as input for a semantic segmentation model based on deep neural networks. We trained the model with an extensive dataset of coastal images. Our classification and analysis of coastal LC dynamics from 1988 to 2022 provide insights at a high spatiotemporal resolution. We identified key factors driving urban transformation, underscoring the impact of urban expansion on vegetated areas, and explored its correlation with economic and demographic growth. This study includes a multiscale analysis of coastal changes, encompassing long-term trends and seasonal fluctuations across Sicilian beaches. Our findings can contribute to preserve coastal areas by informing policymaking aimed at sustainable management.es_ES
dc.description.sponsorshipA.T. acknowledges the financial support from the Ministerio de Ciencia e Innovación through the Ramon y Cajal Programme (RYC2021-030873-I with funding from MCIN/AEI and NextGenerationEU/PRTR) and the grant COASTALfutures (PID2021-126506OB-100 with funding from MCIN/AEI/ 10.13039/501100011033/FEDER UE). G.M. is supported by the RE- TURN Extended Partnership funded by the European Union - Next Generation-EU (National Recovery and Resilience Plan – NRRP, Mission 4, Component 2, Investment 1.3 – D.D. 1243 2/8/2022, PE0000005).es_ES
dc.format.extent16 p.es_ES
dc.language.isoenges_ES
dc.publisherNaturees_ES
dc.rightsAttribution-NonCommercial-NoDerivatives 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/*
dc.sourceScientific Reports, 2024, 14, 22222es_ES
dc.titleMapping decadal land cover dynamics in Sicily’s coastal regionses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1038/s41598-024-73085-5es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2021-2023/PID2021-126506OB-I00/ES/AVANCES EN LA PROYECCION DEL RIESGO COMBINADO DE INUNDACION Y EROSION EN LA COSTA POR EFECTO DEL CAMBIO CLIMATICO/es_ES
dc.identifier.DOI10.1038/s41598-024-73085-5
dc.type.versionpublishedVersiones_ES


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Attribution-NonCommercial-NoDerivatives 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution-NonCommercial-NoDerivatives 4.0 International