Utilize este identificador para referenciar este registo: http://hdl.handle.net/10362/173177
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Campo DCValorIdioma
dc.contributor.authorAlmeida, Bruna-
dc.contributor.authorCabral, Pedro-
dc.date.accessioned2024-10-08T22:10:21Z-
dc.date.available2024-10-08T22:10:21Z-
dc.date.issued2024-07-03-
dc.identifier.otherPURE: 100883326-
dc.identifier.otherPURE UUID: 6fca3e5d-0553-4d7d-8ea3-bc3e7625e77f-
dc.identifier.otherORCID: /0000-0002-3349-1470/work/170199348-
dc.identifier.otherORCID: /0000-0001-8622-6008/work/170201413-
dc.identifier.urihttp://hdl.handle.net/10362/173177-
dc.descriptionAlmeida, B., & Cabral, P. (2024). A Hybrid Modelling Approach for Detecting Seasonal Variations in Inland Green-Blue Ecosystems [poster]. 1. Poster session presented at Encontro Ciência 2024, Porto, Portugal. --- This study was supported by the research project MaSOT – Mapping Ecosystem Services from Earth Observations, funded by the Portuguese Science Foundation – FCT [EXPL/CTA-AMB/0165/2021], and by national funds through FCT (Fundação para a Ciência e a Tecnologia), under the project - UIDB/04152/2020 (DOI: 10.54499/UIDB/04152/2020) - Centro de Investigação em Gestão de Informação (MagIC)/NOVA IMS)-
dc.description.abstractDeforestation, environmental pollution, and the overexploitation of resources, in addition to the Earth's natural cycles, are scaling up the impacts of climate change in the provision of Ecosystem Services (ES). Green-Blue Ecosystems (GBE) are impacted by climatic conditions, topography, and water presence. In the context of climate change, Portugal is recognized as a hotspot among the most vulnerable European countries. Recent studies have shown evidence of climatic changes, such as the long periods of drought recorded in 1990, 2004/2005 and2012. The more frequent occurrence of these events is increasing the severity of seasonality effects on GBE and compromising the provision of services such as freshwater supply, and consequently crop and wood production, and carbon storage and sequestration.en
dc.format.extent1-
dc.language.isoeng-
dc.relationinfo:eu-repo/grantAgreement/FCT/3599-PPCDT/EXPL%2FCTA-AMB%2F0165%2F2021/PT-
dc.relationinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04152%2F2020/PT-
dc.relationhttps://doi.org/10.54499/EXPL/CTA-AMB/0165/2021-
dc.rightsrestrictedAccess-
dc.subjectRemote Sensing-
dc.subjectMachine Learning-
dc.subjectGeographic Information Systems-
dc.subjectAquatic Ecosystems-
dc.subjectTerrestrial Ecosystems-
dc.subjectClimate Change-
dc.subjectSDG 6 - Clean Water and Sanitation-
dc.subjectSDG 11 - Sustainable Cities and Communities-
dc.subjectSDG 12 - Responsible Consumption and Production-
dc.subjectSDG 13 - Climate Action-
dc.subjectSDG 15 - Life on Land-
dc.titleA Hybrid Modelling Approach for Detecting Seasonal Variations in Inland Green-Blue Ecosystems [poster]-
dc.typeconferenceObject-
degois.publication.firstPage-
degois.publication.issue13-
degois.publication.lastPage-
degois.publication.titleEncontro Ciência 2024-
dc.peerreviewedno-
dc.description.versionpublishersversion-
dc.description.versionunpublished-
dc.contributor.institutionInformation Management Research Center (MagIC) - NOVA Information Management School-
Aparece nas colecções:NIMS: MagIC - Documentos de conferências nacionais

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