Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/128905
Campo DC Valoridioma
dc.contributor.authorEugenio, F.en_US
dc.contributor.authorMederos-Barrera, A.en_US
dc.contributor.authorMarcello, J.en_US
dc.date.accessioned2024-02-14T12:53:39Z-
dc.date.available2024-02-14T12:53:39Z-
dc.date.issued2023en_US
dc.identifier.isbn9798350320107en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/128905-
dc.description.abstractCoastal island ecosystems are unique and fragile environments and very sensitive to climate change and direct anthropogenic impact. The use of remote sensing offers the advantage of monitoring these valuable areas in an accessible and cost-effective manner. The main objective of this research, linked to the sustainable management of littoral areas, is the generation of knowledge that is materialized in the implementation of a robust image processing methodology to generate accurate bathymetry and benthic high-resolution maps in coastal shallow waters using remote sensing satellite multispectral sensors (WorldView-2/3). So, this paper presents a methodology for the monitoring of two protected ecosystems in Canary Islands (Spain): Las Canteras beach (Gran Canaria Island) and the channel of La Graciosa-Lanzarote Island. In addition, a multitemporal study is presented where the usefulness of the technology in the monitoring of marine ecosystems is presented.en_US
dc.languageengen_US
dc.relation.ispartofInternational Geoscience And Remote Sensing Symposium (IGARSS)en_US
dc.sourceInternational Geoscience and Remote Sensing Symposium (IGARSS)[EISSN ],v. 2023-July, p. 4104-4107, (Enero 2023)en_US
dc.subject33 Ciencias tecnológicasen_US
dc.subject.otherArtificial Intelligence Algorithmsen_US
dc.subject.otherBathymetric Mappingen_US
dc.subject.otherBenthic Mappingen_US
dc.subject.otherCoastal Ecosystemsen_US
dc.subject.otherHigh-Resolution Satelliteen_US
dc.titleHigh-Resolution Satellite Monitoring of Vulnerable Coastal Ecosystems Using Advanced Artificial Intelligence Techniquesen_US
dc.typeinfo:eu-repo/semantics/conferenceObjecten_US
dc.typeConferenceObjecten_US
dc.relation.conference2023 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2023en_US
dc.identifier.doi10.1109/IGARSS52108.2023.10282981en_US
dc.identifier.scopus85178368728-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.authorscopusid6603605357-
dc.contributor.authorscopusid57220806560-
dc.contributor.authorscopusid6602158797-
dc.description.lastpage4107en_US
dc.description.firstpage4104en_US
dc.relation.volume2023-Julyen_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Actas de congresosen_US
dc.utils.revisionen_US
dc.date.coverdateEnero 2023en_US
dc.identifier.conferenceidevents150510-
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.event.eventsstartdate27-11-2023-
crisitem.event.eventsenddate30-11-2023-
crisitem.author.deptGIR IOCAG: Procesado de Imágenes y Teledetección-
crisitem.author.deptIU de Oceanografía y Cambio Global-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.deptGIR IOCAG: Procesado de Imágenes y Teledetección-
crisitem.author.deptIU de Oceanografía y Cambio Global-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-0010-4024-
crisitem.author.orcid0000-0002-9646-1017-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.fullNameEugenio González, Francisco-
crisitem.author.fullNameMarcello Ruiz, Francisco Javier-
Colección:Actas de congresos
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