Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/118795
Campo DC Valoridioma
dc.contributor.authorMederos Barrera, Antonio Ramónen_US
dc.contributor.authorMarcello, J.en_US
dc.contributor.authorEugenio, F.en_US
dc.contributor.authorHernández Pérez, Eduardoen_US
dc.date.accessioned2022-10-10T09:29:11Z-
dc.date.available2022-10-10T09:29:11Z-
dc.date.issued2022en_US
dc.identifier.issn1569-8432en_US
dc.identifier.otherScopus-
dc.identifier.urihttp://hdl.handle.net/10553/118795-
dc.description.abstractSatellite remote sensing is an efficient and economical technique for studying coastal bottoms in clear and shallow waters. Accordingly, the main objective of this study is the generation of benthic maps using high spatial resolution multispectral images from the WorldView-2/3 satellites. In this context, one of the main challenges consists of eliminating the disturbances caused in the signal by the atmosphere, the sea surface, and the water column. Regarding the water column correction, there is controversy about its effectiveness to improve the results achieved. To assess the impact of the water column correction in seagrass mapping, two coastal areas with different characteristics have been selected. Specifically, an analysis has been carried out consisting of the assessment of the Lyzenga and Sagawa water column correction models to identify the algorithm that provides the best mapping precision and, additionally, to seek if this pre-processing stage is helpful when classifying the seabed. The classification models selected for the study were: Gaussian Naïve Bayes (GNB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN), and Subspace KNN (S-KNN). Machine learning techniques have proven to achieve better results and, in particular, SVM and KNN models provide the best overall accuracy. The results after benthic mapping have demonstrated, that image classification without water column corrections provides better accuracy (95.36% and 99.20%) than using Lyzenga (73.49% and 97.80%) or Sagawa (82.04% and 99.10%), for Case 2 and 1 waters, respectively.en_US
dc.languageengen_US
dc.relation.ispartofInternational Journal of Applied Earth Observation and Geoinformationen_US
dc.sourceInternational Journal of Applied Earth Observation and Geoinformation[ISSN 1569-8432],v. 113, (Septiembre 2022)en_US
dc.subject2599 Otras especialidades de la tierra, espacio o entornoen_US
dc.subject.otherDepth Invariant Indexen_US
dc.subject.otherHigh Resolution Benthic Mapsen_US
dc.subject.otherSagawaen_US
dc.subject.otherSeagrassen_US
dc.subject.otherWater Column Correctionen_US
dc.subject.otherWorldviewen_US
dc.titleSeagrass mapping using high resolution multispectral satellite imagery: A comparison of water column correction modelsen_US
dc.typeinfo:eu-repo/semantics/Articleen_US
dc.typeArticleen_US
dc.identifier.doi10.1016/j.jag.2022.102990en_US
dc.identifier.scopus85138536642-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.orcidNO DATA-
dc.contributor.authorscopusid57220806560-
dc.contributor.authorscopusid6602158797-
dc.contributor.authorscopusid6603605357-
dc.contributor.authorscopusid23091131800-
dc.identifier.eissn1872-826X-
dc.relation.volume113en_US
dc.investigacionIngeniería y Arquitecturaen_US
dc.type2Artículoen_US
dc.utils.revisionen_US
dc.date.coverdateSeptiembre 2022en_US
dc.identifier.ulpgcen_US
dc.contributor.buulpgcBU-TELen_US
dc.description.sjr1,628-
dc.description.jcr7,5-
dc.description.sjrqQ1-
dc.description.jcrqQ1-
dc.description.miaricds11,0-
item.fulltextSin texto completo-
item.grantfulltextnone-
crisitem.author.deptGIR IOCAG: Procesado de Imágenes y Teledetección-
crisitem.author.deptIU de Oceanografía y Cambio Global-
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.deptGIR IDeTIC: División de Procesado Digital de Señales-
crisitem.author.deptIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.deptDepartamento de Señales y Comunicaciones-
crisitem.author.orcid0000-0002-9646-1017-
crisitem.author.orcid0000-0002-0010-4024-
crisitem.author.orcid0000-0001-7473-5454-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.parentorgIU de Oceanografía y Cambio Global-
crisitem.author.parentorgIU para el Desarrollo Tecnológico y la Innovación-
crisitem.author.fullNameMederos Barrera, Antonio Ramón-
crisitem.author.fullNameMarcello Ruiz, Francisco Javier-
crisitem.author.fullNameEugenio González, Francisco-
crisitem.author.fullNameHernández Pérez, Eduardo-
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