Identificador persistente para citar o vincular este elemento: http://hdl.handle.net/10553/70997
Campo DC Valoridioma
dc.contributor.authorEugenio, Francisco-
dc.contributor.authorMarcello, Javier-
dc.contributor.authorMartin, Javier-
dc.date.accessioned2020-03-21T06:05:57Z-
dc.date.available2020-03-21T06:05:57Z-
dc.date.issued2020-
dc.identifier.issn2072-4292-
dc.identifier.otherScopus-
dc.description.abstractThe accurate monitoring of water quality indicators, bathymetry and distribution of benthic habitats in vulnerable ecosystems is key to assessing the effects of climate change, the quality of natural areas and to guide appropriate biodiversity, tourism or fisheries policies. Coastal and inland water ecosystems are very complex but crucial due to their richness and primary production. In this context, remote sensing can be a reliable way to monitor these areas, mainly thanks to satellite sensors' improved spatial and spectral capabilities and airborne or drone instruments. In general, mapping bodies of water is challenging due to low signal-to-noise (SNR) at sensor level, due to the very low reflectance of water surfaces as well as atmospheric effects. Therefore, the main objective of this work is to provide a robust processing framework to estimate water quality parameters in inland shallow waters using multiplatform data. More specifically, we measured chlorophyll concentrations (Chl-a) from multispectral and hyperspectral sensors on board satellites, aircrafts and drones. The Natural Reserve of Maspalomas, Canary Island (Spain), was chosen for the study because of its complexity as well as being an inner lagoon with considerable organic and inorganic matter and chlorophyll concentration. This area can also be considered a well-known coastal-dune ecosystem attracting a large amount of tourists. The water quality parameter estimated by the remote sensing platforms has been validated using co-temporal in situ measurements collected during field campaigns, and quite satisfactory results have been achieved for this complex ecosystem. In particular, for the drone hyperspectral instrument, the root mean square error, computed to quantify the differences between the estimated and in situ chlorophyll-a concentrations, was 3.45 with a bias of 2.96.-
dc.languageeng-
dc.relation.ispartofRemote Sensing-
dc.sourceRemote Sensing [ISSN 2072-4292], v. 12 (2), p. 284-
dc.subject3325 Tecnología de las telecomunicaciones-
dc.subject.otherAirborne-
dc.subject.otherDrone-
dc.subject.otherHyperspectral Imagery-
dc.subject.otherInner Lake-
dc.subject.otherMultiplatform-
dc.subject.otherProtected Ecosystem-
dc.subject.otherWater Quality Mapping-
dc.subject.otherWorldview Satellites-
dc.titleMultiplatform earth observation systems for monitoring water quality in vulnerable inland ecosystems: Maspalomas water lagoon-
dc.typeinfo:eu-repo/semantics/Article-
dc.typeArticle-
dc.identifier.doi10.3390/rs12020284-
dc.identifier.scopus85081082378-
dc.identifier.isi000515569800083-
dc.contributor.authorscopusid6603605357-
dc.contributor.authorscopusid6602158797-
dc.contributor.authorscopusid57199282278-
dc.identifier.eissn2072-4292-
dc.identifier.issue2-
dc.relation.volume12-
dc.investigacionIngeniería y Arquitectura-
dc.type2Artículo-
dc.contributor.daisngid5242233-
dc.contributor.daisngid702897-
dc.contributor.daisngid4911820-
dc.description.notasARTEMISAT-2 (CTM2016-77733-R)-
dc.description.numberofpages18-
dc.utils.revision-
dc.contributor.wosstandardWOS:Eugenio, F-
dc.contributor.wosstandardWOS:Marcello, J-
dc.contributor.wosstandardWOS:Martin, J-
dc.date.coverdateEnero 2020-
dc.identifier.ulpgces
dc.description.sjr1,285
dc.description.jcr4,848
dc.description.sjrqQ1
dc.description.jcrqQ1
dc.description.scieSCIE
item.grantfulltextnone-
item.fulltextSin texto completo-
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.deptDepartamento de Ingeniería Telemática-
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-
crisitem.author.fullNameMartín Abasolo, Javier-
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