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dc.contributor.authorBrewin, Robert J. W.-
dc.contributor.authorHardman-Mountford, Nick J.-
dc.contributor.authorLavender, Samantha J.-
dc.contributor.authorRaitsos, Dionysios E.-
dc.contributor.authorHirata, Takafumi-
dc.contributor.authorUitz, Julia-
dc.contributor.authorDevred, Emmanuel-
dc.contributor.authorBricaud, Annick-
dc.contributor.authorCiotti, Aurea-
dc.contributor.authorGentili, Bernard-
dc.date.accessioned2014-05-20T15:31:32Z-
dc.date.accessioned2016-10-25T18:07:24Z-
dc.date.available2014-05-20T15:31:32Z-
dc.date.available2016-10-25T18:07:24Z-
dc.date.issued2011-02-15-
dc.identifierhttp://dx.doi.org/10.1016/j.rse.2010.09.004-
dc.identifier.citationRemote Sensing of Environment. New York: Elsevier B.V., v. 115, n. 2, p. 325-339, 2011.-
dc.identifier.issn0034-4257-
dc.identifier.urihttp://hdl.handle.net/11449/40644-
dc.identifier.urihttp://acervodigital.unesp.br/handle/11449/40644-
dc.description.abstractSatellite remote sensing of ocean colour is the only method currently available for synoptically measuring wide-area properties of ocean ecosystems, such as phytoplankton chlorophyll biomass. Recently, a variety of bio-optical and ecological methods have been established that use satellite data to identify and differentiate between either phytoplankton functional types (PFTs) or phytoplankton size classes (PSCs). In this study, several of these techniques were evaluated against in situ observations to determine their ability to detect dominant phytoplankton size classes (micro-, nano- and picoplankton). The techniques are applied to a 10-year ocean-colour data series from the SeaWiFS satellite sensor and compared with in situ data (6504 samples) from a variety of locations in the global ocean. Results show that spectral-response, ecological and abundance-based approaches can all perform with similar accuracy. Detection of microplankton and picoplankton were generally better than detection of nanoplankton. Abundance-based approaches were shown to provide better spatial retrieval of PSCs. Individual model performance varied according to PSC, input satellite data sources and in situ validation data types. Uncertainty in the comparison procedure and data sources was considered. Improved availability of in situ observations would aid ongoing research in this field. (C) 2010 Elsevier B.V. All rights reserved.en
dc.description.sponsorshipNational Environmental Research Council, UK-
dc.description.sponsorshipNational Centre for Earth Observation-
dc.description.sponsorshipNERC-
dc.description.sponsorshipNational Aeronautics and Space Administration (NASA)-
dc.format.extent325-339-
dc.language.isoeng-
dc.publisherElsevier B.V.-
dc.sourceWeb of Science-
dc.subjectPhytoplanktonen
dc.subjectSizeen
dc.subjectOcean colouren
dc.subjectRemote sensingen
dc.subjectPigmenten
dc.subjectChlorophyll-aen
dc.subjectSeaWiFSen
dc.subjectAbsorptionen
dc.titleAn intercomparison of bio-optical techniques for detecting dominant phytoplankton size class from satellite remote sensingen
dc.typeoutro-
dc.contributor.institutionUniv Plymouth-
dc.contributor.institutionPML-
dc.contributor.institutionARGANS Ltd-
dc.contributor.institutionHCMR-
dc.contributor.institutionSir Alister Hardy Fdn Ocean Sci-
dc.contributor.institutionUniv Calif San Diego-
dc.contributor.institutionDalhousie Univ-
dc.contributor.institutionBedford Inst Oceanog-
dc.contributor.institutionUniv Paris 06-
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)-
dc.description.affiliationUniv Plymouth, Sch Marine Sci & Engn, Plymouth PL4 8AA, Devon, England-
dc.description.affiliationPML, Natl Ctr Earth Observat, Plymouth PL1 3DH, Devon, England-
dc.description.affiliationARGANS Ltd, Unit 3, Plymouth PL6 8BY, Devon, England-
dc.description.affiliationHCMR, Anavissos 19013, Attica, Greece-
dc.description.affiliationSir Alister Hardy Fdn Ocean Sci, Plymouth PL1 2PB, Devon, England-
dc.description.affiliationUniv Calif San Diego, Marine Phys Lab, Scripps Inst Oceanog, La Jolla, CA 92093 USA-
dc.description.affiliationDalhousie Univ, Dept Oceanog, Halifax, NS B3H 4J1, Canada-
dc.description.affiliationBedford Inst Oceanog, Ocean Sci Div, Dartmouth, NS B2Y 4A2, Canada-
dc.description.affiliationUniv Paris 06, CNRS, Lab Oceanog Villefranche, Villefranche Sur Mer, France-
dc.description.affiliationUniv Estadual Paulista, BR-11220900 São Paulo, Brazil-
dc.description.affiliationUnespUniv Estadual Paulista, BR-11220900 São Paulo, Brazil-
dc.identifier.doi10.1016/j.rse.2010.09.004-
dc.identifier.wosWOS:000286782500006-
dc.rights.accessRightsAcesso restrito-
dc.relation.ispartofRemote Sensing of Environment-
Appears in Collections:Artigos, TCCs, Teses e Dissertações da Unesp

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