Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.12779/5805
DC FieldValueLanguage
dc.contributor.authorHorion, Sen_us
dc.contributor.authorN., Bergaminoen_us
dc.contributor.authorS., Sténuiteen_us
dc.contributor.authorJ. P., Descyen_us
dc.contributor.authorP. D., Plisnieren_us
dc.contributor.authorLoiselle, Steven Arthuren_us
dc.contributor.authorY., Corneten_us
dc.date.accessioned2021-03-30T15:55:16Z-
dc.date.available2021-03-30T15:55:16Z-
dc.date.issued2010-
dc.identifier.issn0034-4257en_US
dc.identifier.urihttp://hdl.handle.net/20.500.12779/5805-
dc.description24116en_US
dc.description.abstractLake Tanganyika is one of the world’s great freshwater ecosystems. In recent decades its hydrodynamic characteristics have undergone important changes that have had consequences on the Lake’s primary productivity. The establishment of a long-term Ocean Color dataset for Lake Tanganyika is a fundamental tool for understanding and monitoring these changes. We develop an alternative approach to create a regionally calibrated dataset of chlorophyll-a concentrations (CHL) and attenuation coefficients at 490 nm (K490) for the period from July 2002 to December 2006 using daily calibrated radiances retrieved from the MODIS-Aqua sensor. Standard MODIS Aqua Ocean Color products were found to not provide a suitable calibration for high altitude lakes such as the Lake Tanganyika. The optimization of the extraction process and the validation of the dataset were performed with independent sets of in situ measurements. Our results show that for geographical, atmospheric and optical conditions of Lake Tanganyika: (i) the coastal aerosol model set with a high relative humidity (90%) performs the best for the atmospheric correction; (ii) a significant correlation between in situ data and CHL estimates using the MODIS specific 0C3 algorithm is possible; (iii) K490 estimates provide a good level of significance. The development of a validated time series of bio-optical properties provides an important information base for the study of lake dynamics and interannual trends.en_US
dc.language.isoenen_US
dc.relationNoneen_US
dc.relation.ispartofREMOTE SENSING OF ENVIRONMENTen_US
dc.subjectPhytoplankton dynamics; Bio-optical algorithms; SeaDAS process optimization; MODIS Aqua; Lake Tanganyikaen_US
dc.titleOptimized extraction of daily bio-optical time series derived from MODIS/Aqua imagery for Lake Tanganyika, Africaen_US
dc.typeArticleen_US
dc.identifier.scopus2-s2.0-75149112247en_US
dc.identifier.isiWOS:000274982700008en_US
dc.relation.volume114en_US
dc.description.firstpage781en_US
dc.description.lastpage791en_US
dc.description.thirdmissionNot applicableen_US
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.openairetypeArticle-
item.fulltextNo Fulltext-
crisitem.author.orcid0000-0001-7414-0389-
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