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dc.contributor.authorMélin, F.
dc.contributor.authorSclepa, G.
dc.contributor.authorJackson, T.
dc.contributor.authorSathyendranath, S.
dc.date.accessioned2021-01-05T16:17:04Z
dc.date.available2021-01-05T16:17:04Z
dc.date.issued2016
dc.identifier.citationMélin, F.; Sclep, G.; Jackson, T, and Sathyendranath, S. (2016) Uncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets Remote Sensing of Environment, 177, pp.107-124. DOI: https://doi.org/10.1016/j.rse.2016.02.014.en_US
dc.identifier.urihttp://hdl.handle.net/11329/1477
dc.identifier.urihttp://dx.doi.org/10.25607/OBP-979
dc.description.abstractAssigning uncertainty to ocean-color satellite products is a requirement to allowinformed use of these data. Here, uncertainty estimates are derived using the comparison on a 12th-degree grid of coincident daily records of the remote-sensing reflectance RRS obtained with the same processing chain from three satellite missions, MERIS, MODIS and SeaWiFS. The approach is spatially resolved and produces σ, the part of the RRS uncertainty budget associated with random effects. The global average of σ decreases with wavelength from approximately 0.7– 0.9 10−3 sr−1 at 412 nm to 0.05–0.1 10−3 sr−1 at the red band, with uncertainties on σ evaluated as 20–30% between 412 and 555 nm, and 30–40% at 670 nm. The distribution of σ shows a restricted spatial variability and small variations with season, which makes the multi-annual global distribution of σ an estimate applicable to all retrievals of the considered missions. The comparison of σ with other uncertainty estimates derived from field data or with the support of algorithms provides a consistent picture. When translated in relative terms, and assuming a relatively low bias, the distribution of σ suggests that the objective of a 5% uncertainty is fulfilled between 412 and 490 nm for oligotrophic waters (chlorophyll-a concentration below 0.1 mg m−3). This study also provides comparison statistics. Spectrally, the mean absolute relative difference between RRS from different missions shows a characteristic U-shapewith both ends at blue and redwavelengths inversely related to the amplitude of RRS. On average and for the considered data sets, SeaWiFS RRS tend to be slightly higher thanMODIS RRS, which in turn appear higher than MERIS RRS. Biases between mission-specific RRS may exhibit a seasonal dependence, particularly in the subtropical belt.en_US
dc.language.isoenen_US
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subject.otherRemote sensing reflectanceen_US
dc.subject.otherUncertainty quantificationen_US
dc.titleUncertainty estimates of remote sensing reflectance derived from comparison of ocean color satellite data sets.en_US
dc.typeJournal Contributionen_US
dc.description.refereedRefereeden_US
dc.format.pagerangepp.107-124en_US
dc.identifier.doihttp://dx.doi.org/10.1016/j.rse.2016.02.014
dc.subject.parameterDisciplineParameter Discipline::Physical oceanography::Other physical oceanographic measurementsen_US
dc.subject.instrumentTypeInstrument Type Vocabulary::radiometersen_US
dc.subject.dmProcessesData Management Practices::Data processingen_US
dc.bibliographicCitation.titleRemote Sensing of Environmenten_US
dc.bibliographicCitation.volume177en_US
dc.description.sdg14.Aen_US
dc.description.eovOcean colouren_US
dc.description.bptypeManual (incl. handbook, guide, cookbook etc)en_US
obps.contact.contactnameF. Mélin
obps.resourceurl.publisherhttps://www.sciencedirect.com/science/article/pii/S0034425716300426/en_US


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Attribution 4.0 International
Except where otherwise noted, this item's license is described as Attribution 4.0 International