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dc.contributor.authorMUELLER Dagmaren_GB
dc.contributor.authorKRASEMANN Hajoen_GB
dc.contributor.authorBREWIN Roberten_GB
dc.contributor.authorBROCKMANN Carstenen_GB
dc.contributor.authorDESCHAMPS Pierre-Yvesen_GB
dc.contributor.authorDOERFFER Rolanden_GB
dc.contributor.authorFOMFERRA Normanen_GB
dc.contributor.authorFRANZ Bryanen_GB
dc.contributor.authorGRANT M.en_GB
dc.contributor.authorGROOM Steveen_GB
dc.contributor.authorMELIN Fredericen_GB
dc.contributor.authorPLATT Trevoren_GB
dc.contributor.authorREGNER Peteren_GB
dc.contributor.authorSATHYENDRANATH Shubhaen_GB
dc.contributor.authorSTEINMETZ Francoisen_GB
dc.contributor.authorSWINTON Johnen_GB
dc.date.accessioned2015-10-01T00:27:15Z-
dc.date.available2015-09-30en_GB
dc.date.available2015-10-01T00:27:15Z-
dc.date.created2015-09-21en_GB
dc.date.issued2015en_GB
dc.date.submitted2015-04-30en_GB
dc.identifier.citationREMOTE SENSING OF ENVIRONMENT vol. 162 p. 257-270en_GB
dc.identifier.issn0034-4257en_GB
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S0034425715000620en_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC95824-
dc.description.abstractThe established procedure to access the quality of atmospheric correction processors and their underlying algorithms is the comparison of satellite data products with related in-situ measurements. Although this approach addresses the accuracy of derived geophysical properties in a straight forward fashion, it is also limited in its ability to catch systematic sensor and processor dependent behaviour of satellite products along the scan-line, which might impair the usefulness of the data in spatial analyses. The Ocean Colour Climate Change Initiative (OC-CCI) aims to create an ocean colour dataset on a global scale to meet the demands of the ecosystem modelling community. The need for products with increasing spatial and temporal resolution that also show as little systematic and random errors as possible, increases. Due to cloud cover, even temporal means can be influenced by along-scanline artefacts if the observations are not balanced and effects cannot be cancelled out mutually. These effects can arise from a multitude of results which are not easily separated, if at all. Among the sources of artefacts, there are some sensor-specific calibration issues which should lead to similar responses in all processors, as well as processor-specific features which correspond with the individual choices in the algorithms. A set of methods is proposed and applied to MERIS data over two regions of interest in the North Atlantic and the South Pacific Gyre. The normalised water leaving reflectance products of four atmospheric correction processors, which have also been evaluated in match-up analysis, is analysed in order to find and interpret systematic effects across track. These results are summed up with a semi-objective ranking and are used as a complement to the match-up analysis in the decision for the best Atmospheric Correction (AC) processor. Although the need for discussion remains concerning the absolutes by which to judge an AC processor, this example demonstrates clearly, that relying on the match-up analysis alone can lead to misjudgement.en_GB
dc.description.sponsorshipJRC.H.1-Water Resourcesen_GB
dc.format.mediumPrinteden_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE INCen_GB
dc.relation.ispartofseriesJRC95824en_GB
dc.titleThe Ocean Colour Climate Change Initiative. II. Spatial and temporal homogeneity of satellite data retrieval due to systematic effects in atmospheric correction processors.en_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1016/j.rse.2015.01.033en_GB
JRC Directorate:Sustainable Resources

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