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dc.contributor.authorDOWELL Marken_GB
dc.contributor.authorMOORE Timothy S.en_GB
dc.contributor.authorFRANZ Bryanen_GB
dc.date.accessioned2013-01-31T01:02:21Z-
dc.date.available2013-01-30en_GB
dc.date.available2013-01-31T01:02:21Z-
dc.date.created2013-01-08en_GB
dc.date.issued2012en_GB
dc.date.submitted2011-11-04en_GB
dc.identifier.citationREMOTE SENSING OF ENVIRONMENT vol. 117 p. 249-263en_GB
dc.identifier.issn0034-4257en_GB
dc.identifier.urihttp://www.sciencedirect.com/science/article/pii/S003442571100349Xen_GB
dc.identifier.urihttp://publications.jrc.ec.europa.eu/repository/handle/JRC67442-
dc.description.abstractA generalized coccolithophore bloom classifier has been developed for use with ocean color imagery. The bloom classifier was developed using extracted satellite reflectance data from SeaWiFS images screened by default bloom detection mask. In the current application, we extend the optical water type (OWT) classification scheme by adding a new coccolithophore bloom class formed from these extracted reflectances. Based on an in situ coccolithophore data set from the North Atlantic, the detection levels with the new scheme were between 1,500 and 1,800 coccolithophore cells/mL and 43,000 and 78,000 liths/mL. The detected bloom area using the OWT method was an average of 1.75 times greater than the default bloom detector based on a collection of SeaWiFS 1 km imagery. The versatility of the scheme is shown with SeaWiFS, MODIS Aqua, CZCS and MERIS imagery at the 1 km scale. The OWT scheme was applied to the daily global SeaWiFS imagery mission data set (years 1997–2010). Based on our results, average annual coccolithophore bloom area was more than two times greater in the southern hemisphere compared to the northern hemisphere with values of 2.00 × 106 km2 and 0.75 × 106 km2, respectively. The new algorithm detects larger bloom areas in the Southern Ocean compared to the default algorithm, and our revised global annual average of 2.75 × 106 km2 is dominated by contributions from the Southern Ocean.en_GB
dc.description.sponsorshipJRC.H.5-Land Resources Managementen_GB
dc.format.mediumOnlineen_GB
dc.languageENGen_GB
dc.publisherELSEVIER SCIENCE INCen_GB
dc.relation.ispartofseriesJRC67442en_GB
dc.titleDetection of coccolithophore blooms in ocean color satellite imagery: A generalized approach for use with multiple sensorsen_GB
dc.typeArticles in periodicals and booksen_GB
dc.identifier.doi10.1016/j.rse.2011.10.001en_GB
JRC Directorate:Sustainable Resources

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