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dc.contributor.authorUmbert, Marta-
dc.contributor.authorGuimbard, Sébastien-
dc.contributor.authorBallabrera-Poy, Joaquim-
dc.contributor.authorTuriel, Antonio-
dc.date.accessioned2020-04-15T13:18:19Z-
dc.date.available2020-04-15T13:18:19Z-
dc.date.issued2020-04-03-
dc.identifiere-issn: 2072-4292-
dc.identifier.citationRemote Sensing 12(7): 1153 (2020)-
dc.identifier.otherCEX2019-000928-S-
dc.identifier.urihttp://hdl.handle.net/10261/207712-
dc.descriptionSpecial Issue Ten Years of Remote Sensing at Barcelona Expert Center.-- 13 pages, 5 figures, 1 table-
dc.description.abstractThe similarity of mesoscale and submesoscale features observed in different ocean scalars indicates that they undergo some common non-linear processes. As a result of quasi-2D turbulence, complicated patterns of filaments, meanders, and eddies are recognized in remote sensing images. A data fusion method used to improve the quality of one ocean variable using another variable as a template is used here as an extrapolation technique to improve the coverage of daily Aqua MODIS Level-3 chlorophyll maps by using MODIS SST maps as a template. The local correspondence of SST and Chl-a multifractal singularities is granted due to the existence of a common cascade process which makes it possible to use SST data to infer Chl-a concentration where data are lacking. The quality of the inference of Level-4 Chl-a maps is assessed by simulating artificial clouds and comparing reconstructed and original data-
dc.description.sponsorshipM.U. is funded by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Individual Fellowship Career Restart Panel (MSCA-IF-EF-CAR Number 840374)-
dc.description.sponsorshipWith the funding support of the ‘Severo Ochoa Centre of Excellence’ accreditation (CEX2019-000928-S), of the Spanish Research Agency (AEI)-
dc.publisherMultidisciplinary Digital Publishing Institute-
dc.relation.isversionofPublisher's version-
dc.rightsopenAccess-
dc.subjectRemote sensing-
dc.subjectOcean color-
dc.subjectData fusion-
dc.subjectData merging-
dc.subjectPhysical oceanography-
dc.subjectSingularity analysi-
dc.titleSynergy between Ocean Variables: Remotely Sensed Surface Temperature and Chlorophyll Concentration Coherence-
dc.typeartículo-
dc.identifier.doihttp://dx.doi.org/10.3390/rs12071153-
dc.relation.publisherversionhttps://doi.org/10.3390/rs12071153-
dc.date.updated2020-04-15T13:18:19Z-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/-
dc.contributor.funderEuropean Commission-
dc.contributor.funderAgencia Estatal de Investigación (España)-
dc.relation.csic-
dc.identifier.funderhttp://dx.doi.org/10.13039/501100000780es_ES
dc.identifier.funderhttp://dx.doi.org/10.13039/501100011033es_ES
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