Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/30513
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dc.contributor.authorWilkie, Craig Jen_UK
dc.contributor.authorScott, E Marianen_UK
dc.contributor.authorMiller, Claireen_UK
dc.contributor.authorTyler, Andrew Nen_UK
dc.contributor.authorHunter, Peter Den_UK
dc.contributor.authorSpyrakos, Evangelosen_UK
dc.date.accessioned2019-12-10T01:01:04Z-
dc.date.available2019-12-10T01:01:04Z-
dc.date.issued2015en_UK
dc.identifier.urihttp://hdl.handle.net/1893/30513-
dc.description.abstractChlorophyll a is a green pigment, used as an indirect measure of lake water quality. Its strong absorption of blue and red light allows for quantification through satellite images, providing better spatial coverage than traditional in-lake samples. However, grid-cell scale imagery must be calibrated spatially using in-lake point samples, presenting a change-of-support problem. This paper presents a method of statistical downscaling, namely a Bayesian spatially-varying coefficient regression, which assimilates remotely-sensed and in-lake data, resulting in a fully calibrated spatial map of chlorophyll a with associated uncertainty measures. The model is applied to a case study dataset from Lake Balaton, Hungary.en_UK
dc.language.isoenen_UK
dc.publisherElsevier BVen_UK
dc.relationWilkie CJ, Scott EM, Miller C, Tyler AN, Hunter PD & Spyrakos E (2015) Data Fusion of Remote-sensing and In-lake chlorophyll a Data Using Statistical Downscaling. Stein A (Editor) & Allard D (Editor) Spatial Statistics conference 2015, Avignon, France, 09.06.2015-12.06.2015. Procedia Environmental Sciences, 26, pp. 123-126. https://doi.org/10.1016/j.proenv.2015.05.014en_UK
dc.rights© 2015 The Authors. Published by Elsevier B.V This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)en_UK
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/en_UK
dc.subjectstatistical downscalingen_UK
dc.subjectBayesian spatially-varying coefficientsen_UK
dc.subjectchlorophyll aen_UK
dc.subjectspatial calibrationen_UK
dc.subjectMCMCen_UK
dc.titleData Fusion of Remote-sensing and In-lake chlorophyll a Data Using Statistical Downscalingen_UK
dc.typeConference Paperen_UK
dc.identifier.doi10.1016/j.proenv.2015.05.014en_UK
dc.citation.jtitleProcedia Environmental Sciencesen_UK
dc.citation.issn1878-0296en_UK
dc.citation.issn1878-0296en_UK
dc.citation.volume26en_UK
dc.citation.spage123en_UK
dc.citation.epage126en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.contributor.funderNatural Environment Research Councilen_UK
dc.citation.conferencedates2015-06-09 - 2015-06-12en_UK
dc.citation.conferencelocationAvignon, Franceen_UK
dc.citation.conferencenameSpatial Statistics conference 2015en_UK
dc.citation.date05/06/2015en_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationUniversity of Glasgowen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.identifier.isiWOS:000380492800025en_UK
dc.identifier.wtid1450561en_UK
dc.contributor.orcid0000-0003-0604-5827en_UK
dc.contributor.orcid0000-0001-7269-795Xen_UK
dc.date.accepted2015-12-15en_UK
dc.description.refREF Compliant by Deposit in Stirling's Repositoryen_UK
dc.date.filedepositdate2019-12-06en_UK
Appears in Collections:Biological and Environmental Sciences Conference Papers and Proceedings

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