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Πεδίο DCΤιμήΓλώσσα
dc.contributor.authorClayton, Chris R I-
dc.contributor.authorHadjimitsis, Diofantos G.-
dc.date.accessioned2012-10-23T09:31:42Zen
dc.date.accessioned2013-05-17T10:30:54Z-
dc.date.accessioned2015-12-09T13:51:56Z-
dc.date.available2012-10-23T09:31:42Zen
dc.date.available2013-05-17T10:30:54Z-
dc.date.available2015-12-09T13:51:56Z-
dc.date.issued2011-02-
dc.identifier.citationRemote Sensing, 2011, vol. 3, no. 2, pp. 362-377en_US
dc.identifier.issn20724292-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/4486-
dc.description.abstractThe overall objective of this study was to use field spectro-radiometers for finding possible spectral regions in which chlorophyll-a (Chl-a) and particulate organic carbon(POC) could be identified so as to assist the assessment and monitoring of water quality using satellite remote sensing technology. This paper presents the methodology adopted in this study which is based on the application of linear regression analysis between the mean reflectance values (measured with the GER1500 field spectro-radiometer) across the spectrum and the concentrations of chlorophyll-a (μg/L) and POC (μg/L) acquired simultaneously on the same day and time in the Lower Thames Valley in West London (U.K.) from old campaigns. Each regression model (512 in total) corresponded to a measured wavelength of the GER1500 field spectro-radiometer. The achieved correlations presented as r2 against wavelength, indicate the regions with high correlation values for both water quality variables. Based on the results from this study and by matching the spectral bands of the field spectro-radiometer with those of the Landsat TM satellite sensor (or any other sensor), it has been found that suitable spectral regions for monitoring water quality in water treatment reservoirs are the following: for chlorophyll-a, the spectral region of 0.45–0.52 μm (TM band 1), and for POC, the region 0.52–0.60 μm (TM bands 1 and 2). Then 12 atmospheric corrected Landsat TM/ETM+ band 1 images acquired from 2001 to 2010 were used for validation purposes to retrieve the Chl-a concentrations.en_US
dc.formatpdfen_US
dc.language.isoenen_US
dc.relation.ispartofRemote Sensingen_US
dc.rights© by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution licenseen_US
dc.subjectLinear regressionen_US
dc.subjectRemote sensingen_US
dc.subjectChl-aen_US
dc.subjectPOCen_US
dc.subjectSpectro-radiometric measurementsen_US
dc.titleField spectroscopy for assisting water quality monitoring and assessment in water treatment reservoirs using atmospheric corrected satellite remotely sensed imageryen_US
dc.typeArticleen_US
dc.collaborationUniversity of Southamptonen_US
dc.collaborationCyprus University of Technologyen_US
dc.subject.categoryCivil Engineeringen_US
dc.journalsOpen Accessen_US
dc.reviewpeer reviewed-
dc.countryCyprusen_US
dc.countryUnited Kingdomen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.identifier.doi10.3390/rs3020362en_US
dc.dept.handle123456789/148en
dc.relation.issue2en_US
dc.relation.volume3en_US
cut.common.academicyear2010-2011en_US
dc.identifier.spage362en_US
dc.identifier.epage377en_US
item.fulltextWith Fulltext-
item.cerifentitytypePublications-
item.grantfulltextopen-
item.openairecristypehttp://purl.org/coar/resource_type/c_6501-
item.openairetypearticle-
item.languageiso639-1en-
crisitem.journal.journalissn2072-4292-
crisitem.journal.publisherMDPI-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-2684-547X-
crisitem.author.parentorgFaculty of Engineering and Technology-
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