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dc.contributor.authorTheenathayalan, V
dc.contributor.authorSathyendranath, S
dc.contributor.authorKulk, G
dc.contributor.authorMenon, N
dc.contributor.authorGeorge, G
dc.contributor.authorAbdulaziz, A
dc.contributor.authorSelmes, N
dc.contributor.authorBrewin, R
dc.contributor.authorRajendran, A
dc.contributor.authorXavier, S
dc.contributor.authorPlatt, T
dc.date.accessioned2023-01-03T14:19:47Z
dc.date.issued2022-12-19
dc.date.updated2023-01-03T11:37:57Z
dc.description.abstractA growing coastal population is leading to increased anthropogenic pollution that greatly affects coastal and inland water bodies, especially in the tropics. The Sustainable Development Goal-14, ‘Life below water’ emphasises the importance of conservation and sustainable use of the ocean and its resources. Pollution management practices often include monitoring of water quality using in situ observations of chlorophyll-a (chl-a) and total suspended matter (TSM). Satellite technology, including the MultiSpectral Instrument (MSI) sensor onboard Sentinel-2, enables the continuous monitoring of these variables in inland waters at high spatial and temporal resolutions. To improve the monitoring of water quality in the tropical Vembanad-Kol-Wetland (VKW) system, situated on the southwest coast of India, we present two regionally tuned satellite algorithms developed to estimate chl-a and TSM concentrations. The new algorithms estimate the chl-a and TSM concentrations from the simulated reflectance values as a function of the inherent optical properties using a forward modelling approach. The model was parameterised using the National Aeronautics and Space Administration (NASA) bio-Optical Marine Algorithm Dataset (NOMAD) and in situ measurements collected in the VKW system. To assess model performance, results were compared with in situ measurements of chl-a and TSM and other existing satellite-based models of chl-a and TSM. For satellite application, two different atmospheric correction methods (ACOLITE and POLYMER) were tested and satellite matchups were used to validate the new chl-a and TSM algorithms following standard validation procedures. The results demonstrated that the new algorithms were in good agreement with in situ observations and outperform existing chl-a and TSM algorithms. The new regional satellite algorithms can be used to monitor water quality within the VKW system to support the sustainable management under natural (cyclones, floods, rainfall, and tsunami) and anthropogenic pressures (industrial effluents, agricultural practices, recreational activities, construction, and demolishing concrete structures) and help achieve Sustainable Development Goal 14.en_GB
dc.description.sponsorshipNatural Environment Research Council (NERC)en_GB
dc.description.sponsorshipDepartment of Science and Technology, Indiaen_GB
dc.description.sponsorshipEuropean Space Agencyen_GB
dc.description.sponsorshipUKRIen_GB
dc.format.extent6404-
dc.identifier.citationVol. 14(24), article 6404en_GB
dc.identifier.doihttps://doi.org/10.3390/rs14246404
dc.identifier.grantnumberDST/TM/INDOUK/2K17/64en_GB
dc.identifier.grantnumberMR/V022792/1en_GB
dc.identifier.urihttp://hdl.handle.net/10871/132132
dc.identifierORCID: 0000-0001-5134-8291 (Brewin, Robert)
dc.identifierScopusID: 35725269400 (Brewin, Robert)
dc.language.isoenen_GB
dc.publisherMDPIen_GB
dc.rights© 2022 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 (CC BY) license (https://creativecommons.org/licenses/by/4.0/).en_GB
dc.subjectwater constituentsen_GB
dc.subjectabsorptionen_GB
dc.subjectbackscatteringen_GB
dc.subjectforward modellingen_GB
dc.subjectACOLITEen_GB
dc.subjectPOLYMERen_GB
dc.subjectatmospheric correctionen_GB
dc.subjectremote-sensing reflectanceen_GB
dc.subjectwater qualityen_GB
dc.subjectinland watersen_GB
dc.subjectsustainable development goalsen_GB
dc.titleRegional Satellite Algorithms to Estimate Chlorophyll-a and Total Suspended Matter Concentrations in Vembanad Lakeen_GB
dc.typeArticleen_GB
dc.date.available2023-01-03T14:19:47Z
dc.identifier.issn2072-4292
dc.descriptionThis is the final version. Available on open access from MDPI via the DOI in this recorden_GB
dc.descriptionData Availability Statement: Data available with the corresponding author. Would be shared on request.en_GB
dc.identifier.eissn2072-4292
dc.identifier.journalRemote Sensingen_GB
dc.relation.ispartofRemote Sensing, 14(24)
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/en_GB
dcterms.dateAccepted2022-12-10
rioxxterms.versionVoRen_GB
rioxxterms.licenseref.startdate2022-12-19
rioxxterms.typeJournal Article/Reviewen_GB
refterms.dateFCD2023-01-03T14:17:29Z
refterms.versionFCDVoR
refterms.dateFOA2023-01-03T14:19:52Z
refterms.panelBen_GB
refterms.dateFirstOnline2022-12-19


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© 2022 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 (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Except where otherwise noted, this item's licence is described as © 2022 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 (CC BY) license (https://creativecommons.org/licenses/by/4.0/).