Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters SCIE SCOPUS

DC Field Value Language
dc.contributor.author Balasubramanian S.V. -
dc.contributor.author Pahlevan N. -
dc.contributor.author Smith B. -
dc.contributor.author Binding C. -
dc.contributor.author Schalles J. -
dc.contributor.author Loisel H. -
dc.contributor.author Gurlin D. -
dc.contributor.author Greb S. -
dc.contributor.author Alikas K. -
dc.contributor.author Randla M. -
dc.contributor.author Bunkei M. -
dc.contributor.author Moses W. -
dc.contributor.author Nguyễn H. -
dc.contributor.author Lehmann M.K. -
dc.contributor.author O'Donnell D. -
dc.contributor.author Ondrusek M. -
dc.contributor.author Han, Tai Hyun -
dc.contributor.author Fichot C.G. -
dc.contributor.author Moore T. -
dc.contributor.author Boss E. -
dc.date.accessioned 2020-12-10T07:46:18Z -
dc.date.available 2020-12-10T07:46:18Z -
dc.date.created 2020-06-08 -
dc.date.issued 2020-09 -
dc.identifier.issn 0034-4257 -
dc.identifier.uri https://sciwatch.kiost.ac.kr/handle/2020.kiost/38588 -
dc.description.abstract One of the challenging tasks in modern aquatic remote sensing is the retrieval of near-surface concentrations of Total Suspended Solids (TSS). This study aims to present a Statistical, inherent Optical property (IOP)-based, and muLti-conditional Inversion proceDure (SOLID) for enhanced retrievals of satellite-derived TSS under a wide range of in-water bio-optical conditions in rivers, lakes, estuaries, and coastal waters. In this study, using a large in situ database (N > 3500), the SOLID model is devised using a three-step procedure: (a) water-type classification of the input remote sensing reflectance (R-rs), (b) retrieval of particulate backscattering (b(bp)) in the red or near-infrared (NIR) regions using semi-analytical, machine-learning, and empirical models, and (c) estimation of TSS from b(bp) via water-type-specific empirical models. Using an independent subset of our in situ data (N = 2729) with TSS ranging from 0.1 to 2626.8 [g/m(3)], the SOLID model is thoroughly examined and compared against several state-of-the-art algorithms (Miller and McKee, 2004; Nechad et al., 2010; Novoa et al., 2017; Ondrusek et al., 2012; Petus et al., 2010). We show that SOLID outperforms all the other models to varying degrees, i.e.,from 10 to> 100%, depending on the statistical attributes (e.g., global versus water-type-specific metrics). For demonstration purposes, the model is implemented for images acquired by the MultiSpectral Imager aboard Sentinel-2A/B over the Chesapeake Bay, San-Francisco-Bay-Delta Estuary, Lake Okeechobee, and Lake Taihu. To enable generating consistent, multimission TSS products, its performance is further extended to, and evaluated for, other missions, such as the Ocean and Land Color Instrument (OLCI), Moderate Resolution Imaging Spectroradiometer (MODIS), Visible Infrared Imaging Radiometer Suite (VIIRS), and Operational Land Imager (OLI). Sensitivity analyses on uncertainties induced by the atmospheric correction indicate that 10% uncertainty in R-rs leads to< 20% uncertainty in TSS retrievals from SOLID. While this study suggests that SOLID has a potential for producing TSS products in global coastal and inland waters, our statistical analysis certainly verifies that there is still a need for improving retrievals across a wide spectrum of particle loads. -
dc.description.uri 1 -
dc.language English -
dc.publisher Elsevier Inc. -
dc.title Robust algorithm for estimating total suspended solids (TSS) in inland and nearshore coastal waters -
dc.type Article -
dc.citation.title Remote Sensing of Environment -
dc.contributor.alternativeName 한태현 -
dc.identifier.bibliographicCitation Remote Sensing of Environment -
dc.identifier.doi 10.1016/j.rse.2020.111768 -
dc.identifier.scopusid 2-s2.0-85085340652 -
dc.identifier.wosid 000537691800001 -
dc.type.docType Article -
dc.description.journalClass 1 -
dc.description.isOpenAccess N -
dc.subject.keywordPlus INHERENT OPTICAL-PROPERTIES -
dc.subject.keywordPlus REMOTE-SENSING REFLECTANCE -
dc.subject.keywordPlus QUASI-ANALYTICAL ALGORITHM -
dc.subject.keywordPlus OCEAN COLOR -
dc.subject.keywordPlus PARTICULATE MATTER -
dc.subject.keywordPlus MINERAL PARTICLES -
dc.subject.keywordPlus SATELLITE DATA -
dc.subject.keywordPlus SEDIMENT CONCENTRATION -
dc.subject.keywordPlus ATMOSPHERIC CORRECTION -
dc.subject.keywordPlus FIELD-MEASUREMENTS -
dc.subject.keywordAuthor Total suspended solids -
dc.subject.keywordAuthor Remote sensing reflectance -
dc.subject.keywordAuthor Backscattering -
dc.subject.keywordAuthor Coastal and inland waters -
dc.subject.keywordAuthor Inversion models -
dc.subject.keywordAuthor Inherent optical properties -
dc.subject.keywordAuthor Aquatic remote sensing -
dc.subject.keywordAuthor Sentinel-3 -
dc.relation.journalWebOfScienceCategory Environmental Sciences -
dc.relation.journalWebOfScienceCategory Remote Sensing -
dc.relation.journalWebOfScienceCategory Imaging Science & Photographic Technology -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
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Marine Digital Resources Department > Korea Ocean Satellite Center > 1. Journal Articles
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