A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
Ocean color remote sensing has been shown to be a useful tool to map turbidity (T) and suspended particulate matter (SPM) concentration in turbid coastal waters. Different algorithms to retrieve T and/or SPM from water reflectance already exist, however there are important questions as to whether th...
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description | Ocean color remote sensing has been shown to be a useful tool to map turbidity (T) and suspended particulate matter (SPM) concentration in turbid coastal waters. Different algorithms to retrieve T and/or SPM from water reflectance already exist, however there are important questions as to whether these algorithms need to be calibrated specifically for different regions. In the present work the potential generality of a semi-empirical single band turbidity retrieval algorithm using the near infrared (NIR) band at 859nm in highly turbid waters is assessed. For completeness the use of 645nm in medium to low turbidity waters is also proposed. Radiative transfer simulations and in situ measurements from various European and South American coastal and shallow estuarine environments characterized by high concentrations of suspended sediments are analyzed. Reflectance and turbidity measurements were performed in the southern North Sea (SNS) and French Guyana (FG) coastal waters, and Scheldt (SC), Gironde (GIR) and Río de la Plata (RdP) estuaries. Simulations showed that uncertainty for turbidity estimation associated with different particle types and bidirectional effects is typically less than 6%. When applied to field data from the five different sites, the semi-analytical algorithm performed well: turbidity estimates were within 12% and 22% of in situ values. A good performance was also found when the entire database was analyzed (n=106) with a mean relative error of 13.7% and bias of 4.8%. The good performance of the algorithm for all these regions, despite differences in sediment characteristics, and the results of the radiative transfer simulations suggest the global applicability of the algorithm to map turbidity up to 1000FNU. Consequently regional algorithms to retrieve SPM concentration from reflectance can be designed by combining this global algorithm to retrieve T from water reflectance with a regional relationship to convert T to SPM. This has the very practical advantage that the measurements needed to calibrate the latter T/SPM conversion for any new region are much easier and cheaper than in situ reflectance measurements.
•Generality of a single-band turbidity algorithm from water reflectance is analyzed•A sensitivity analysis and algorithm's uncertainties are calculated•A good performance of the algorithm in different regions using field data is found•Algorithm's global applicability to map turbidity between 1–1000FNU is suggested•Advantage of gl |
doi_str_mv | 10.1016/j.rse.2014.09.020 |
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•Generality of a single-band turbidity algorithm from water reflectance is analyzed•A sensitivity analysis and algorithm's uncertainties are calculated•A good performance of the algorithm in different regions using field data is found•Algorithm's global applicability to map turbidity between 1–1000FNU is suggested•Advantage of global T algorithm to estimate SPM is discussed</description><identifier>ISSN: 0034-4257</identifier><identifier>EISSN: 1879-0704</identifier><identifier>DOI: 10.1016/j.rse.2014.09.020</identifier><language>eng</language><publisher>Elsevier Inc</publisher><subject>Algorithms ; Brackish ; Coastal ; Computer simulation ; French Guyana ; Gironde ; Ocean, Atmosphere ; Radiative transfer ; Radiative transfer simulations ; Reflectance ; Reflectivity ; Río de la Plata ; Scheldt ; Sciences of the Universe ; Sediments ; Southern North Sea ; T algorithm validation ; Turbidity ; Turbidity (T) ; Uncertainty analysis ; Water reflectance</subject><ispartof>Remote sensing of environment, 2015-01, Vol.156, p.157-168</ispartof><rights>2014 The Authors</rights><rights>Attribution - NoDerivatives</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c548t-f004d9d8ec71cab85619b772294d4aa24ff963d4ffb8c614c562560d2dddd4903</citedby><cites>FETCH-LOGICAL-c548t-f004d9d8ec71cab85619b772294d4aa24ff963d4ffb8c614c562560d2dddd4903</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.rse.2014.09.020$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,780,784,885,3548,27923,27924,45994</link.rule.ids><backlink>$$Uhttps://insu.hal.science/insu-03190140$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Dogliotti, A.I.</creatorcontrib><creatorcontrib>Ruddick, K.G.</creatorcontrib><creatorcontrib>Nechad, B.</creatorcontrib><creatorcontrib>Doxaran, D.</creatorcontrib><creatorcontrib>Knaeps, E.</creatorcontrib><title>A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters</title><title>Remote sensing of environment</title><description>Ocean color remote sensing has been shown to be a useful tool to map turbidity (T) and suspended particulate matter (SPM) concentration in turbid coastal waters. Different algorithms to retrieve T and/or SPM from water reflectance already exist, however there are important questions as to whether these algorithms need to be calibrated specifically for different regions. In the present work the potential generality of a semi-empirical single band turbidity retrieval algorithm using the near infrared (NIR) band at 859nm in highly turbid waters is assessed. For completeness the use of 645nm in medium to low turbidity waters is also proposed. Radiative transfer simulations and in situ measurements from various European and South American coastal and shallow estuarine environments characterized by high concentrations of suspended sediments are analyzed. Reflectance and turbidity measurements were performed in the southern North Sea (SNS) and French Guyana (FG) coastal waters, and Scheldt (SC), Gironde (GIR) and Río de la Plata (RdP) estuaries. Simulations showed that uncertainty for turbidity estimation associated with different particle types and bidirectional effects is typically less than 6%. When applied to field data from the five different sites, the semi-analytical algorithm performed well: turbidity estimates were within 12% and 22% of in situ values. A good performance was also found when the entire database was analyzed (n=106) with a mean relative error of 13.7% and bias of 4.8%. The good performance of the algorithm for all these regions, despite differences in sediment characteristics, and the results of the radiative transfer simulations suggest the global applicability of the algorithm to map turbidity up to 1000FNU. Consequently regional algorithms to retrieve SPM concentration from reflectance can be designed by combining this global algorithm to retrieve T from water reflectance with a regional relationship to convert T to SPM. This has the very practical advantage that the measurements needed to calibrate the latter T/SPM conversion for any new region are much easier and cheaper than in situ reflectance measurements.
•Generality of a single-band turbidity algorithm from water reflectance is analyzed•A sensitivity analysis and algorithm's uncertainties are calculated•A good performance of the algorithm in different regions using field data is found•Algorithm's global applicability to map turbidity between 1–1000FNU is suggested•Advantage of global T algorithm to estimate SPM is discussed</description><subject>Algorithms</subject><subject>Brackish</subject><subject>Coastal</subject><subject>Computer simulation</subject><subject>French Guyana</subject><subject>Gironde</subject><subject>Ocean, Atmosphere</subject><subject>Radiative transfer</subject><subject>Radiative transfer simulations</subject><subject>Reflectance</subject><subject>Reflectivity</subject><subject>Río de la Plata</subject><subject>Scheldt</subject><subject>Sciences of the Universe</subject><subject>Sediments</subject><subject>Southern North Sea</subject><subject>T algorithm validation</subject><subject>Turbidity</subject><subject>Turbidity (T)</subject><subject>Uncertainty analysis</subject><subject>Water reflectance</subject><issn>0034-4257</issn><issn>1879-0704</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNqNkU9r3DAQxUVpoNs0HyA3HUvBzowt_xE9LaFtAgu9tGehlcaJFtlKJXnLfvto2dJj6VwGht8bHu8xdotQI2B_d6hjoroBFDXIGhp4wzY4DrKCAcRbtgFoRSWabnjH3qd0AMBuHHDDpi1PbnnyxLV_CtHl55nnwCPl6OhIPK9x76zLJz7FMJf7HDL5U5VoSWS51VlztxSx5ybolLXnerGcUl51dAvx3zpTTB_Y1aR9ops_-5r9_Prlx_1Dtfv-7fF-u6tMJ8ZcTQDCSjuSGdDo_dj1KPfD0DRSWKF1I6ZJ9q0taz-aHoXp-qbrwTa2jJDQXrNPl7_P2quX6GYdTypopx62O-WWtCpoUZaU4IgF_niBX2L4tRbLanbJkPd6obAmhX0PMLYC2v9AxQDQIZ4t4AU1MaQUafrrA0Gdu1IHVbpS564USFW6KprPFw2VbI6OokrG0WLIukgmKxvcP9Sv2QGchw</recordid><startdate>201501</startdate><enddate>201501</enddate><creator>Dogliotti, A.I.</creator><creator>Ruddick, K.G.</creator><creator>Nechad, B.</creator><creator>Doxaran, D.</creator><creator>Knaeps, E.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SN</scope><scope>7ST</scope><scope>7TG</scope><scope>7TN</scope><scope>7TV</scope><scope>C1K</scope><scope>F1W</scope><scope>H96</scope><scope>KL.</scope><scope>L.G</scope><scope>SOI</scope><scope>7SU</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope><scope>1XC</scope><scope>VOOES</scope></search><sort><creationdate>201501</creationdate><title>A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters</title><author>Dogliotti, A.I. ; Ruddick, K.G. ; Nechad, B. ; Doxaran, D. ; Knaeps, E.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c548t-f004d9d8ec71cab85619b772294d4aa24ff963d4ffb8c614c562560d2dddd4903</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Algorithms</topic><topic>Brackish</topic><topic>Coastal</topic><topic>Computer simulation</topic><topic>French Guyana</topic><topic>Gironde</topic><topic>Ocean, Atmosphere</topic><topic>Radiative transfer</topic><topic>Radiative transfer simulations</topic><topic>Reflectance</topic><topic>Reflectivity</topic><topic>Río de la Plata</topic><topic>Scheldt</topic><topic>Sciences of the Universe</topic><topic>Sediments</topic><topic>Southern North Sea</topic><topic>T algorithm validation</topic><topic>Turbidity</topic><topic>Turbidity (T)</topic><topic>Uncertainty analysis</topic><topic>Water reflectance</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Dogliotti, A.I.</creatorcontrib><creatorcontrib>Ruddick, K.G.</creatorcontrib><creatorcontrib>Nechad, B.</creatorcontrib><creatorcontrib>Doxaran, D.</creatorcontrib><creatorcontrib>Knaeps, E.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>CrossRef</collection><collection>Ecology Abstracts</collection><collection>Environment Abstracts</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Oceanic Abstracts</collection><collection>Pollution Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ASFA: Aquatic Sciences and Fisheries Abstracts</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) 2: Ocean Technology, Policy & Non-Living Resources</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Aquatic Science & Fisheries Abstracts (ASFA) Professional</collection><collection>Environment Abstracts</collection><collection>Environmental Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>Hyper Article en Ligne (HAL) (Open Access)</collection><jtitle>Remote sensing of environment</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Dogliotti, A.I.</au><au>Ruddick, K.G.</au><au>Nechad, B.</au><au>Doxaran, D.</au><au>Knaeps, E.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters</atitle><jtitle>Remote sensing of environment</jtitle><date>2015-01</date><risdate>2015</risdate><volume>156</volume><spage>157</spage><epage>168</epage><pages>157-168</pages><issn>0034-4257</issn><eissn>1879-0704</eissn><abstract>Ocean color remote sensing has been shown to be a useful tool to map turbidity (T) and suspended particulate matter (SPM) concentration in turbid coastal waters. Different algorithms to retrieve T and/or SPM from water reflectance already exist, however there are important questions as to whether these algorithms need to be calibrated specifically for different regions. In the present work the potential generality of a semi-empirical single band turbidity retrieval algorithm using the near infrared (NIR) band at 859nm in highly turbid waters is assessed. For completeness the use of 645nm in medium to low turbidity waters is also proposed. Radiative transfer simulations and in situ measurements from various European and South American coastal and shallow estuarine environments characterized by high concentrations of suspended sediments are analyzed. Reflectance and turbidity measurements were performed in the southern North Sea (SNS) and French Guyana (FG) coastal waters, and Scheldt (SC), Gironde (GIR) and Río de la Plata (RdP) estuaries. Simulations showed that uncertainty for turbidity estimation associated with different particle types and bidirectional effects is typically less than 6%. When applied to field data from the five different sites, the semi-analytical algorithm performed well: turbidity estimates were within 12% and 22% of in situ values. A good performance was also found when the entire database was analyzed (n=106) with a mean relative error of 13.7% and bias of 4.8%. The good performance of the algorithm for all these regions, despite differences in sediment characteristics, and the results of the radiative transfer simulations suggest the global applicability of the algorithm to map turbidity up to 1000FNU. Consequently regional algorithms to retrieve SPM concentration from reflectance can be designed by combining this global algorithm to retrieve T from water reflectance with a regional relationship to convert T to SPM. This has the very practical advantage that the measurements needed to calibrate the latter T/SPM conversion for any new region are much easier and cheaper than in situ reflectance measurements.
•Generality of a single-band turbidity algorithm from water reflectance is analyzed•A sensitivity analysis and algorithm's uncertainties are calculated•A good performance of the algorithm in different regions using field data is found•Algorithm's global applicability to map turbidity between 1–1000FNU is suggested•Advantage of global T algorithm to estimate SPM is discussed</abstract><pub>Elsevier Inc</pub><doi>10.1016/j.rse.2014.09.020</doi><tpages>12</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Brackish Coastal Computer simulation French Guyana Gironde Ocean, Atmosphere Radiative transfer Radiative transfer simulations Reflectance Reflectivity Río de la Plata Scheldt Sciences of the Universe Sediments Southern North Sea T algorithm validation Turbidity Turbidity (T) Uncertainty analysis Water reflectance |
title | A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters |
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