A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters

Autores
Dogliotti, Ana Inés; Ruddick, K. G.; Nechad, B.; Doxaran, D.; Knaeps, E.
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
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 859 nm in highly turbid waters is assessed. For completeness the use of 645 nm 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 1000 FNU. 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.
Fil: Dogliotti, Ana Inés. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Ruddick, K. G.. Royal Belgian Institute For Natural Sciences ; Bélgica
Fil: Nechad, B.. Royal Belgian Institute For Natural Sciences ; Bélgica
Fil: Doxaran, D.. Laboratoire D; Francia
Fil: Knaeps, E.. Flemish Institute For Technological Research; Bélgica
Materia
Turbidity (T)
Water Reflectance
Radiative Transfer Simulations
Uncertainty Analysis
T Algorithm Validation
Southern North Sea
Scheldt
Gironde
Río de La Plata
French Guyana
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/16701

id CONICETDig_88c3b05aa824e9014295c9857e374732
oai_identifier_str oai:ri.conicet.gov.ar:11336/16701
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine watersDogliotti, Ana InésRuddick, K. G.Nechad, B.Doxaran, D.Knaeps, E.Turbidity (T)Water ReflectanceRadiative Transfer SimulationsUncertainty AnalysisT Algorithm ValidationSouthern North SeaScheldtGirondeRío de La PlataFrench Guyanahttps://purl.org/becyt/ford/1.5https://purl.org/becyt/ford/1Ocean 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 859 nm in highly turbid waters is assessed. For completeness the use of 645 nm 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 1000 FNU. 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.Fil: Dogliotti, Ana Inés. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; ArgentinaFil: Ruddick, K. G.. Royal Belgian Institute For Natural Sciences ; BélgicaFil: Nechad, B.. Royal Belgian Institute For Natural Sciences ; BélgicaFil: Doxaran, D.. Laboratoire D; FranciaFil: Knaeps, E.. Flemish Institute For Technological Research; BélgicaElsevier Science Inc2015-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/16701Dogliotti, Ana Inés; Ruddick, K. G.; Nechad, B.; Doxaran, D.; Knaeps, E.; A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters; Elsevier Science Inc; Remote Sensing Of Environment; 156; 1-2015; 157-1680034-4257enginfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0034425714003654info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2014.09.020info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T10:23:21Zoai:ri.conicet.gov.ar:11336/16701instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-09-29 10:23:21.301CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
title A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
spellingShingle A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
Dogliotti, Ana Inés
Turbidity (T)
Water Reflectance
Radiative Transfer Simulations
Uncertainty Analysis
T Algorithm Validation
Southern North Sea
Scheldt
Gironde
Río de La Plata
French Guyana
title_short A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
title_full A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
title_fullStr A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
title_full_unstemmed A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
title_sort A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters
dc.creator.none.fl_str_mv Dogliotti, Ana Inés
Ruddick, K. G.
Nechad, B.
Doxaran, D.
Knaeps, E.
author Dogliotti, Ana Inés
author_facet Dogliotti, Ana Inés
Ruddick, K. G.
Nechad, B.
Doxaran, D.
Knaeps, E.
author_role author
author2 Ruddick, K. G.
Nechad, B.
Doxaran, D.
Knaeps, E.
author2_role author
author
author
author
dc.subject.none.fl_str_mv Turbidity (T)
Water Reflectance
Radiative Transfer Simulations
Uncertainty Analysis
T Algorithm Validation
Southern North Sea
Scheldt
Gironde
Río de La Plata
French Guyana
topic Turbidity (T)
Water Reflectance
Radiative Transfer Simulations
Uncertainty Analysis
T Algorithm Validation
Southern North Sea
Scheldt
Gironde
Río de La Plata
French Guyana
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.5
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv 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 859 nm in highly turbid waters is assessed. For completeness the use of 645 nm 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 1000 FNU. 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.
Fil: Dogliotti, Ana Inés. Consejo Nacional de Investigaciónes Científicas y Técnicas. Oficina de Coordinación Administrativa Ciudad Universitaria. Instituto de Astronomía y Física del Espacio. - Universidad de Buenos Aires. Facultad de Ciencias Exactas y Naturales. Instituto de Astronomía y Física del Espacio; Argentina
Fil: Ruddick, K. G.. Royal Belgian Institute For Natural Sciences ; Bélgica
Fil: Nechad, B.. Royal Belgian Institute For Natural Sciences ; Bélgica
Fil: Doxaran, D.. Laboratoire D; Francia
Fil: Knaeps, E.. Flemish Institute For Technological Research; Bélgica
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 859 nm in highly turbid waters is assessed. For completeness the use of 645 nm 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 1000 FNU. 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.
publishDate 2015
dc.date.none.fl_str_mv 2015-01
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/16701
Dogliotti, Ana Inés; Ruddick, K. G.; Nechad, B.; Doxaran, D.; Knaeps, E.; A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters; Elsevier Science Inc; Remote Sensing Of Environment; 156; 1-2015; 157-168
0034-4257
url http://hdl.handle.net/11336/16701
identifier_str_mv Dogliotti, Ana Inés; Ruddick, K. G.; Nechad, B.; Doxaran, D.; Knaeps, E.; A single algorithm to retrieve turbidity from remotely-sensed data in all coastal and estuarine waters; Elsevier Science Inc; Remote Sensing Of Environment; 156; 1-2015; 157-168
0034-4257
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0034425714003654
info:eu-repo/semantics/altIdentifier/doi/10.1016/j.rse.2014.09.020
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
dc.publisher.none.fl_str_mv Elsevier Science Inc
publisher.none.fl_str_mv Elsevier Science Inc
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
_version_ 1844614228206419968
score 13.070432