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
- Institución
- Consejo Nacional de Investigaciones Científicas y Técnicas
- OAI Identificador
- oai:ri.conicet.gov.ar:11336/16701
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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 |
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1844614228206419968 |
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13.070432 |