Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters

Detalhes bibliográficos
Autor(a) principal: Pacheco, André
Data de Publicação: 2015
Outros Autores: Horta, João, Loureiro, Carlos, Ferreira, Oscar
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10400.1/12311
Resumo: Nearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the nearshore is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques is a topic of increasing interest in coastalmonitoring and research. This contribution focuses on the application of the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa, Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques (e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry frommulti-spectral satellite data for shallowwater depths (0 to 12 m), showing amean bias of−0.2m, a median difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use of freely available satellite imagery proved to be a quick and reliable method for acquiring updated mediumresolution, high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged beach and the shoreface.
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spelling Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow watersSatellite-derived bathymetryRia FormosaLandsatLiDARLinear transform algorithmCoastal monitoringNearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the nearshore is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques is a topic of increasing interest in coastalmonitoring and research. This contribution focuses on the application of the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa, Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques (e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry frommulti-spectral satellite data for shallowwater depths (0 to 12 m), showing amean bias of−0.2m, a median difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use of freely available satellite imagery proved to be a quick and reliable method for acquiring updated mediumresolution, high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged beach and the shoreface.ElsevierSapientiaPacheco, AndréHorta, JoãoLoureiro, CarlosFerreira, Oscar2019-01-30T12:28:19Z20152015-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.1/12311eng10.1016/j.rse.2014.12.004info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-24T10:24:16ZPortal AgregadorONG
dc.title.none.fl_str_mv Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
title Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
spellingShingle Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
Pacheco, André
Satellite-derived bathymetry
Ria Formosa
Landsat
LiDAR
Linear transform algorithm
Coastal monitoring
title_short Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
title_full Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
title_fullStr Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
title_full_unstemmed Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
title_sort Retrieval of nearshore bathymetry from Landsat 8 images: a tool for coastal monitoring in shallow waters
author Pacheco, André
author_facet Pacheco, André
Horta, João
Loureiro, Carlos
Ferreira, Oscar
author_role author
author2 Horta, João
Loureiro, Carlos
Ferreira, Oscar
author2_role author
author
author
dc.contributor.none.fl_str_mv Sapientia
dc.contributor.author.fl_str_mv Pacheco, André
Horta, João
Loureiro, Carlos
Ferreira, Oscar
dc.subject.por.fl_str_mv Satellite-derived bathymetry
Ria Formosa
Landsat
LiDAR
Linear transform algorithm
Coastal monitoring
topic Satellite-derived bathymetry
Ria Formosa
Landsat
LiDAR
Linear transform algorithm
Coastal monitoring
description Nearshore bathymetry is likely to be the coastal variable that most limits the investigation of coastal processes and the accuracy of numerical models in coastal areas, as acquiring medium spatial resolution data in the nearshore is highly demanding and costly. As such, the ability to derive bathymetry using remote sensing techniques is a topic of increasing interest in coastalmonitoring and research. This contribution focuses on the application of the linear transform algorithm to obtain satellite-derived bathymetry (SDB) maps of the nearshore, at medium resolution (30 m), from freely available and easily accessible Landsat 8 imagery. The algorithm was tuned with available bathymetric Light Detection and Ranging (LiDAR) data for a 60-km-long nearshore stretch of a highly complex coastal system that includes barrier islands, exposed sandy beaches, and tidal inlets (Ria Formosa, Portugal). A comparison of the retrieved depths is presented, enabling the configuration of nearshore profiles and extracted isobaths to be explored and compared with traditional topographic/bathymetric techniques (e.g., high- and medium-resolution LiDAR data and survey-grade echo-sounding combined with high-precision positioning systems). The results demonstrate that the linear algorithm is efficient for retrieving bathymetry frommulti-spectral satellite data for shallowwater depths (0 to 12 m), showing amean bias of−0.2m, a median difference of −0.1 m, and a root mean square error of 0.89 m. Accuracy is shown to be depth dependent, an inherent limitation of passive optical detection systems. Accuracy further decreases in areas where turbidity is likely to be higher, such as locations adjacent to tidal inlets. The SDB maps provide reliable estimations of the shoreline position and of nearshore isobaths for different cases along the complex coastline analysed. The use of freely available satellite imagery proved to be a quick and reliable method for acquiring updated mediumresolution, high-frequency (days and weeks), low-cost bathymetric information for large areas and depths of up to 12 m in clear waters without wave breaking, allowing almost constant monitoring of the submerged beach and the shoreface.
publishDate 2015
dc.date.none.fl_str_mv 2015
2015-01-01T00:00:00Z
2019-01-30T12:28:19Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
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status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.1/12311
url http://hdl.handle.net/10400.1/12311
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1016/j.rse.2014.12.004
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
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instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
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