How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)

Macroalgae have attracted the interest of remote sensing as targets to study coastal marine ecosystems because of their key ecological role. The goal of this paper is to analyze a new spectral library, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use in hyperspe...

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Detalhes bibliográficos
Autores: Olmedo Masat, Olga Magalí, Raffo, María Paula, Rodríguez Pérez, Daniel, Arijón, Marianela, Sánchez Carnero, Noela
Tipo de documento: artigo
Data de publicação:2020
País:España
Recursos:Universidad Nacional de Educación a Distancia
Repositório:e-spacio. Repositorio Institucional de la UNED
Idioma:inglês
OAI Identifier:oai:e-spacio.uned.es:20.500.14468/31101
Acesso em linha:https://hdl.handle.net/20.500.14468/31101
Access Level:Acceso aberto
Palavra-chave:2417.05 Biología marina
Coastal macroalgae
Spectral features
Hyperspectral sensors
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spelling How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)Olmedo Masat, Olga MagalíRaffo, María PaulaRodríguez Pérez, DanielArijón, MarianelaSánchez Carnero, Noela2417.05 Biología marinaCoastal macroalgaeSpectral featuresHyperspectral sensorsMacroalgae have attracted the interest of remote sensing as targets to study coastal marine ecosystems because of their key ecological role. The goal of this paper is to analyze a new spectral library, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use in hyperspectral remote sensing. The library includes species collected in the Atlantic Patagonian coast (Argentina) with representatives of brown, red, and green algae, being 22 of the species included in a spectral library for the first time. The spectra of these main groups are described, and the intraspecific variability is also assessed, considering kelp differentiated tissues and depth range, discussing them from the point of view of their effects on spectral features. A classification and an independent component analysis using the spectral range and simulated bands of two state-of-the-art drone-borne hyperspectral sensors were performed. The results show spectral features and clusters identifying further algae taxonomic groups, showing the potential applications of this spectral library for drone-based mapping of this ecological and economical asset of our coastal marine ecosystems.MDPIe-Spacio UNED20252025-12-1120202020-11-2620202020-11-26journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/20.500.14468/31101reponame:e-spacio. Repositorio Institucional de la UNEDinstname:Universidad Nacional de Educación a DistanciaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2info:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/4.0/deed.esoai:e-spacio.uned.es:20.500.14468/311012026-06-06T12:38:31Z
dc.title.none.fl_str_mv How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
title How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
spellingShingle How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
Olmedo Masat, Olga Magalí
2417.05 Biología marina
Coastal macroalgae
Spectral features
Hyperspectral sensors
title_short How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
title_full How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
title_fullStr How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
title_full_unstemmed How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
title_sort How Far Can We Classify Macroalgae Remotely? An Example Using a New Spectral Library of Species from the South West Atlantic (Argentine Patagonia)
dc.creator.none.fl_str_mv Olmedo Masat, Olga Magalí
Raffo, María Paula
Rodríguez Pérez, Daniel
Arijón, Marianela
Sánchez Carnero, Noela
author Olmedo Masat, Olga Magalí
author_facet Olmedo Masat, Olga Magalí
Raffo, María Paula
Rodríguez Pérez, Daniel
Arijón, Marianela
Sánchez Carnero, Noela
author_role author
author2 Raffo, María Paula
Rodríguez Pérez, Daniel
Arijón, Marianela
Sánchez Carnero, Noela
author2_role author
author
author
author
dc.contributor.none.fl_str_mv e-Spacio UNED
dc.subject.none.fl_str_mv 2417.05 Biología marina
Coastal macroalgae
Spectral features
Hyperspectral sensors
topic 2417.05 Biología marina
Coastal macroalgae
Spectral features
Hyperspectral sensors
description Macroalgae have attracted the interest of remote sensing as targets to study coastal marine ecosystems because of their key ecological role. The goal of this paper is to analyze a new spectral library, including 28 macroalgae from the South-West Atlantic coast, in order to assess its use in hyperspectral remote sensing. The library includes species collected in the Atlantic Patagonian coast (Argentina) with representatives of brown, red, and green algae, being 22 of the species included in a spectral library for the first time. The spectra of these main groups are described, and the intraspecific variability is also assessed, considering kelp differentiated tissues and depth range, discussing them from the point of view of their effects on spectral features. A classification and an independent component analysis using the spectral range and simulated bands of two state-of-the-art drone-borne hyperspectral sensors were performed. The results show spectral features and clusters identifying further algae taxonomic groups, showing the potential applications of this spectral library for drone-based mapping of this ecological and economical asset of our coastal marine ecosystems.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-11-26
2020
2020-11-26
2025
2025-12-11
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/20.500.14468/31101
url https://hdl.handle.net/20.500.14468/31101
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
info:eu-repo/semantics/openAccess
http://creativecommons.org/licenses/by/4.0/deed.es
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
http://creativecommons.org/licenses/by/4.0/deed.es
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv MDPI
publisher.none.fl_str_mv MDPI
dc.source.none.fl_str_mv reponame:e-spacio. Repositorio Institucional de la UNED
instname:Universidad Nacional de Educación a Distancia
instname_str Universidad Nacional de Educación a Distancia
reponame_str e-spacio. Repositorio Institucional de la UNED
collection e-spacio. Repositorio Institucional de la UNED
repository.name.fl_str_mv
repository.mail.fl_str_mv
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