A 10-year survey of trace metals in sediments using self-organizing maps

Self-organizing maps (SOMs) (in particular, Matrix reOrganization Layout to Map Analytical Patterns (MOLMAP)) were used to unravel the main patterns in a three-way dataset after a preliminary unfolding of the cube. Eleven sites of the ría of Vigo (NW of Spain) were monitored during the last decade (...

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Detalles Bibliográficos
Autores: Besada, Victoria, Quelle, Cristina, Andrade, José Manuel, Gutiérrez, Noemí, Gómez-Carracedo, María Paz, Schultze, Fernando
Tipo de recurso: artículo
Fecha de publicación:2014
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/321655
Acceso en línea:http://hdl.handle.net/10261/321655
Access Level:acceso abierto
Palabra clave:Medio Marino
Self-organizing maps
Centro Oceanográfico de Vigo
Three-way unfolding
Three-way unsupervised pattern recognition
Trace metals
Sediments
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spelling A 10-year survey of trace metals in sediments using self-organizing mapsBesada, VictoriaQuelle, CristinaAndrade, José ManuelGutiérrez, NoemíGómez-Carracedo, María PazSchultze, FernandoMedio MarinoSelf-organizing mapsCentro Oceanográfico de VigoThree-way unfoldingThree-way unsupervised pattern recognitionTrace metalsSedimentsSelf-organizing maps (SOMs) (in particular, Matrix reOrganization Layout to Map Analytical Patterns (MOLMAP)) were used to unravel the main patterns in a three-way dataset after a preliminary unfolding of the cube. Eleven sites of the ría of Vigo (NW of Spain) were monitored during the last decade (from 2000 to 2010) to assess pollution trends in this area. Twelve trace metals (Hg, Pb, Cd, Cu, Zn, Cr, As, Li, Fe, Al, Ni and Mn), the total organic carbon and the percentage of fine particles were measured. Results from MOLMAP, the SOM-based approach, were compared to those of three established alternatives: parallel factor analysis, matrix-augmented principal component analysis and generalized Procrustes rotation, the latter two employing unfolding as well. MOLMAP showed the best capabilities to differentiate groups of samples. The spatial and temporal trends, as well as the analytical variables causing them, were almost the same for all methods, which confirms MOLMAP as a simple and reliable methodology to treat three-way environmental datasets202320232014info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501http://hdl.handle.net/10261/321655reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésCentro Oceanográfico de Vigohttp://onlinelibrary.wiley.com/doi/10.1002/cem.2615/abstractinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/3216552026-05-22T06:33:51Z
dc.title.none.fl_str_mv A 10-year survey of trace metals in sediments using self-organizing maps
title A 10-year survey of trace metals in sediments using self-organizing maps
spellingShingle A 10-year survey of trace metals in sediments using self-organizing maps
Besada, Victoria
Medio Marino
Self-organizing maps
Centro Oceanográfico de Vigo
Three-way unfolding
Three-way unsupervised pattern recognition
Trace metals
Sediments
title_short A 10-year survey of trace metals in sediments using self-organizing maps
title_full A 10-year survey of trace metals in sediments using self-organizing maps
title_fullStr A 10-year survey of trace metals in sediments using self-organizing maps
title_full_unstemmed A 10-year survey of trace metals in sediments using self-organizing maps
title_sort A 10-year survey of trace metals in sediments using self-organizing maps
dc.creator.none.fl_str_mv Besada, Victoria
Quelle, Cristina
Andrade, José Manuel
Gutiérrez, Noemí
Gómez-Carracedo, María Paz
Schultze, Fernando
author Besada, Victoria
author_facet Besada, Victoria
Quelle, Cristina
Andrade, José Manuel
Gutiérrez, Noemí
Gómez-Carracedo, María Paz
Schultze, Fernando
author_role author
author2 Quelle, Cristina
Andrade, José Manuel
Gutiérrez, Noemí
Gómez-Carracedo, María Paz
Schultze, Fernando
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Medio Marino
Self-organizing maps
Centro Oceanográfico de Vigo
Three-way unfolding
Three-way unsupervised pattern recognition
Trace metals
Sediments
topic Medio Marino
Self-organizing maps
Centro Oceanográfico de Vigo
Three-way unfolding
Three-way unsupervised pattern recognition
Trace metals
Sediments
description Self-organizing maps (SOMs) (in particular, Matrix reOrganization Layout to Map Analytical Patterns (MOLMAP)) were used to unravel the main patterns in a three-way dataset after a preliminary unfolding of the cube. Eleven sites of the ría of Vigo (NW of Spain) were monitored during the last decade (from 2000 to 2010) to assess pollution trends in this area. Twelve trace metals (Hg, Pb, Cd, Cu, Zn, Cr, As, Li, Fe, Al, Ni and Mn), the total organic carbon and the percentage of fine particles were measured. Results from MOLMAP, the SOM-based approach, were compared to those of three established alternatives: parallel factor analysis, matrix-augmented principal component analysis and generalized Procrustes rotation, the latter two employing unfolding as well. MOLMAP showed the best capabilities to differentiate groups of samples. The spatial and temporal trends, as well as the analytical variables causing them, were almost the same for all methods, which confirms MOLMAP as a simple and reliable methodology to treat three-way environmental datasets
publishDate 2014
dc.date.none.fl_str_mv 2014
2023
2023
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
format article
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/321655
url http://hdl.handle.net/10261/321655
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Centro Oceanográfico de Vigo
http://onlinelibrary.wiley.com/doi/10.1002/cem.2615/abstract
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,81155

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