Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/36778 |
Resumo: | The validity and usefulness of multivariate statistical tools for the facies characterization in deep-marine environments have been applied on the geochemical, sedimentological and magnetic data from a piston core extracted from the Transitional Zone in the Galician Continental Margin. The combination of geochemical profiles of Fe, Mn, Ti, Ba and Ca and magnetic susceptibility (MS) obtained using the ItraxTM Core Scanner at the University of Vigo, together with the grain-size, grey level and R (red) G (green) B (blue) colour analyses have allowed characterizing and classifying the sediments of the core PC13-3 using SPSS package v. 23. Cluster Analysis (CA) displays, in the first level of the hierarchy, two major groups that correspond with clay-silt and sand facies. In a second level, it is possible to observe six subfacies that match de visu preliminary classification and allowed us to complete and improve the characterization and the facies limits in the whole core. Discriminant Analysis (DA) confirmed the validity of the cluster analyses and enhanced the results of the classification. The Principal Component Analysis (PCA) shows four principal components: coarse lithogenic fraction (PC1), fine lithogenic fraction (PC2), high density fraction (PC3) and biogenic fraction (PC4). These results are in concordance with the Pearson correlation coefficient and the SEM observations. In general terms, the results confirm the utility of the multivariate statistical methods applied on high resolution geochemical and magnetic data acquired with ItraxTM corer scanner, as a quick and complementary tool in sedimentary facies analysis and description in deep marine environments. |
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Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental MarginGalicia continental marginSedimentologyFacies analysisMultivariate statistical analysisItraxTM core scannerThe validity and usefulness of multivariate statistical tools for the facies characterization in deep-marine environments have been applied on the geochemical, sedimentological and magnetic data from a piston core extracted from the Transitional Zone in the Galician Continental Margin. The combination of geochemical profiles of Fe, Mn, Ti, Ba and Ca and magnetic susceptibility (MS) obtained using the ItraxTM Core Scanner at the University of Vigo, together with the grain-size, grey level and R (red) G (green) B (blue) colour analyses have allowed characterizing and classifying the sediments of the core PC13-3 using SPSS package v. 23. Cluster Analysis (CA) displays, in the first level of the hierarchy, two major groups that correspond with clay-silt and sand facies. In a second level, it is possible to observe six subfacies that match de visu preliminary classification and allowed us to complete and improve the characterization and the facies limits in the whole core. Discriminant Analysis (DA) confirmed the validity of the cluster analyses and enhanced the results of the classification. The Principal Component Analysis (PCA) shows four principal components: coarse lithogenic fraction (PC1), fine lithogenic fraction (PC2), high density fraction (PC3) and biogenic fraction (PC4). These results are in concordance with the Pearson correlation coefficient and the SEM observations. In general terms, the results confirm the utility of the multivariate statistical methods applied on high resolution geochemical and magnetic data acquired with ItraxTM corer scanner, as a quick and complementary tool in sedimentary facies analysis and description in deep marine environments.Elsevier2023-03-31T14:31:18Z2019-04-30T00:00:00Z2019-04-30info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/36778eng1040-618210.1016/j.quaint.2018.06.035López Pérez, A.E.Rey, D.Martins, VirgíniaPlaza-Morlote, M.Rubio, B.info: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:RCAAP2024-02-22T12:10:53Zoai:ria.ua.pt:10773/36778Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:07:28.815560Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
title |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
spellingShingle |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin López Pérez, A.E. Galicia continental margin Sedimentology Facies analysis Multivariate statistical analysis ItraxTM core scanner |
title_short |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
title_full |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
title_fullStr |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
title_full_unstemmed |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
title_sort |
Application of multivariate statistical analyses to Itrax core scanner data for the identification of deep-marine sedimentary facies: a case study in the Galician Continental Margin |
author |
López Pérez, A.E. |
author_facet |
López Pérez, A.E. Rey, D. Martins, Virgínia Plaza-Morlote, M. Rubio, B. |
author_role |
author |
author2 |
Rey, D. Martins, Virgínia Plaza-Morlote, M. Rubio, B. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
López Pérez, A.E. Rey, D. Martins, Virgínia Plaza-Morlote, M. Rubio, B. |
dc.subject.por.fl_str_mv |
Galicia continental margin Sedimentology Facies analysis Multivariate statistical analysis ItraxTM core scanner |
topic |
Galicia continental margin Sedimentology Facies analysis Multivariate statistical analysis ItraxTM core scanner |
description |
The validity and usefulness of multivariate statistical tools for the facies characterization in deep-marine environments have been applied on the geochemical, sedimentological and magnetic data from a piston core extracted from the Transitional Zone in the Galician Continental Margin. The combination of geochemical profiles of Fe, Mn, Ti, Ba and Ca and magnetic susceptibility (MS) obtained using the ItraxTM Core Scanner at the University of Vigo, together with the grain-size, grey level and R (red) G (green) B (blue) colour analyses have allowed characterizing and classifying the sediments of the core PC13-3 using SPSS package v. 23. Cluster Analysis (CA) displays, in the first level of the hierarchy, two major groups that correspond with clay-silt and sand facies. In a second level, it is possible to observe six subfacies that match de visu preliminary classification and allowed us to complete and improve the characterization and the facies limits in the whole core. Discriminant Analysis (DA) confirmed the validity of the cluster analyses and enhanced the results of the classification. The Principal Component Analysis (PCA) shows four principal components: coarse lithogenic fraction (PC1), fine lithogenic fraction (PC2), high density fraction (PC3) and biogenic fraction (PC4). These results are in concordance with the Pearson correlation coefficient and the SEM observations. In general terms, the results confirm the utility of the multivariate statistical methods applied on high resolution geochemical and magnetic data acquired with ItraxTM corer scanner, as a quick and complementary tool in sedimentary facies analysis and description in deep marine environments. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-04-30T00:00:00Z 2019-04-30 2023-03-31T14:31:18Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10773/36778 |
url |
http://hdl.handle.net/10773/36778 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1040-6182 10.1016/j.quaint.2018.06.035 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
publisher.none.fl_str_mv |
Elsevier |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
instname_str |
Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137729856929792 |