Procrustes analysis as a tool for land management

Autores
Matteucci, Silvia Diana; Pla, Laura
Año de publicación
2010
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Generalized Procrustes analysis (GPA) is a multivariate technique that involves transformations of data matrices to provide optimal comparability. We propose GPA to quantify the concordance among sets of variables that characterize natural, human and productive subsystems. When the land use fits in with the physical support of agricultural production, people’s well-being should be evident in a high concordance between the land use and the social conditions. In a situation of instability each set of variables operates in diverse directions resulting in lower resilience and sustainability. Two GPA were performed, between physical support and land use data sets (concordance = 67.4%), and between land use and social conditions data sets (concordance = 65.3%). The interplay between the pair of concordance values constitutes a bi-dimensional index which serves as an ecological indicator. Based on bootstrap confidence interval, the 49 counties of the Pampa Ecoregion, Argentina, were classified in medium, high or low concordance. The lack of concordance is an indicator of imbalances which may contribute to guide environmental management.
Fil: Matteucci, Silvia Diana. Universidad de Buenos Aires. Facultad de Arquitectura y Urbanismo. Grupo de Ecología del Paisaje y Medio Ambiente; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pla, Laura. Universidad Nacional Experimental Francisco de Miranda; Venezuela
Materia
Ecologica Indicator
Matrix Concordance Space
Environmental Policy
Land Use
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-nd/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/16362
Acceder
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oai_identifier_str oai:ri.conicet.gov.ar:11336/16362
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Procrustes analysis as a tool for land managementMatteucci, Silvia DianaPla, LauraEcologica IndicatorMatrix Concordance SpaceEnvironmental PolicyLand Usehttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Generalized Procrustes analysis (GPA) is a multivariate technique that involves transformations of data matrices to provide optimal comparability. We propose GPA to quantify the concordance among sets of variables that characterize natural, human and productive subsystems. When the land use fits in with the physical support of agricultural production, people’s well-being should be evident in a high concordance between the land use and the social conditions. In a situation of instability each set of variables operates in diverse directions resulting in lower resilience and sustainability. Two GPA were performed, between physical support and land use data sets (concordance = 67.4%), and between land use and social conditions data sets (concordance = 65.3%). The interplay between the pair of concordance values constitutes a bi-dimensional index which serves as an ecological indicator. Based on bootstrap confidence interval, the 49 counties of the Pampa Ecoregion, Argentina, were classified in medium, high or low concordance. The lack of concordance is an indicator of imbalances which may contribute to guide environmental management.Fil: Matteucci, Silvia Diana. Universidad de Buenos Aires. Facultad de Arquitectura y Urbanismo. Grupo de Ecología del Paisaje y Medio Ambiente; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Pla, Laura. Universidad Nacional Experimental Francisco de Miranda; VenezuelaElsevier Science2010-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/16362Matteucci, Silvia Diana; Pla, Laura; Procrustes analysis as a tool for land management; Elsevier Science; Ecological Indicators; 10; 2; 3-2010; 516-5261470-160Xenginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2009.09.005info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1470160X09001538info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-09-29T09:58:12Zoai:ri.conicet.gov.ar:11336/16362instacron: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 09:58:12.62CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Procrustes analysis as a tool for land management
title Procrustes analysis as a tool for land management
spellingShingle Procrustes analysis as a tool for land management
Matteucci, Silvia Diana
Ecologica Indicator
Matrix Concordance Space
Environmental Policy
Land Use
title_short Procrustes analysis as a tool for land management
title_full Procrustes analysis as a tool for land management
title_fullStr Procrustes analysis as a tool for land management
title_full_unstemmed Procrustes analysis as a tool for land management
title_sort Procrustes analysis as a tool for land management
dc.creator.none.fl_str_mv Matteucci, Silvia Diana
Pla, Laura
author Matteucci, Silvia Diana
author_facet Matteucci, Silvia Diana
Pla, Laura
author_role author
author2 Pla, Laura
author2_role author
dc.subject.none.fl_str_mv Ecologica Indicator
Matrix Concordance Space
Environmental Policy
Land Use
topic Ecologica Indicator
Matrix Concordance Space
Environmental Policy
Land Use
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Generalized Procrustes analysis (GPA) is a multivariate technique that involves transformations of data matrices to provide optimal comparability. We propose GPA to quantify the concordance among sets of variables that characterize natural, human and productive subsystems. When the land use fits in with the physical support of agricultural production, people’s well-being should be evident in a high concordance between the land use and the social conditions. In a situation of instability each set of variables operates in diverse directions resulting in lower resilience and sustainability. Two GPA were performed, between physical support and land use data sets (concordance = 67.4%), and between land use and social conditions data sets (concordance = 65.3%). The interplay between the pair of concordance values constitutes a bi-dimensional index which serves as an ecological indicator. Based on bootstrap confidence interval, the 49 counties of the Pampa Ecoregion, Argentina, were classified in medium, high or low concordance. The lack of concordance is an indicator of imbalances which may contribute to guide environmental management.
Fil: Matteucci, Silvia Diana. Universidad de Buenos Aires. Facultad de Arquitectura y Urbanismo. Grupo de Ecología del Paisaje y Medio Ambiente; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Pla, Laura. Universidad Nacional Experimental Francisco de Miranda; Venezuela
description Generalized Procrustes analysis (GPA) is a multivariate technique that involves transformations of data matrices to provide optimal comparability. We propose GPA to quantify the concordance among sets of variables that characterize natural, human and productive subsystems. When the land use fits in with the physical support of agricultural production, people’s well-being should be evident in a high concordance between the land use and the social conditions. In a situation of instability each set of variables operates in diverse directions resulting in lower resilience and sustainability. Two GPA were performed, between physical support and land use data sets (concordance = 67.4%), and between land use and social conditions data sets (concordance = 65.3%). The interplay between the pair of concordance values constitutes a bi-dimensional index which serves as an ecological indicator. Based on bootstrap confidence interval, the 49 counties of the Pampa Ecoregion, Argentina, were classified in medium, high or low concordance. The lack of concordance is an indicator of imbalances which may contribute to guide environmental management.
publishDate 2010
dc.date.none.fl_str_mv 2010-03
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/11336/16362
Matteucci, Silvia Diana; Pla, Laura; Procrustes analysis as a tool for land management; Elsevier Science; Ecological Indicators; 10; 2; 3-2010; 516-526
1470-160X
url http://hdl.handle.net/11336/16362
identifier_str_mv Matteucci, Silvia Diana; Pla, Laura; Procrustes analysis as a tool for land management; Elsevier Science; Ecological Indicators; 10; 2; 3-2010; 516-526
1470-160X
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecolind.2009.09.005
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1470160X09001538
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
publisher.none.fl_str_mv Elsevier Science
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
_version_ 1844613735907328000
score 13.070432

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