Scaling functions evaluation for estimation of landscape metrics at higher resolutions

Understanding the relationship between landscape pattern and environmental processes requires quantification of landscape pattern at multiple scales. This will make it possible to relate broad-scale patterns to fine-scale processes and vice versa. In this study, we used class level landscape metrics...

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Detalhes bibliográficos
Autores: Argañaraz, Juan Pablo, Entraigas, Ilda
Formato: artículo
Estado:Versión publicada
Fecha de publicación:2014
País:Argentina
Recursos:Consejo Nacional de Investigaciones Científicas y Técnicas
Repositorio:CONICET Digital (CONICET)
Idioma:inglés
OAI Identifier:oai:ri.conicet.gov.ar:11336/7920
Acesso em linha:http://hdl.handle.net/11336/7920
Access Level:acceso abierto
Palavra-chave:Scale
Landscape Pattern
Landscape Metrics
Scaling Functions
Downscaling
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
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spelling Scaling functions evaluation for estimation of landscape metrics at higher resolutionsArgañaraz, Juan PabloEntraigas, IldaScaleLandscape PatternLandscape MetricsScaling FunctionsDownscalinghttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Understanding the relationship between landscape pattern and environmental processes requires quantification of landscape pattern at multiple scales. This will make it possible to relate broad-scale patterns to fine-scale processes and vice versa. In this study, we used class level landscape metrics calculated at multiple scales to fit scaling functions that were used to downscale metrics at higher resolutions. The main objectives were to assess the performance of different type of functions (i.e. power, logarithmic, etc.) to downscale metrics at the subpixel level and to analyze the variability of the accuracy of subpixel estimates among patch classes for each landscape metric. We used thirteen frequently used landscape metrics, computed on a land use/land cover map derived from Landsat imagery through visual interpretation and supervised classification using Support Vector Machines. The performance of scaling functions was assessed with the Accuracy Improvement percentage (AI). In general, the power function fitted better for most landscape metrics and classes; however, in several cases, more than one type of function showed similar R2 values. Accuracy of subpixel estimates was very variable among landscape metrics and also among patch classes within a metric. The amount of variation was such that no generalization about the predictability of a landscape metric calculated at the class level was possible. Indeed, predictability seemed to be more of a characteristic of the class than a characteristic of the landscape metric. Additionally, the goodness of fit of the scaling functions was not a good indicator of the functions' ability to downscale landscape metrics accurately, indicating that different scaling functions should be analyzed when downscaling landscape metrics at higher resolutions is required.Fil: Argañaraz, Juan Pablo. Provincia de Buenos Aires. Gobernación. Comisión de Investigaciones Científicas; Argentina. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; Argentina. Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Cordoba. Instituto de Diversidad y Ecologia Animal; ArgentinaFil: Entraigas, Ilda. Universidad Nacional del Centro de la Provincia de Buenos Aires. Rectorado. Instituto de Hidrología de Llanuras - Sede Azul; ArgentinaElsevier Science2014-07info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/7920Argañaraz, Juan Pablo; Entraigas, Ilda; Scaling functions evaluation for estimation of landscape metrics at higher resolutions; Elsevier Science; Ecological Informatics; 22; 7-2014; 1-121574-9541enginfo:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecoinf.2014.02.004info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1574954114000211info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-nd/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2024-05-08T13:57:36Zoai:ri.conicet.gov.ar:11336/7920instacron: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:34982024-05-08 13:57:36.968CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Scaling functions evaluation for estimation of landscape metrics at higher resolutions
title Scaling functions evaluation for estimation of landscape metrics at higher resolutions
spellingShingle Scaling functions evaluation for estimation of landscape metrics at higher resolutions
Argañaraz, Juan Pablo
Scale
Landscape Pattern
Landscape Metrics
Scaling Functions
Downscaling
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
title_short Scaling functions evaluation for estimation of landscape metrics at higher resolutions
title_full Scaling functions evaluation for estimation of landscape metrics at higher resolutions
title_fullStr Scaling functions evaluation for estimation of landscape metrics at higher resolutions
title_full_unstemmed Scaling functions evaluation for estimation of landscape metrics at higher resolutions
title_sort Scaling functions evaluation for estimation of landscape metrics at higher resolutions
dc.creator.none.fl_str_mv Argañaraz, Juan Pablo
Entraigas, Ilda
author Argañaraz, Juan Pablo
author_facet Argañaraz, Juan Pablo
Entraigas, Ilda
author_role author
author2 Entraigas, Ilda
author2_role author
dc.subject.none.fl_str_mv Scale
Landscape Pattern
Landscape Metrics
Scaling Functions
Downscaling
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
topic Scale
Landscape Pattern
Landscape Metrics
Scaling Functions
Downscaling
https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
description Understanding the relationship between landscape pattern and environmental processes requires quantification of landscape pattern at multiple scales. This will make it possible to relate broad-scale patterns to fine-scale processes and vice versa. In this study, we used class level landscape metrics calculated at multiple scales to fit scaling functions that were used to downscale metrics at higher resolutions. The main objectives were to assess the performance of different type of functions (i.e. power, logarithmic, etc.) to downscale metrics at the subpixel level and to analyze the variability of the accuracy of subpixel estimates among patch classes for each landscape metric. We used thirteen frequently used landscape metrics, computed on a land use/land cover map derived from Landsat imagery through visual interpretation and supervised classification using Support Vector Machines. The performance of scaling functions was assessed with the Accuracy Improvement percentage (AI). In general, the power function fitted better for most landscape metrics and classes; however, in several cases, more than one type of function showed similar R2 values. Accuracy of subpixel estimates was very variable among landscape metrics and also among patch classes within a metric. The amount of variation was such that no generalization about the predictability of a landscape metric calculated at the class level was possible. Indeed, predictability seemed to be more of a characteristic of the class than a characteristic of the landscape metric. Additionally, the goodness of fit of the scaling functions was not a good indicator of the functions' ability to downscale landscape metrics accurately, indicating that different scaling functions should be analyzed when downscaling landscape metrics at higher resolutions is required.
publishDate 2014
dc.date.none.fl_str_mv 2014-07
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/11336/7920
Argañaraz, Juan Pablo; Entraigas, Ilda; Scaling functions evaluation for estimation of landscape metrics at higher resolutions; Elsevier Science; Ecological Informatics; 22; 7-2014; 1-12
1574-9541
url http://hdl.handle.net/11336/7920
identifier_str_mv Argañaraz, Juan Pablo; Entraigas, Ilda; Scaling functions evaluation for estimation of landscape metrics at higher resolutions; Elsevier Science; Ecological Informatics; 22; 7-2014; 1-12
1574-9541
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1016/j.ecoinf.2014.02.004
info:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S1574954114000211
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
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
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
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score 15,228081

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