Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis

Detalhes bibliográficos
Autor(a) principal: Toneli, Carlos Augusto Zangrando
Data de Publicação: 2013
Outros Autores: Carvalho, Luis Marcelo Tavares de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Repositório Institucional da UFLA
Texto Completo: http://repositorio.ufla.br/jspui/handle/1/959
http://www.sciencedirect.com/science/article/pii/S0303243404000194
Resumo: Sub-pixel analysis is capable of generating continuous fi elds, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.
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spelling Sub-pixel estimation of tree cover and bare surface densities using regression tree analysisEstimativa subpixel da cobertura arbórea e superfície esposta utilizando análise por árvore de regfressãoSensoriamento remotoMapeamentoCerradoRemote sensingMappingSub-pixel analysis is capable of generating continuous fi elds, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.A análise subpixel é capaz de gerar campos contínuos que representam a variabilidade intrínseca das classes temáticas. Neste trabalho, objetivou-se desenvolver um modelo numérico para representar a variabilidade de cobertura de dossel e de superfície exposta dentro de cada formação fl orestal. Este estudo foi conduzido em área de amortecimento ao longo da sub-bacia no médio São Francisco em MG, Brasil. Foram usados imagens dos satélites Landsat TM, e IKONOS, e o algoritmo GUIDE para ajustes dos modelos. Os resultados foram duas imagens índices, uma de cobertura arbórea e outra de superfície exposta para toda a área estudada, utilizando o modelo de árvore de regressão. O uso de modelos não-paramétricos e não-lineares por árvore de regressão apresentou resultados satisfatórios na representação de padrões de formações florestais aluviais, deciduais e savânicas.2013-09-02T19:10:57Z2013-09-02T19:10:57Z2013info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfTONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. Cerne, Lavras, MG, v. 17, n. 3, p. 411-416, jul./set. 2011.http://repositorio.ufla.br/jspui/handle/1/959http://www.sciencedirect.com/science/article/pii/S0303243404000194Toneli, Carlos Augusto ZangrandoCarvalho, Luis Marcelo Tavares deinfo:eu-repo/semantics/openAccessporreponame:Repositório Institucional da UFLAinstname:Universidade Federal de Lavras (UFLA)instacron:UFLA2013-10-04T11:50:53Zoai:localhost:1/959Repositório InstitucionalPUBhttp://repositorio.ufla.br/oai/requestnivaldo@ufla.br || repositorio.biblioteca@ufla.bropendoar:2013-10-04T11:50:53Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)false
dc.title.none.fl_str_mv Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
Estimativa subpixel da cobertura arbórea e superfície esposta utilizando análise por árvore de regfressão
title Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
spellingShingle Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
Toneli, Carlos Augusto Zangrando
Sensoriamento remoto
Mapeamento
Cerrado
Remote sensing
Mapping
title_short Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
title_full Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
title_fullStr Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
title_full_unstemmed Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
title_sort Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis
author Toneli, Carlos Augusto Zangrando
author_facet Toneli, Carlos Augusto Zangrando
Carvalho, Luis Marcelo Tavares de
author_role author
author2 Carvalho, Luis Marcelo Tavares de
author2_role author
dc.contributor.author.fl_str_mv Toneli, Carlos Augusto Zangrando
Carvalho, Luis Marcelo Tavares de
dc.subject.por.fl_str_mv Sensoriamento remoto
Mapeamento
Cerrado
Remote sensing
Mapping
topic Sensoriamento remoto
Mapeamento
Cerrado
Remote sensing
Mapping
description Sub-pixel analysis is capable of generating continuous fi elds, which represent the spatial variability of certain thematic classes. The aim of this work was to develop numerical models to represent the variability of tree cover and bare surfaces within the study area. This research was conducted in the riparian buffer within a watershed of the São Francisco River in the North of Minas Gerais, Brazil. IKONOS and Landsat TM imagery were used with the GUIDE algorithm to construct the models. The results were two index images derived with regression trees for the entire study area, one representing tree cover and the other representing bare surface. The use of non-parametric and non-linear regression tree models presented satisfactory results to characterize wetland, deciduous and savanna patterns of forest formation.
publishDate 2013
dc.date.none.fl_str_mv 2013-09-02T19:10:57Z
2013-09-02T19:10:57Z
2013
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 TONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. Cerne, Lavras, MG, v. 17, n. 3, p. 411-416, jul./set. 2011.
http://repositorio.ufla.br/jspui/handle/1/959
http://www.sciencedirect.com/science/article/pii/S0303243404000194
identifier_str_mv TONELI, C. A. Z.; CARVALHO, L. M. T. de. Sub-pixel estimation of tree cover and bare surface densities using regression tree analysis. Cerne, Lavras, MG, v. 17, n. 3, p. 411-416, jul./set. 2011.
url http://repositorio.ufla.br/jspui/handle/1/959
http://www.sciencedirect.com/science/article/pii/S0303243404000194
dc.language.iso.fl_str_mv por
language por
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.source.none.fl_str_mv reponame:Repositório Institucional da UFLA
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Repositório Institucional da UFLA
collection Repositório Institucional da UFLA
repository.name.fl_str_mv Repositório Institucional da UFLA - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv nivaldo@ufla.br || repositorio.biblioteca@ufla.br
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