EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE

Detalhes bibliográficos
Autor(a) principal: Figueiredo, Symone Maria de Melo
Data de Publicação: 2015
Outros Autores: Carvalho, Luis Marcelo Tavares de
Tipo de documento: Artigo
Idioma: por
Título da fonte: Cerne (Online)
Texto Completo: https://cerne.ufla.br/site/index.php/CERNE/article/view/397
Resumo: This study evaluated the accuracy of mapping land cover in Capixaba, state of Acre, Brazil, using decision trees. Eleven attributes were used to build the decision trees: TM Landsat datafrom bands 1, 2, 3, 4, 5, and 7; fraction images derived from linear spectral unmixing; and the normalized difference vegetation index (NDVI). The Kappa values were greater than 0,83, producing excellent classification results and demonstrating that the technique is promising for mapping land cover in the study area.
id UFLA-3_59c66f3b39e3ed5a7e362f8b34670420
oai_identifier_str oai:cerne.ufla.br:article/397
network_acronym_str UFLA-3
network_name_str Cerne (Online)
repository_id_str
spelling EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACREdigital image classificationdata mininglinear spectral unmixingNDVIThis study evaluated the accuracy of mapping land cover in Capixaba, state of Acre, Brazil, using decision trees. Eleven attributes were used to build the decision trees: TM Landsat datafrom bands 1, 2, 3, 4, 5, and 7; fraction images derived from linear spectral unmixing; and the normalized difference vegetation index (NDVI). The Kappa values were greater than 0,83, producing excellent classification results and demonstrating that the technique is promising for mapping land cover in the study area.CERNECERNE2015-09-17info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://cerne.ufla.br/site/index.php/CERNE/article/view/397CERNE; Vol. 12 No. 1 (2006); 038-047CERNE; v. 12 n. 1 (2006); 038-0472317-63420104-7760reponame:Cerne (Online)instname:Universidade Federal de Lavras (UFLA)instacron:UFLAporhttps://cerne.ufla.br/site/index.php/CERNE/article/view/397/339Copyright (c) 2015 CERNEinfo:eu-repo/semantics/openAccessFigueiredo, Symone Maria de MeloCarvalho, Luis Marcelo Tavares de2015-10-22T10:12:00Zoai:cerne.ufla.br:article/397Revistahttps://cerne.ufla.br/site/index.php/CERNEPUBhttps://cerne.ufla.br/site/index.php/CERNE/oaicerne@dcf.ufla.br||cerne@dcf.ufla.br2317-63420104-7760opendoar:2024-05-21T19:53:48.579833Cerne (Online) - Universidade Federal de Lavras (UFLA)true
dc.title.none.fl_str_mv EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
title EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
spellingShingle EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
Figueiredo, Symone Maria de Melo
digital image classification
data mining
linear spectral unmixing
NDVI
title_short EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
title_full EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
title_fullStr EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
title_full_unstemmed EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
title_sort EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
author Figueiredo, Symone Maria de Melo
author_facet Figueiredo, Symone Maria de Melo
Carvalho, Luis Marcelo Tavares de
author_role author
author2 Carvalho, Luis Marcelo Tavares de
author2_role author
dc.contributor.author.fl_str_mv Figueiredo, Symone Maria de Melo
Carvalho, Luis Marcelo Tavares de
dc.subject.por.fl_str_mv digital image classification
data mining
linear spectral unmixing
NDVI
topic digital image classification
data mining
linear spectral unmixing
NDVI
description This study evaluated the accuracy of mapping land cover in Capixaba, state of Acre, Brazil, using decision trees. Eleven attributes were used to build the decision trees: TM Landsat datafrom bands 1, 2, 3, 4, 5, and 7; fraction images derived from linear spectral unmixing; and the normalized difference vegetation index (NDVI). The Kappa values were greater than 0,83, producing excellent classification results and demonstrating that the technique is promising for mapping land cover in the study area.
publishDate 2015
dc.date.none.fl_str_mv 2015-09-17
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/397
url https://cerne.ufla.br/site/index.php/CERNE/article/view/397
dc.language.iso.fl_str_mv por
language por
dc.relation.none.fl_str_mv https://cerne.ufla.br/site/index.php/CERNE/article/view/397/339
dc.rights.driver.fl_str_mv Copyright (c) 2015 CERNE
info:eu-repo/semantics/openAccess
rights_invalid_str_mv Copyright (c) 2015 CERNE
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv CERNE
CERNE
publisher.none.fl_str_mv CERNE
CERNE
dc.source.none.fl_str_mv CERNE; Vol. 12 No. 1 (2006); 038-047
CERNE; v. 12 n. 1 (2006); 038-047
2317-6342
0104-7760
reponame:Cerne (Online)
instname:Universidade Federal de Lavras (UFLA)
instacron:UFLA
instname_str Universidade Federal de Lavras (UFLA)
instacron_str UFLA
institution UFLA
reponame_str Cerne (Online)
collection Cerne (Online)
repository.name.fl_str_mv Cerne (Online) - Universidade Federal de Lavras (UFLA)
repository.mail.fl_str_mv cerne@dcf.ufla.br||cerne@dcf.ufla.br
_version_ 1799874940515647488

Registros relacionados