EVALUATION OF DECISION TREE CLASSIFICATION ACCURACY TO MAP LAND COVER IN CAPIXABA, ACRE
Autor(a) principal: | |
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Data de Publicação: | 2015 |
Outros Autores: | |
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. |
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Cerne (Online) |
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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 |