Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000600427 |
Resumo: | ABSTRACT The knowledge on reliable estimates of areas under sugarcane cultivation is essential for the Brazilian agribusiness, since it helps in the development of public policies, in determining prices by sugar mills to producers and allows establishing the logistics of production disposal. The objective of this work was to develop a methodology for mapping the sugarcane crop area in the state of Paraná, Brazil, using images from the Landsat/TM/OLI and IRS/LISS-3 satellites, for the crop years from 2010/2011 to 2013/2014. The mappings were conducted through the supervised Maximum likelihood classification (Maxver) achieving, on average, an overall accuracy of 94.13% and kappa index of 0.82. The correlation with the official data of the IBGE ranged from moderate to strong (0.64 ≤ rs ≤ 0.80) with average agreement (dr) of 0.81. There was an increase of 2.73% (18,630 ha) in the area with sugarcane in Paraná between 2010/2011 and 2013/2014. |
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Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 imagesremote sensingdigital image processingsupervised classificationmaxveragricultural statisticABSTRACT The knowledge on reliable estimates of areas under sugarcane cultivation is essential for the Brazilian agribusiness, since it helps in the development of public policies, in determining prices by sugar mills to producers and allows establishing the logistics of production disposal. The objective of this work was to develop a methodology for mapping the sugarcane crop area in the state of Paraná, Brazil, using images from the Landsat/TM/OLI and IRS/LISS-3 satellites, for the crop years from 2010/2011 to 2013/2014. The mappings were conducted through the supervised Maximum likelihood classification (Maxver) achieving, on average, an overall accuracy of 94.13% and kappa index of 0.82. The correlation with the official data of the IBGE ranged from moderate to strong (0.64 ≤ rs ≤ 0.80) with average agreement (dr) of 0.81. There was an increase of 2.73% (18,630 ha) in the area with sugarcane in Paraná between 2010/2011 and 2013/2014.Departamento de Engenharia Agrícola - UFCG2017-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000600427Revista Brasileira de Engenharia Agrícola e Ambiental v.21 n.6 2017reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online)instname:Universidade Federal de Campina Grande (UFCG)instacron:UFCG10.1590/1807-1929/agriambi.v21n6p427-432info:eu-repo/semantics/openAccessCechim Junior,ClóvisJohann,Jerry A.Antunes,João F. G.eng2017-05-17T00:00:00Zoai:scielo:S1415-43662017000600427Revistahttp://www.scielo.br/rbeaaPUBhttps://old.scielo.br/oai/scielo-oai.php||agriambi@agriambi.com.br1807-19291415-4366opendoar:2017-05-17T00:00Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG)false |
dc.title.none.fl_str_mv |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
title |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
spellingShingle |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images Cechim Junior,Clóvis remote sensing digital image processing supervised classification maxver agricultural statistic |
title_short |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
title_full |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
title_fullStr |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
title_full_unstemmed |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
title_sort |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images |
author |
Cechim Junior,Clóvis |
author_facet |
Cechim Junior,Clóvis Johann,Jerry A. Antunes,João F. G. |
author_role |
author |
author2 |
Johann,Jerry A. Antunes,João F. G. |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Cechim Junior,Clóvis Johann,Jerry A. Antunes,João F. G. |
dc.subject.por.fl_str_mv |
remote sensing digital image processing supervised classification maxver agricultural statistic |
topic |
remote sensing digital image processing supervised classification maxver agricultural statistic |
description |
ABSTRACT The knowledge on reliable estimates of areas under sugarcane cultivation is essential for the Brazilian agribusiness, since it helps in the development of public policies, in determining prices by sugar mills to producers and allows establishing the logistics of production disposal. The objective of this work was to develop a methodology for mapping the sugarcane crop area in the state of Paraná, Brazil, using images from the Landsat/TM/OLI and IRS/LISS-3 satellites, for the crop years from 2010/2011 to 2013/2014. The mappings were conducted through the supervised Maximum likelihood classification (Maxver) achieving, on average, an overall accuracy of 94.13% and kappa index of 0.82. The correlation with the official data of the IBGE ranged from moderate to strong (0.64 ≤ rs ≤ 0.80) with average agreement (dr) of 0.81. There was an increase of 2.73% (18,630 ha) in the area with sugarcane in Paraná between 2010/2011 and 2013/2014. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000600427 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000600427 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1807-1929/agriambi.v21n6p427-432 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
publisher.none.fl_str_mv |
Departamento de Engenharia Agrícola - UFCG |
dc.source.none.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental v.21 n.6 2017 reponame:Revista Brasileira de Engenharia Agrícola e Ambiental (Online) instname:Universidade Federal de Campina Grande (UFCG) instacron:UFCG |
instname_str |
Universidade Federal de Campina Grande (UFCG) |
instacron_str |
UFCG |
institution |
UFCG |
reponame_str |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
collection |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) |
repository.name.fl_str_mv |
Revista Brasileira de Engenharia Agrícola e Ambiental (Online) - Universidade Federal de Campina Grande (UFCG) |
repository.mail.fl_str_mv |
||agriambi@agriambi.com.br |
_version_ |
1750297685536014336 |