Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images

Detalhes bibliográficos
Autor(a) principal: Cechim Junior,Clóvis
Data de Publicação: 2017
Outros Autores: Johann,Jerry A., Antunes,João F. G.
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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spelling 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
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dc.identifier.uri.fl_str_mv http://old.scielo.br/scielo.php?script=sci_arttext&pid=S1415-43662017000600427
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dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 10.1590/1807-1929/agriambi.v21n6p427-432
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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)
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instname_str Universidade Federal de Campina Grande (UFCG)
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reponame_str Revista Brasileira de Engenharia Agrícola e Ambiental (Online)
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