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Registro Completo |
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
22/05/2017 |
Data da última atualização: |
22/05/2017 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Autoria: |
CECHIM JUNIOR, C.; JOHANN, J. A.; ANTUNES, J. F. G. |
Afiliação: |
CLÓVIS CECHIM JUNIOR, Unioeste; JERRY A. JOHANN, Unioeste; JOÃO FRANCISCO GONÇALVES ANTUNES, CNPTIA. |
Título: |
Mapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images. |
Ano de publicação: |
2017 |
Fonte/Imprenta: |
Revista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande, v. 21, n. 6, p. 427-432, jun. 2017. |
DOI: |
http://dx.doi.org/10.1590/1807-1929/agriambi.v21n6p427-432 |
Idioma: |
Inglês |
Notas: |
Agriambi. |
Conteúdo: |
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. |
Palavras-Chave: |
Classificação supervisionada; Digital image processing; Maxver; Processamento de imagem digital; Supervised classification. |
Thesagro: |
Cana de açúcar; Estatística agrícola; Sensoriamento remoto. |
Thesaurus Nal: |
Agricultural statistics; Image analysis; Remote sensing; Sugarcane. |
Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/160105/1/AP-Mapping-Cechim-Agriambi-2017.pdf
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Marc: |
LEADER 02027naa a2200313 a 4500 001 2069839 005 2017-05-22 008 2017 bl uuuu u00u1 u #d 024 7 $ahttp://dx.doi.org/10.1590/1807-1929/agriambi.v21n6p427-432$2DOI 100 1 $aCECHIM JUNIOR, C. 245 $aMapping of sugarcane crop area in the Paraná State using Landsat/TM/OLI and IRS/LISS-3 images.$h[electronic resource] 260 $c2017 500 $aAgriambi. 520 $aABSTRACT. 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. 650 $aAgricultural statistics 650 $aImage analysis 650 $aRemote sensing 650 $aSugarcane 650 $aCana de açúcar 650 $aEstatística agrícola 650 $aSensoriamento remoto 653 $aClassificação supervisionada 653 $aDigital image processing 653 $aMaxver 653 $aProcessamento de imagem digital 653 $aSupervised classification 700 1 $aJOHANN, J. A. 700 1 $aANTUNES, J. F. G. 773 $tRevista Brasileira de Engenharia Agrícola e Ambiental, Campina Grande$gv. 21, n. 6, p. 427-432, jun. 2017.
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Embrapa Agricultura Digital (CNPTIA) |
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