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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
06/08/2012 |
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Data da última atualização: |
15/08/2017 |
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Autoria: |
GUSSO, A.; FORMAGGIO, A. R.; RIZZI, R.; ADAMI, M.; RUDORFF, B. F. T. |
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Afiliação: |
ANIBAL GUSSO, Instituto Nacional de Pesquisas Espaciais; ANTÔNIO ROBERTO FORMAGGIO, Instituto Nacional de Pesquisas Espaciais; RODRIGO RIZZI, Instituto Nacional de Pesquisas Espaciais; MARCOS ADAMI, Instituto Nacional de Pesquisas Espaciais; BERNARDO FRIEDRICH THEODOR RUDORFF, Instituto Nacional de Pesquisas Espaciais. |
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Título: |
Soybean crop area estimation by Modis/Evi data. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
Pesquisa Agropecuaria Brasileira, Brasília, DF, v. 47, n. 3, p. 425-435, mar. 2012. |
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Idioma: |
Inglês |
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Notas: |
Título em português: Estimativa de áreas de cultivo de soja por meio de dados Modis/Evi. |
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Conteúdo: |
The objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics. |
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Palavras-Chave: |
Algoritmo; Área agrícola; Crop area; Perfil temporal; Temporal profile. |
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Thesagro: |
Glycine Max; Mapa; Soja. |
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Thesaurus Nal: |
Algorithms. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/63040/1/Soybean-crop-area.pdf
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Marc: |
LEADER 02173naa a2200289 a 4500
001 1930528
005 2017-08-15
008 2012 bl uuuu u00u1 u #d
100 1 $aGUSSO, A.
245 $aSoybean crop area estimation by Modis/Evi data.
260 $c2012
500 $aTítulo em português: Estimativa de áreas de cultivo de soja por meio de dados Modis/Evi.
520 $aThe objective of this work was to develop a procedure to estimate soybean crop areas in Rio Grande do Sul state, Brazil. Estimations were made based on the temporal profiles of the enhanced vegetation index (Evi) calculated from moderate resolution imaging spectroradiometer (Modis) images. The methodology developed for soybean classification was named Modis crop detection algorithm (MCDA). The MCDA provides soybean area estimates in December (first forecast), using images from the sowing period, and March (second forecast), using images from the sowing and maximum crop development periods. The results obtained by the MCDA were compared with the official estimates on soybean area of the Instituto Brasileiro de Geografia e Estatística. The coefficients of determination ranged from 0.91 to 0.95, indicating good agreement between the estimates. For the 2000/2001 crop year, the MCDA soybean crop map was evaluated using a soybean crop map derived from Landsat images, and the overall map accuracy was approximately 82%, with similar commission and omission errors. The MCDA was able to estimate soybean crop areas in Rio Grande do Sul State and to generate an annual thematic map with the geographic position of the soybean fields. The soybean crop area estimates by the MCDA are in good agreement with the official agricultural statistics.
650 $aAlgorithms
650 $aGlycine Max
650 $aMapa
650 $aSoja
653 $aAlgoritmo
653 $aÁrea agrícola
653 $aCrop area
653 $aPerfil temporal
653 $aTemporal profile
700 1 $aFORMAGGIO, A. R.
700 1 $aRIZZI, R.
700 1 $aADAMI, M.
700 1 $aRUDORFF, B. F. T.
773 $tPesquisa Agropecuaria Brasileira, Brasília, DF$gv. 47, n. 3, p. 425-435, mar. 2012.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Hortaliças. Para informações adicionais entre em contato com cnph.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Hortaliças. |
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Data corrente: |
14/08/2014 |
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Data da última atualização: |
14/08/2014 |
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Tipo da produção científica: |
Resumo em Anais de Congresso |
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Autoria: |
SOUZA, J. O.; INOUE-NAGATA, A. K. |
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Afiliação: |
J. O. SOUZA, UNIVERSIDADE DE BRASÍLIA, DEPARTAMENTO DE PATOLOGIA DE PLANTA; EMBRAPA HORTALIÇAS; ALICE KAZUKO INOUE NAGATA, CNPH. |
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Título: |
Diversity of begomoviruses in tomato plants cultivated in the North-East part of Brazil. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
In: INTERNATIONAL GEMINIVIRUS SYMPOSIUM, 7.; INTERNATIONAL SSDNA COMPARATIVE VIROLOGY WORKSHOP, 5., 2013, Hangzhou. Program and abstracts... [S.l.: s.n., 2013]. |
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Páginas: |
p. 43 |
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Idioma: |
Inglês |
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Notas: |
Resumo. |
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Conteúdo: |
This study aimed at analyzing the diversity of tomato begomoviruses that occur in the North-East Brazil. |
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Palavras-Chave: |
Tomato. |
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Thesagro: |
Doença de planta. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 00691nam a2200169 a 4500
001 1992606
005 2014-08-14
008 2013 bl uuuu u00u1 u #d
100 1 $aSOUZA, J. O.
245 $aDiversity of begomoviruses in tomato plants cultivated in the North-East part of Brazil.
260 $aIn: INTERNATIONAL GEMINIVIRUS SYMPOSIUM, 7.; INTERNATIONAL SSDNA COMPARATIVE VIROLOGY WORKSHOP, 5., 2013, Hangzhou. Program and abstracts... [S.l.: s.n.$c2013
300 $ap. 43
500 $aResumo.
520 $aThis study aimed at analyzing the diversity of tomato begomoviruses that occur in the North-East Brazil.
650 $aDoença de planta
653 $aTomato
700 1 $aINOUE-NAGATA, A. K.
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