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Registro Completo |
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Biblioteca(s): |
Embrapa Unidades Centrais. |
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Data corrente: |
03/04/2017 |
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Data da última atualização: |
16/05/2017 |
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Autoria: |
GUSSO, A.; ARVOR, D.; DUCATI, J. R. |
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Afiliação: |
ANIBAL GUSSO, UFRGS; DAMIEN ARVOR, CNRS; JORGE RICARDO DUCATI, UFRGS. |
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Título: |
Model for soybean production forecast based on prevailing physical conditions. |
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Ano de publicação: |
2017 |
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Fonte/Imprenta: |
Pesquisa Agropecuária Brasileira, Brasília, DF, v. 52, n. 2, p. 95-103, fev. 2017. |
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Idioma: |
Inglês |
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Notas: |
Título em português: Modelo para previsão da produção de soja baseado em condições físicas predominantes. |
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Conteúdo: |
The objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p?0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast. |
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Thesagro: |
Agricultura; Satélite; Sensoriamento remoto. |
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Thesaurus Nal: |
Moderate resolution imaging spectroradiometer; Remote sensing; Satellites. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/158533/1/Model-for-soybean-production.pdf
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Marc: |
LEADER 02255naa a2200229 a 4500
001 2068041
005 2017-05-16
008 2017 bl uuuu u00u1 u #d
100 1 $aGUSSO, A.
245 $aModel for soybean production forecast based on prevailing physical conditions.
260 $c2017
500 $aTítulo em português: Modelo para previsão da produção de soja baseado em condições físicas predominantes.
520 $aThe objective of this work was to evaluate the reliability of the physiological meaning of the enhanced vegetation index (EVI) data for the development of a remote sensing-based procedure to estimate soybean production prior to crop harvest. Time-series data from the moderate resolution imaging spectroradiometer (Modis) were applied to investigate the relationship between local yield fluctuations of soybean and the prevailing physically-driven conditions in the state of Mato Grosso, located in the south of the Brazilian Amazon. The developed methodology was based on the coupled model (CM). The CM provides production estimates for early January, using images from the maximum crop development period. Production estimates were validated at three different spatial scales: state, municipality, and local. At the state and municipality levels, the results obtained from the CM were compared with official agricultural statistics from Instituto Brasileiro de Geografia e Estatística and Companhia Nacional de Abastecimento, from 2001 to 2011. The coefficients of determination ranged from 0.91 to 0.98, with overall result of R2=0.96 (p?0.01), indicating that the model adheres to official statistics. At the local level, spatially distributed data were compared with production data from 422 crop fields. The coefficient of determination (R2=0.87) confirmed the reliability of the EVI for its applicability on remote sensing-based models for soybean production forecast.
650 $aModerate resolution imaging spectroradiometer
650 $aRemote sensing
650 $aSatellites
650 $aAgricultura
650 $aSatélite
650 $aSensoriamento remoto
700 1 $aARVOR, D.
700 1 $aDUCATI, J. R.
773 $tPesquisa Agropecuária Brasileira, Brasília, DF$gv. 52, n. 2, p. 95-103, fev. 2017.
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Registro original: |
Embrapa Unidades Centrais (AI-SEDE) |
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| Registros recuperados : 32 | |
| 6. |  | BÉGUÉ, A.; ARVOR, D.; LELONG, C.; VINTROU, E.; SIMÕES, M. Agricultural systems studies using remote sensing. In: TENKABAIL, P. S. (Ed.). Land resources monitoring, modeling, and mapping with remote sensing. Boca Raton: CRC Press, 2015. cap. 5, p. 113-130.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Solos. |
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| 9. | | JONATHAN, M.; ARVOR, D.; MEIRELLES, M. S. P.; DUBREUIL, V. Field-oriented assessment of agricultural crops through temporal segmentation of modis VI data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 37, pt. B7, p. 921-926, 2008. Edition of Proceedings of XXI ISPRS Congress, Beijing, Jul. 2008.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Solos. |
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| 10. | | ARVOR, D.; JONATHAN, M.; MEIRELLES, M. S. P.; DUBREUIL, V. Detecting outliers and asserting consistency in agriculture ground truth information by using temporal VI data from modis. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, v. 37, pt. B7, p. 1031-1036, 2008. Edition of Proceedings of XXI ISPRS Congress, Beijing, Jul. 2008.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Solos. |
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| 12. | | KUCHLER, P. C.; BÉGUÉ, A.; SIMÕES, M.; GAETANO, R.; ARVOR, D.; FERRAZ, R. P. D. Assessing the optimal preprocessing steps of MODIS time series to map cropping systems in Mato Grosso, Brazil. International Journal of Applied Earth Observation and Geoinformation, v. 92, 102150, Oct. 2020.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Solos. |
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| 13. | | ARVOR, D.; MEIRELLES, M. S. P.; DUBREUIL, V.; BEGUÈ, A.; SHIMABUKURO, Y. E. Analyzing the agricultural transition in Mato Grosso, Brazil, using satellite-derived indices. Applied Geography, v. 32, p. 702-713, 2011.| Biblioteca(s): Embrapa Solos. |
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| 14. | | ARVOR, D.; SAN'TANNA NETO, J. L.; DUBREUIL, V.; ALMEIDA, I. R. de; MEIRELLES, M. S. P. Análise dos perfis temporais de EVI/MODIS para o monitoramento da cultura da soja no Estado de Mato Grosso, Brasil. In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO., 13., 2007, Florianópolis/SC. [São José dos Campos: INPE, 2007]. p. 51-58.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 15. | | MEIRELLES, M. S. P.; FREITAS, P. L. de; FERRAZ, R. P. D.; ARVOR, D.; DUBREUIL, V. Avaliação da dinâmica de uso da terra por meio de dados de sensores remotos para uma agricultura sustentável. In: LEITE, L. F. C.; MACIEL, G. A.; ARAÚJO, A. S. F. de (Ed.). Agricultura conservacionista no Brasil. Brasília, DF: Embrapa, 2014. pt 5, cap. 6, p. 489-511.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Solos. |
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| 16. | | ARVOR, D.; JONATHAN, M.; MEIRELLES, M. S. P.; DUBREUIL, V.; LECERF, R. Comparison of multitemporal MODIS-EVI smoothing algorithms and its contribution to crop monitoring. In: IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2008, Boston. Proceedings... Danvers, MA: IEEE, 2008. v. 2, p. 958-961.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Solos. |
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| 19. | | ARVOR, D.; JONATHAN, M.; MEIRELLES, M. S. P.; DUBREUIL, V.; DURIEUX, L. Classification of MODIS EVI time series for crop mapping in the state of Mato Grosso, Brazil. International Journal of Remote Sensing, v. 32, n. 22, p. 7847-7871, 2011.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Solos. |
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| Registros recuperados : 32 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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