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Registro Completo |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
08/02/2022 |
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Data da última atualização: |
11/03/2022 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
KUCHLER, P. C.; SIMÕES, M.; BEGUE, A.; FERRAZ, R. P. D. |
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Afiliação: |
PATRICK CALVANO KUCHLER, UERJ; MARGARETH GONCALVES SIMOES, CNPS; AGNÈS BEGUE, CIRAD; RODRIGO PECANHA DEMONTE FERRAZ, CNPS. |
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Título: |
Big earth observation data and machine learning for mapping crop-livestock integrated system in Brazil. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
In: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. WCCLF 2021 proceedings. Brasília, DF: Embrapa, 2021. p. 904-909. WCCLF 2021. Evento online. |
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Idioma: |
Inglês |
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Conteúdo: |
The adoption of crop-livestock (iCL) integrated systems has been pointed out as an important strategy for increasing production based on sustainable intensification of land use in Brazil. Mapping and monitoring the iCL areas would allow us to know the expansion rates and the adoption level of the integrated system, being an important instrument for public policy management. However, due to the time-space variability from integrated production systems, developing methods based on remote sensing remains a major challenge. In this sense, this work discusses the application of Big Data and machine learning concepts in Earth Observation Data as a strategy to compose a methodology for monitoring the iCL in Brazil. We tested the capacity of the Random Forest (RF) classifier applied to MODIS time series to iCL detection in the Mato Grosso State, Brazil. For this, we evaluated the classification accuracy for the years between 2012 and 2019, totaling 3,864 images processed. The overall accuracy founded was between 0.77 and 0.89 and an fscore average of 0.85 was found for the iCL class. The generated maps showed a trajectory of sustainable intensification, with the expansion of the iCL area from 1,100,000 ha in 2012/2013 to 2,597,000 ha in 2018/2019, an increase of 135%. The results indicate that the use of the RF classification technique with MODIS times series has great potential to compose an iCL monitoring methodology, requiring parallel and cloud computing applied to advanced algorithms. MenosThe adoption of crop-livestock (iCL) integrated systems has been pointed out as an important strategy for increasing production based on sustainable intensification of land use in Brazil. Mapping and monitoring the iCL areas would allow us to know the expansion rates and the adoption level of the integrated system, being an important instrument for public policy management. However, due to the time-space variability from integrated production systems, developing methods based on remote sensing remains a major challenge. In this sense, this work discusses the application of Big Data and machine learning concepts in Earth Observation Data as a strategy to compose a methodology for monitoring the iCL in Brazil. We tested the capacity of the Random Forest (RF) classifier applied to MODIS time series to iCL detection in the Mato Grosso State, Brazil. For this, we evaluated the classification accuracy for the years between 2012 and 2019, totaling 3,864 images processed. The overall accuracy founded was between 0.77 and 0.89 and an fscore average of 0.85 was found for the iCL class. The generated maps showed a trajectory of sustainable intensification, with the expansion of the iCL area from 1,100,000 ha in 2012/2013 to 2,597,000 ha in 2018/2019, an increase of 135%. The results indicate that the use of the RF classification technique with MODIS times series has great potential to compose an iCL monitoring methodology, requiring parallel and cloud computing applied to advanced algo... Mostrar Tudo |
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Palavras-Chave: |
Machine learning; MODIS time series. |
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Thesagro: |
Agricultura Sustentável. |
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Thesaurus Nal: |
Sustainable agricultural intensification. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/231050/1/Big-earth-observation-data-and-machine-learning-2021.pdf
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Marc: |
LEADER 02262nam a2200193 a 4500
001 2139789
005 2022-03-11
008 2021 bl uuuu u00u1 u #d
100 1 $aKUCHLER, P. C.
245 $aBig earth observation data and machine learning for mapping crop-livestock integrated system in Brazil.$h[electronic resource]
260 $aIn: WORLD CONGRESS ON INTEGRATED CROP-LIVESTOCK-FORESTRY SYSTEMS, 2., 2021. WCCLF 2021 proceedings. Brasília, DF: Embrapa, 2021. p. 904-909. WCCLF 2021. Evento online.$c2021
520 $aThe adoption of crop-livestock (iCL) integrated systems has been pointed out as an important strategy for increasing production based on sustainable intensification of land use in Brazil. Mapping and monitoring the iCL areas would allow us to know the expansion rates and the adoption level of the integrated system, being an important instrument for public policy management. However, due to the time-space variability from integrated production systems, developing methods based on remote sensing remains a major challenge. In this sense, this work discusses the application of Big Data and machine learning concepts in Earth Observation Data as a strategy to compose a methodology for monitoring the iCL in Brazil. We tested the capacity of the Random Forest (RF) classifier applied to MODIS time series to iCL detection in the Mato Grosso State, Brazil. For this, we evaluated the classification accuracy for the years between 2012 and 2019, totaling 3,864 images processed. The overall accuracy founded was between 0.77 and 0.89 and an fscore average of 0.85 was found for the iCL class. The generated maps showed a trajectory of sustainable intensification, with the expansion of the iCL area from 1,100,000 ha in 2012/2013 to 2,597,000 ha in 2018/2019, an increase of 135%. The results indicate that the use of the RF classification technique with MODIS times series has great potential to compose an iCL monitoring methodology, requiring parallel and cloud computing applied to advanced algorithms.
650 $aSustainable agricultural intensification
650 $aAgricultura Sustentável
653 $aMachine learning
653 $aMODIS time series
700 1 $aSIMÕES, M.
700 1 $aBEGUE, A.
700 1 $aFERRAZ, R. P. D.
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Registro original: |
Embrapa Solos (CNPS) |
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| Registros recuperados : 15 | |
| 2. |  | TOLEDO, M. Z.; CAVARIANI, C.; FRANCA-NETO, J. de B. Physiological quality of soybean seeds as affected by chemical treatment and genotype. In: WORLD SOYBEAN RESEARCH CONFERENCE, 8., 2009, Beijing. Developing a global soy blueprint for a safe secure and sustainable supply: abstracts. Beijing: Chinese Academy of Agricultural Sciences: Institute of Crop Science, 2009. p. 215, ref. P502. WSRC 2009. Editado por Lijuan Qiu, Rongxia Guan, Jian Jin, Qijan Song, Shuntang Guo, Wenbin Li, Yuanchao Wang, Tianfu Han, Xiaobing Liu, Deyue Yu, Lianzhou Jiang, Deliang Peng.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 5. | | TOLEDO, M. Z.; CAVARIANI, C.; FRANÇA-NETO, J. de B.; NAKAGAWA, J. Imbibition damage in soybean seeds as affected by initial moisture content, cultivar and production location . Seed Science and Technology, Zurich, v. 38, n. 2, p. 399-408, Jul. 2010.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Soja. |
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| 6. | | TOLEDO, M. Z.; TOMAZ, C. A.; CAVARIANI, C.; FRANCA NETO, J. de B. Pre-harvest desiccation with glyphosate and physiological quality of soybean seeds. Informativo ABRATES, Brasília, DF, v. 21, n. 1, p. 223, abr. 2011. N. Especial, ref. 298. Edition of the Abstracts: 10th Conference of the International Society for Seed Science, Costa do Sauípe, Apr. 2011.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 7. | | TOLEDO, M. Z.; ISHIZUKA, M. S.; CAVARIANI, C.; FRANÇA-NETO, J. B.; PICOLI, L. B. Pre-harvest desiccation with glyphosate and quality of stored soybean seeds. Semina: Ciências Agrárias, Londrina, v. 35, n. 2, p. 765-774, mar./abr. 2014.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Soja. |
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| 9. | | SOUZA, F. L. G.; TOLEDO, M. Z.; CAVARIANI, C.; FRANCA NETO, J. de B.; ALVES, E. Effects of chemical dessication and soybean genotypeon seed physiological quality. In: WORLD SOYBEAN RESEARCH CONFERENCE, 8., 2009, Beijing. Developing a global soy blueprint for a safe secure and sustainable supply: abstracts. Beijing: Chinese Academy of Agricultural Sciences: Institute of Crop Science, 2009. p. 215, ref. P503. WSRC 2009. Editado por Lijuan Qiu, Rongxia Guan, Jian Jin, Qijan Song, Shuntang Guo, Wenbin Li, Yuanchao Wang, Tianfu Han, Xiaobing Liu, Deyue Yu, Lianzhou Jiang, Deliang Peng.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 10. | | ISHIZUKA, M. S.; TOLEDO, M. Z.; CAVARIANI, C.; FRANÇA NETO, J. B.; PICOLI, L. B. Dessecação de plantas de soja com glyphosate e qualidade das sementes armazenadas. Informativo ABRATES, Londrina, v. 21, n. 2, ago. 2011. CD-ROM. Edição dos Anais do XVII Congresso Brasileiro de Sementes., Natal, ago. 2011.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 11. | | TOLEDO, M. Z.; CAVARIANI, C.; BENNETT, M. A.; FRANÇA NETO, J. B. Fitotoxicidade em plântulas de soja decorrente da dessecação das plantas e tratamento das sementes. In: REUNIÃO DE PESQUISA DE SOJA DA REGIÃO CENTRAL DO BRASIL, 32., 2011, São Pedro, SP. Resumos expandidos... Londrina: Embrapa Soja, 2011. p. 357-360. Editado por Adilson de Oliveira Junior, Odilon Ferreira Saraiva, Regina Maria Villas Bôas de Campos Leite.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 13. | | CAVARIANI, C.; TOLEDO, M. Z.; RODELLA, R. A.; FRANCA NETO, J. de B.; NAKAGAWA, J. Velocidade de hidratação em função de características do tegumento de sementes de soja de diferentes cultivares e localidades. Revista Brasileira de Sementes, Lavras, v. 31, n. 1, p. 30-39, mar. 2009.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 2 |
| Biblioteca(s): Embrapa Soja. |
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| 14. | | CAVARIANI, C.; TOLEDO, M. Z.; FRANCA NETO, J. B.; ISHIZUKA, M. S.; PICOLI, L. B.; DOGNINI, A. C. Efeitos da dessecação das plantas e do tratamento fungicida na qualidade de sementes de soja. Informativo ABRATES, Londrina, v. 21, n. 2, ago. 2011. CD-ROM. Edição dos Anais do XVII Congresso Brasileiro de Sementes., Natal, ago. 2011.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Soja. |
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| 15. | | TOLEDO, M. Z.; CASTRO, G. S. A.; CRUSCIOL, C. A. C.; SORATTO, R. P.; CAVARIANI, C.; ISHIZUKA, M. S; PICOLI, L. B. Silicon leaf application and physiological quality of white oat and wheat seeds. Semina. Ciências Agrárias, Londrina, v. 33, n. 5, p. 1693-1702, set./out. 2012.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Amapá. |
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| Registros recuperados : 15 | |
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| Registros recuperados : 1 | |
| 1. | | 1250047, CEPALINDEX; RESUMENES DE DOCUMENTOS CEPAL/ILPES, Comision Economica para America Latina. Centro Latino Americano de Documentacion Economica y Social, Santiago-Chile
Biblioteca(s): Catálogo Coletivo de Periódicos Embrapa; Embrapa Acre; Embrapa Amazônia Oriental; Embrapa Meio-Norte; Embrapa Soja. | |
| Registros recuperados : 1 | |
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