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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 : 327 | |
| 45. |  | WETZEL, M. M. V. S.; RAMOS, S. R. R.; PEREIRA NETO, L. G. Comportamento das sementes de feijão-caupi no armazenamento a longo prazo. In: CONGRESSO NACIONAL DE FEIJÃO-CAUPI; REUNIÃO NACIONAL DE FEIJÃO-CAUPI, 6., 2006, Teresina, PI. [Anais...]. Teresina, PI: Embrapa Meio-Norte, 2006. Não paginado. (Embrapa Meio-Norte. Documentos, 121).| Biblioteca(s): Embrapa Recursos Genéticos e Biotecnologia. |
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| 53. | | ARAGAO, W. M.; LOIOLA, C. M.; GOIS, S. S.; RAMOS, S. R. R. Seleção de cultivares de coqueiro (Cocos nucifera L.) com menor porte. Revista RG News, Brasília, DF, v. 3, n. 2, 2017. p. 117. Edição Especial dos Anais do 3° Simpósio da Rede de Recursos Genéticos Vegetais do Nordeste, Aracaju, out. 2017.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Tabuleiros Costeiros. |
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| 54. | | RAMOS, S. R. R.; CASALI, V. W. D.; QUEIROZ, M. A. de; CRUZ, C. D. Selecao de descritores para a caracterizacao de acessos em banco de germoplasma de cucurbita sp. Horticultura Brasileira, Brasília, DF, v. 14, n.1, set. p. 110, maio. 1996. Edição dos Resumos do 36 Congresso Brasileiro de Olericultura, Rio de Janeiro, maio, 1996.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Semiárido. |
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| 55. | | QUEIROZ, M. A. de; RAMOS, S. R. R.; DIAS, R. de C. S. Divergencia genetica entre linhagens de melancia parcialmente endogamicas. Horticultura Brasileira, Brasília, DF, v. 19, n. 2, jul. 2001. 1 CD-ROM. Suplemento. Edição do 41 Congresso Brasileiro de Olericultura; 1 Encontro sobre Plantas Medicinais, Aromáticas e Condimentares, Brasília, DF, jul. 2001.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Semiárido. |
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| 56. | | RAMOS, S. R. R.; QUEIROZ, M. A. de; CASALI, V. W. D.; CRUZ, C. D. Divergencia genetica em germoplasma de abobora procedente de diferentes areas do Nordeste. Horticultura Brasileira, Brasília, DF, v. 18, n. 3, p. 195-199, nov. 2000.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: Nacional - B |
| Biblioteca(s): Embrapa Semiárido. |
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| 59. | | QUEIROZ, M. A. de; RAMOS, S. R. R.; ROMAO, R. L.; ASSIS, J. G. de A. Coleta de germoplasma de cucurbita mochata e cucurbita maxima em duas regioes do Nordeste brasileiro. In: SIMPOSIO LATINOAMERICANO SOBRE RECURSOS GENETICOS DE ESPECIES HORTICOLAS, 2.; CONGRESSO ARGENTINO DE HORTICULTURA, 14.,1991, Mar del Plata, Argentina. Actas... Mar del Plata: Asociacion Argentina de Horticultura, 1991. p. 35-43.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Semiárido. |
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| 60. | | SILVA, M. A. S. da; RAMOS, S. R. R.; QUEIROZ, M. A. de. Coleta de germoplasma de maxixe (Cucumis anguria) na região de Brumado, Dom Basílio e Rio de Contas- BA. Horticultura Brasileira, Brasília, DF, v. 15, 1997. Resumo 281. Suplemento. Edição dos Resumos do 37 Congresso Brasileiro de Olericultura, Manaus, 1997.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Semiárido. |
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| Registros recuperados : 327 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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