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Registro Completo |
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Biblioteca(s): |
Embrapa Arroz e Feijão; Embrapa Solos. |
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Data corrente: |
04/04/2022 |
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Data da última atualização: |
05/04/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
KUCHLER, P. C.; SIMÕES, M.; FERRAZ, R. P. D.; ARVOR, D.; MACHADO, P. L. O. de A.; ROSA, M.; GAETANO, R.; BÉGUÉ, A. |
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Afiliação: |
PATRICK CALVANO KUCHLER, UERJ; MARGARETH GONCALVES SIMOES, CNPS; RODRIGO PECANHA DEMONTE FERRAZ, CNPS; DAMIEN ARVOR, UNIVERSITÉ RENNES; PEDRO LUIZ OLIVEIRA DE A MACHADO, CNPAF; MARCOS ROSA, UNIVERSIDADE ESTADUAL DE FEIRA DE SANTANA; RAFFAELE GAETANO, CIRAD; AGNÈS BÉGUÉ, CIRAD. |
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Título: |
Monitoring complex integrated crop-livestock systems at regional scale in Brazil: a big earth observation data approach. |
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Ano de publicação: |
2022 |
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Fonte/Imprenta: |
Remote Sensing, v. 14, n. 7, 1648, 2022. |
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DOI: |
https://doi.org/10.3390/rs14071648 |
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Idioma: |
Inglês |
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Conteúdo: |
Due to different combinations of agriculture, livestock and forestry managed by rotation, succession and intercropping practices, integrated agriculture production systems such as integrated crop-livestock systems (iCL) constitute a very complex target and a challenge for automatic mapping of cropping practices based on remote sensing data. The overall objective of this study was to develop a classification strategy for the annual mapping of integrated Crop-Livestock systems (iCL) at a regional scale. This strategy was designed and tested in the six agro-climatic regions of Mato Grosso, the largest Brazilian soybean producer state, using MODIS satellite time-series images acquired between 2012 and 2019, ground data with heterogeneous distribution in space and time and a Random Forest classifier. The results showed that: 1. the use of unbalanced training samples with a class composition close to the real one was the right classifier training strategy; 2. the use of a single training database (pooling samples from different years and regions) to classify each region and year individually proved to be robust enough to provide similar classification accuracies in comparison to those based on the use of a database acquired for each region and for each year. The final hierarchical classification overall accuracy was 0.89 for Level 1, the cropping pattern level (single and double crops DC); 0.84 for Level 2, the DC category level (integrated system iCL soy-pasture/brachiaria, soy-cotton and soy-cereal); 0.77 for Level 3, the iCL level (iCL1 soy-pasture and iCL2 soy-pasture mixed with corn). The F-scores for DC, iCL and iCL1 cropping systems presented high accuracy (0.89, 0.85 and 0.84), while iCL2 was more difficult to classify (0.63). This approach will next be applied across the entire Brazilian soybean corridor, leading to an operational tool for monitoring the adoption of sustainable intensification practices recognized by Brazil's Agriculture Low Carbon Plan (ABC PLAN). MenosDue to different combinations of agriculture, livestock and forestry managed by rotation, succession and intercropping practices, integrated agriculture production systems such as integrated crop-livestock systems (iCL) constitute a very complex target and a challenge for automatic mapping of cropping practices based on remote sensing data. The overall objective of this study was to develop a classification strategy for the annual mapping of integrated Crop-Livestock systems (iCL) at a regional scale. This strategy was designed and tested in the six agro-climatic regions of Mato Grosso, the largest Brazilian soybean producer state, using MODIS satellite time-series images acquired between 2012 and 2019, ground data with heterogeneous distribution in space and time and a Random Forest classifier. The results showed that: 1. the use of unbalanced training samples with a class composition close to the real one was the right classifier training strategy; 2. the use of a single training database (pooling samples from different years and regions) to classify each region and year individually proved to be robust enough to provide similar classification accuracies in comparison to those based on the use of a database acquired for each region and for each year. The final hierarchical classification overall accuracy was 0.89 for Level 1, the cropping pattern level (single and double crops DC); 0.84 for Level 2, the DC category level (integrated system iCL soy-pasture/brachiaria, soy-c... Mostrar Tudo |
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Palavras-Chave: |
Big data; Hierarchical classification; Machine learning; MODIS; Samples balancing; Satellite image time series; Training sample designs. |
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Thesagro: |
Agricultura Sustentável. |
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Thesaurus Nal: |
Cropping systems; Double cropping; Sustainable agriculture. |
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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/doc/1141783/1/Monitoring-complex-integrated-crop-livestock-systems-at-regional-scale-in-Brazil-2022.pdf
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Marc: |
LEADER 03062naa a2200349 a 4500
001 2141783
005 2022-04-05
008 2022 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.3390/rs14071648$2DOI
100 1 $aKUCHLER, P. C.
245 $aMonitoring complex integrated crop-livestock systems at regional scale in Brazil$ba big earth observation data approach.$h[electronic resource]
260 $c2022
520 $aDue to different combinations of agriculture, livestock and forestry managed by rotation, succession and intercropping practices, integrated agriculture production systems such as integrated crop-livestock systems (iCL) constitute a very complex target and a challenge for automatic mapping of cropping practices based on remote sensing data. The overall objective of this study was to develop a classification strategy for the annual mapping of integrated Crop-Livestock systems (iCL) at a regional scale. This strategy was designed and tested in the six agro-climatic regions of Mato Grosso, the largest Brazilian soybean producer state, using MODIS satellite time-series images acquired between 2012 and 2019, ground data with heterogeneous distribution in space and time and a Random Forest classifier. The results showed that: 1. the use of unbalanced training samples with a class composition close to the real one was the right classifier training strategy; 2. the use of a single training database (pooling samples from different years and regions) to classify each region and year individually proved to be robust enough to provide similar classification accuracies in comparison to those based on the use of a database acquired for each region and for each year. The final hierarchical classification overall accuracy was 0.89 for Level 1, the cropping pattern level (single and double crops DC); 0.84 for Level 2, the DC category level (integrated system iCL soy-pasture/brachiaria, soy-cotton and soy-cereal); 0.77 for Level 3, the iCL level (iCL1 soy-pasture and iCL2 soy-pasture mixed with corn). The F-scores for DC, iCL and iCL1 cropping systems presented high accuracy (0.89, 0.85 and 0.84), while iCL2 was more difficult to classify (0.63). This approach will next be applied across the entire Brazilian soybean corridor, leading to an operational tool for monitoring the adoption of sustainable intensification practices recognized by Brazil's Agriculture Low Carbon Plan (ABC PLAN).
650 $aCropping systems
650 $aDouble cropping
650 $aSustainable agriculture
650 $aAgricultura Sustentável
653 $aBig data
653 $aHierarchical classification
653 $aMachine learning
653 $aMODIS
653 $aSamples balancing
653 $aSatellite image time series
653 $aTraining sample designs
700 1 $aSIMÕES, M.
700 1 $aFERRAZ, R. P. D.
700 1 $aARVOR, D.
700 1 $aMACHADO, P. L. O. de A.
700 1 $aROSA, M.
700 1 $aGAETANO, R.
700 1 $aBÉGUÉ, A.
773 $tRemote Sensing$gv. 14, n. 7, 1648, 2022.
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Registro original: |
Embrapa Solos (CNPS) |
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| Registros recuperados : 190 | |
| 81. |  | MACHADO, C. de S.; SOUZA, R. de O.; ALVES, T. M.; MACHADO, P. L. O. de A.; QUINTELA, E. D.; BARRIGOSSI, J. A. F. Fauna do solo da cultura do arroz cultivado sobre diferentes coberturas em plantio direto. In: SEMINÁRIO JOVENS TALENTOS, 4., 2010, Santo Antônio de Goiás. Resumos apresentados. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2010. p. 16. (Embrapa Arroz e Feijão. Documentos, 257).| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 83. | | MACHADO, P. L. O. de A; DUNN, W. A.; OLIVEIRA, E. L. de; SOHI, S. P.; POULTON, P. R.; GAUNT, J. L. The effects of tillage and crop rotation on organic matter content and distribution. In: REUNIAO BRASILEIRA DE FERTILIDADE DE SOLO E NUTRICAO DE PLANTAS, 23.; REUNIAO BRASILEIRA SOBRE MICORRIZAS, 7.; SIMPOSIO BRASILEIRO DE MICROBIOLOGIA DO SOLO, 5.; REUNIAO BRASILEIRA DE BIOLOGIA DO SOLO, 2., 1998, Caxambu, MG.Resumos... Lavras: UFLA /SBCS / SBM, 1998. p.119. FERTBIO 98: Interrelacao fertilidade, biologia do solo e nutricao de plantas: consolidacao de um paradigma.| Biblioteca(s): Embrapa Solos. |
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| 84. | | LIMA, M. de L.; MEDEIROS, J. C.; OLIVEIRA, D. G. de; STONE, L. F.; MACHADO, P. L. O. de A.; MADARI, B. E. Integração lavoura-pecuária no Cerrado: caracterização físico-hídrica de um latossolo vermelho. In: SILVA JÚNIOR, M. G. da; UCKER, F. E. (org.). Gestão, monitoramento e recuperação dos recursos naturais: do desenvolvimento a sustentabilidade. Rio de Janeiro: e-Publicar, 2020. Capítulo 4, p. 45-60.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 85. | | BERNARDI, A. C. de C.; TADINI, A. M.; BIELUCZYK, W.; PEZZOPANE, J. R. M.; MACHADO, P. L. O. de A.; MADARI, B. E.; MARTIN NETO, L. Manejo conservacionista da matéria orgânica do solo: sistema de integração lavoura-pecuária-floresta. BETTIOL, W.; SILVA, C. A.; CERRI, C. E. P.; MARTIN NETO, L.; ANDRADE, C. A. de (ed.). Entendendo a matéria orgânica do solo em ambientes tropical e subtropical. Brasília, DF: Embrapa, 2023. p. 569-600. ODS 7 - Energia acessível e limpa, ODS 13 - Ação contra a mudança global do clima.| Tipo: Capítulo em Livro Técnico-Científico |
| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Instrumentação; Embrapa Pecuária Sudeste. |
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| 88. | | MACHADO, P. L. O. de A.; SANTOS, H. P. dos; FREIXO, A. A.; OLIVEIRA, E. L. de; SILVA, C. A.; CONCEICAO, M. da; GAUNT, J. L. Long-term effects of no tillage on carbon sequestration of two oxisols from South Brazil. In: CONGRESO LATINOAMERICANO DE LA CIENCIA DEL SUELO, 14.; CONGRESO DE LA SOCIEDAD AGRONOMICA DE CHILE, 50.; CONGRESO NACIONAL DE LA CIENCIA DEL SUELO, 9., 1999, Temuco, Chile. Resumenes... Temuco: Universidad de la Frontera, 1999. p. 660.| Biblioteca(s): Embrapa Solos. |
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| 89. | | WADT, P. G. S.; SILVA, D. J.; MAIA, C. E.; TOME JUNIOR, J. B.; PINTO, P. A. da C.; MACHADO, P. L. O. de A. Modelagem de funções no cálculo dos índices DRIS. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 42, n. 1, p. 57-64, 2007.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: Nacional - A |
| Biblioteca(s): Embrapa Acre; Embrapa Arroz e Feijão; Embrapa Semiárido; Embrapa Unidades Centrais. |
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| 91. | | SOARES, R.; MADDOCK, J. E. L.; CAMPOS, D. V. B. de; MADARI, B. E.; MACHADO, P. L. O. de A.; SANTELLI, R. E. Seriam as Terras Pretas de índio marcadores ambientais da Idade Meghalayan ou da Época do Antropoceno? In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE QUÍMICA, 42., 2019, Joinville. Eixos mobilizadores em Química: programa e resumos. São Paulo: Sociedade Brasileira de Química, 2019.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Solos. |
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| 92. | | SANTOS, J. L. S.; MADARI, B. E.; COSTA, A. R. da; MACHADO, P. L. O. de A.; FERNANDES, E. P.; CARNEVALLI, R. A. Qualidade do solo em sistema integração lavoura-pecuária, no cerrado. In: WORKSHOP INTEGRAÇÃO LAVOURA-PECUÁRIA-FLORESTA NA EMBRAPA, Brasília, DF, 2009. Resumos e palestras apresentados. Brasília, DF: Embrapa, 2009.| Tipo: Artigo em Anais de Congresso / Nota Técnica |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 94. | | SIQUEIRA, F. C. de J.; MADARI, B. E.; CARVALHO, M. T. de M.; COSTA, A. R. da; MACHADO, P. L. O. de A. Perdas de nitrogênio por emissão de óxido nitroso (N2O) no feijoeiro irrigado. In: SEMINÁRIO JOVENS TALENTOS, 6., 2012, Santo Antônio de Goiás. Resumos apresentados. Santo Antônio de Goiás: Embrapa Arroz e Feijão, 2012. p. 43. (Embrapa Arroz e Feijão. Documentos, 275).| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 96. | | SOARES, R.; MADDOCK, J. E. L.; CAMPOS, D. V. B. de; MADARI, B. E.; MACHADO, P. L. O. de A.; SANTELLI, R. E. O papel das Terras Pretas de Índio no Antropoceno. Revista Virtual de Química, v. 10, n. 6, p. 1659-1692, nov./dez. 2018.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Solos. |
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| 98. | | KUCHLER, P. C.; SIMÕES, M.; BÉGUÉ, A.; MACHADO, P. L. O. de A.; FERRAZ, R. P. D.; MADARI, B. E.; FREITAS, P. L. de; MANZATTO, C. V. Monitoring Brazilian low-carbon agriculture plan: the potential of remote sensing to detect adoption of selected agricultural practices. In: EFITA WCCA CONGRESS, 2017, Montpellier. Conference proceedings. Montpellier: Efita, 2017. p. 169-170.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Arroz e Feijão. |
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| 99. | | KUCHLER, P. C.; SIMÕES, M.; BÉGUÉ, A.; MACHADO, P. L. O. de A.; FERRAZ, R. P. D.; MADARI, B. E.; FREITAS, P. L. de; MANZATTO, C. V. Monitoring Brazilian low-carbon agriculture plan: the potential of remote sensing to detect adoption of selected agricultural practices. In: EFITA WCCA CONGRESS, 2017, Montpellier. Conference proceedings. Montpellier: Efita, 2017. p. 169-170.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Solos. |
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| 100. | | KUCHLER, P. C.; SIMÕES, M.; FERRAZ, R. P. D.; ARVOR, D.; MACHADO, P. L. O. de A.; ROSA, M.; GAETANO, R.; BÉGUÉ, A. Monitoring complex integrated crop-livestock systems at regional scale in Brazil: a big earth observation data approach. Remote Sensing, v. 14, n. 7, 1648, 2022.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 1 |
| Biblioteca(s): Embrapa Arroz e Feijão; Embrapa Solos. |
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| Registros recuperados : 190 | |
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| Nenhum registro encontrado para a expressão de busca informada. |
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