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Registro Completo |
Biblioteca(s): |
Embrapa Gado de Leite. |
Data corrente: |
18/12/2007 |
Data da última atualização: |
13/12/2022 |
Tipo da produção científica: |
Circular Técnica |
Autoria: |
OLIVEIRA, J. S. e; SOUZA SOBRINHO, F de; LANES, E. C. M. de; ALMEIDA, E. J. D. de. |
Afiliação: |
Jackson Silva e Oliveira, Embrapa Gado de Leite; Fausto de Souza Sobrinho, Embrapa Gado de Leite; Éder Cristian Malta de Lanes, Centro de Ensino Superior de Juiz de Fora; Emerson José Dornelas de Almeida, UFJF. |
Título: |
Avaliação de cultivares de milho para silagem: resultados do ano agrícola 2005/2006. |
Ano de publicação: |
2007 |
Fonte/Imprenta: |
Juiz de Fora: Embrapa Gado de Leite, 2007. |
Páginas: |
16 p. |
Série: |
(Embrapa Gado de Leite. Circular Técnica, 91). |
ISSN: |
1517-4816 |
Idioma: |
Português |
Palavras-Chave: |
avaliação; cultivares. |
Thesagro: |
Milho; Produtividade; Silagem; Valor Nutritivo. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/65274/1/CT-91-Cultiv-milho-silagem.pdf
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Marc: |
LEADER 00702nam a2200241 a 4500 001 1596677 005 2022-12-13 008 2007 bl uuuu u0uu1 u #d 022 $a1517-4816 100 1 $aOLIVEIRA, J. S. e 245 $aAvaliação de cultivares de milho para silagem$bresultados do ano agrícola 2005/2006. 260 $aJuiz de Fora: Embrapa Gado de Leite$c2007 300 $a16 p. 490 $a(Embrapa Gado de Leite. Circular Técnica, 91). 650 $aMilho 650 $aProdutividade 650 $aSilagem 650 $aValor Nutritivo 653 $aavaliação 653 $acultivares 700 1 $aSOUZA SOBRINHO, F de 700 1 $aLANES, E. C. M. de 700 1 $aALMEIDA, E. J. D. de
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Embrapa Gado de Leite (CNPGL) |
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Registro Completo
Biblioteca(s): |
Embrapa Cerrados. |
Data corrente: |
14/12/2020 |
Data da última atualização: |
14/12/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
ARAI, E.; SANO, E. E.; DUTRA. A. C.; CASSOL, H. L. G.; HOFFMANN, T. B.; SHIMABUKURO, Y. E. |
Afiliação: |
EDSON EYJI SANO, CPAC. |
Título: |
Vegetation Fraction Images Derived from PROBA-V Data for Rapid Assessment of Annual Croplands in Brazil. |
Ano de publicação: |
2020 |
Fonte/Imprenta: |
Remote Sensing, v. 12, n. 7, 2020. |
ISSN: |
2072-4292 |
Idioma: |
Português |
Conteúdo: |
Abstract: This paper presents a new method for rapid assessment of the extent of annual croplands in Brazil. The proposed method applies a linear spectral mixing model (LSMM) to PROBA-V time series images to derive vegetation, soil, and shade fraction images for regional analysis. We used S10-TOC (10 days synthesis, 1 km spatial resolution, and top-of-canopy) products for Brazil and S5-TOC (five days synthesis, 100 m spatial resolution, and top-of-canopy) products for Mato Grosso State (Brazilian Legal Amazon). Using the time series of the vegetation fraction images of the whole year (2015 in this case), only one mosaic composed with maximum values of vegetation fraction was generated, allowing detecting and mapping semi-automatically the areas occupied by annual crops during the year. The results (100 m spatial resolution map) for the Mato Grosso State were compared with existing global datasets (Finer Resolution Observation and Monitoring?Global Land Cover (FROM-GLC) and Global Food Security?Support Analyses Data (GFSAD30)). Visually those maps present a good agreement, but the area estimated are not comparable since the agricultural class definition are different for those maps. In addition, we found 11.8 million ha of agricultural areas in the entire Brazilian territory. The area estimation for the Mato Grosso State was 3.4 million ha for 1 km dataset and 5.3 million ha for 100 m dataset. This difference is due to the spatial resolution of the PROBA-V datasets used. A coefficient of determination of 0.82 was found between PROBA-V 100 m and Landsat-8 OLI area estimations for the Mato Grosso State. Therefore, the proposed method is suitable for detecting and mapping annual croplands distribution operationally using PROBA-V datasets for regional analysis. MenosAbstract: This paper presents a new method for rapid assessment of the extent of annual croplands in Brazil. The proposed method applies a linear spectral mixing model (LSMM) to PROBA-V time series images to derive vegetation, soil, and shade fraction images for regional analysis. We used S10-TOC (10 days synthesis, 1 km spatial resolution, and top-of-canopy) products for Brazil and S5-TOC (five days synthesis, 100 m spatial resolution, and top-of-canopy) products for Mato Grosso State (Brazilian Legal Amazon). Using the time series of the vegetation fraction images of the whole year (2015 in this case), only one mosaic composed with maximum values of vegetation fraction was generated, allowing detecting and mapping semi-automatically the areas occupied by annual crops during the year. The results (100 m spatial resolution map) for the Mato Grosso State were compared with existing global datasets (Finer Resolution Observation and Monitoring?Global Land Cover (FROM-GLC) and Global Food Security?Support Analyses Data (GFSAD30)). Visually those maps present a good agreement, but the area estimated are not comparable since the agricultural class definition are different for those maps. In addition, we found 11.8 million ha of agricultural areas in the entire Brazilian territory. The area estimation for the Mato Grosso State was 3.4 million ha for 1 km dataset and 5.3 million ha for 100 m dataset. This difference is due to the spatial resolution of the PROBA-V datasets used. A co... Mostrar Tudo |
Palavras-Chave: |
Fração máxima; Mapeamento de terras agrícolas; Mato Grosso. |
Thesagro: |
Cerrado; Sensoriamento Remoto. |
Categoria do assunto: |
-- |
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/219147/1/SANO-VEGETATION-FRACTION-IMAGES-DERIVED.pdf
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Marc: |
LEADER 02519naa a2200253 a 4500 001 2128068 005 2020-12-14 008 2020 bl uuuu u00u1 u #d 022 $a2072-4292 100 1 $aARAI, E. 245 $aVegetation Fraction Images Derived from PROBA-V Data for Rapid Assessment of Annual Croplands in Brazil.$h[electronic resource] 260 $c2020 520 $aAbstract: This paper presents a new method for rapid assessment of the extent of annual croplands in Brazil. The proposed method applies a linear spectral mixing model (LSMM) to PROBA-V time series images to derive vegetation, soil, and shade fraction images for regional analysis. We used S10-TOC (10 days synthesis, 1 km spatial resolution, and top-of-canopy) products for Brazil and S5-TOC (five days synthesis, 100 m spatial resolution, and top-of-canopy) products for Mato Grosso State (Brazilian Legal Amazon). Using the time series of the vegetation fraction images of the whole year (2015 in this case), only one mosaic composed with maximum values of vegetation fraction was generated, allowing detecting and mapping semi-automatically the areas occupied by annual crops during the year. The results (100 m spatial resolution map) for the Mato Grosso State were compared with existing global datasets (Finer Resolution Observation and Monitoring?Global Land Cover (FROM-GLC) and Global Food Security?Support Analyses Data (GFSAD30)). Visually those maps present a good agreement, but the area estimated are not comparable since the agricultural class definition are different for those maps. In addition, we found 11.8 million ha of agricultural areas in the entire Brazilian territory. The area estimation for the Mato Grosso State was 3.4 million ha for 1 km dataset and 5.3 million ha for 100 m dataset. This difference is due to the spatial resolution of the PROBA-V datasets used. A coefficient of determination of 0.82 was found between PROBA-V 100 m and Landsat-8 OLI area estimations for the Mato Grosso State. Therefore, the proposed method is suitable for detecting and mapping annual croplands distribution operationally using PROBA-V datasets for regional analysis. 650 $aCerrado 650 $aSensoriamento Remoto 653 $aFração máxima 653 $aMapeamento de terras agrícolas 653 $aMato Grosso 700 1 $aSANO, E. E. 700 1 $aDUTRA. A. C. 700 1 $aCASSOL, H. L. G. 700 1 $aHOFFMANN, T. B. 700 1 $aSHIMABUKURO, Y. E. 773 $tRemote Sensing$gv. 12, n. 7, 2020.
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