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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 |
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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Registros recuperados : 49 | |
6. | | 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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7. | | TRABAQUINI, K.; SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; GALVÃO, L. S. Dynamics and distribution of anthropic occupation in the Cerrado of Mato Grosso in the period from 1990 to 2008. Geografia, Rio Claro, v. 38, n. 2, p. 209-224, maio/ago. 2013. p. 209-224Tipo: Artigo em Periódico Indexado | Circulação/Nível: A - 2 |
Biblioteca(s): Embrapa Territorial. |
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8. | | SILVA, G. B. S. da; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; ADAMI, M.; SANO, E. E. Discriminação da cobertura vegetal do Cerrado matogrossense por meio de imagens MODIS. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 45, n. 2, p. 186-194, fev. 2010 Título em inglês: Discrimination of Cerrado vegetation cover in the state of Mato Grosso using MODIS images.Biblioteca(s): Embrapa Unidades Centrais. |
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13. | | ADAMI, M.; FREITAS, R. M. de; PADOVANI, C. R.; SHIMABUKURO, Y. E.; MOREIRA, M. A. Estudo da dinâmica espaço-temporal do bioma Pantanal por meio de imagens MODIS. Pesquisa Agropecuária Brasileira, Brasília, DF, v. 43, n. 10, p. 1371-1378, out. 2008. Título em inglês: Spatial-temporal analysis of MODIS image applied to dynamic of Pantanal biome.Biblioteca(s): Embrapa Unidades Centrais. |
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14. | | WALKER, R.; DeFRIES, R.; VERA-DIAZ, M. del C.; SHIMABUKURO, Y.; VENTURIERI, A. The expansion of intensive agriculture and ranching in brazilian Amazonia. In: KELLER, M.; BUSTAMANTE, M.; GASH, J.; DIAS, P. S. (Ed.). Amazonia and global change. Washington, DC: American Geophysical Union, 2009. p. 61-81. (Geophysical monograph series, 186).Tipo: Capítulo em Livro Técnico-Científico |
Biblioteca(s): Embrapa Amazônia Oriental. |
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15. | | PADOVANI, C. R.; SHIMABUKURO, Y. E.; FREITAS, R. M.; ADAMI, M.; VETTORAZZI, C. A. Spatial analysis of Pantanal wetland flood dynamics determined from modis images: a case study . In: INTECOL INTERNATIONAL WETLANDS CONFERENCE, 8., Cuiabá, 2008. Big wetlands, big concerns: abstracts. [Sl.: s.n], 2008. p.160Tipo: Resumo em Anais de Congresso |
Biblioteca(s): Embrapa Pantanal. |
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20. | | MIURA, A. K.; FORMAGGIO, A. R.; SHIMABUKURO, Y. E.; ANJOS, S. D. dos; LUIZ, A. J. B. Avaliação de áreas potenciais ao cultivo de biomassa para produção de energia e uma contribuição de sensoriamento remoto e sistemas de informações geográficas. Engenharia Agrícola, Jaboticabal, v. 31, n. 3, p. 607-620, maio/jun. 2011.Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
Biblioteca(s): Embrapa Clima Temperado; Embrapa Meio Ambiente. |
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Registros recuperados : 49 | |
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