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Registro Completo |
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Biblioteca(s): |
Embrapa Amazônia Oriental. |
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Data corrente: |
29/01/2020 |
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Data da última atualização: |
29/01/2020 |
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Autoria: |
CARVALHO, C. J. R. de (coord.). |
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Afiliação: |
CLAUDIO JOSE REIS DE CARVALHO, CPATU. |
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Título: |
Desenvolvimento de metodologia para monitoramento químico-atmosférico da Amazônia no experimento LBA. |
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Ano de publicação: |
2002 |
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Fonte/Imprenta: |
In: BRASIL. Ministério da Ciência e Tecnologia. Livro de resultados dos projetos de pesquisa dirigida (PPDs) - PPG7. Brasília, DF, 2002. |
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Páginas: |
p. 47-51. |
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Idioma: |
Português |
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Thesagro: |
Clima; Impacto Ambiental; Uso da Terra. |
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Categoria do assunto: |
-- |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/209880/1/Desenvolvimentto-de-metodologia.pdf
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Marc: |
LEADER 00569naa a2200157 a 4500
001 2119564
005 2020-01-29
008 2002 bl uuuu u00u1 u #d
100 1 $aCARVALHO, C. J. R. de
245 $aDesenvolvimento de metodologia para monitoramento químico-atmosférico da Amazônia no experimento LBA.
260 $c2002
300 $ap. 47-51.
650 $aClima
650 $aImpacto Ambiental
650 $aUso da Terra
773 $tIn: BRASIL. Ministério da Ciência e Tecnologia. Livro de resultados dos projetos de pesquisa dirigida (PPDs) - PPG7. Brasília, DF, 2002.
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Registro original: |
Embrapa Amazônia Oriental (CPATU) |
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 | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
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Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
19/12/2013 |
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Data da última atualização: |
08/01/2020 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
COLTRI, P. P.; ZULLO JÚNIOR, J.; GONÇALVES, R. R. do V.; ROMANI, L. A. S.; PINTO, H. S. |
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Afiliação: |
PRISCILA PEREIRA COLTRI, Cepagri/Unicamp; JURANDIR ZULLO JÚNIOR, Cepagri/Unicamp; RENATA RIBEIRO DO VALLE GONÇALVES, Cepagri/Unicamp; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; HILTON SILVEIRA PINTO, Cepagri/Unicamp. |
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Título: |
Coffee crop's biomass and carbon stock estimation with usage of high resolution satellites images. |
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Ano de publicação: |
2013 |
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Fonte/Imprenta: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 6, n. 3, p. 1786-1795, June 2013. |
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Idioma: |
Inglês |
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Conteúdo: |
Abstract-Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee´s biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created. |
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Palavras-Chave: |
Biophysical properties; Coffee arabica; Índice de vegetação; Propriedades biofísicas. |
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Thesagro: |
Biomassa; Café. |
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Thesaurus NAL: |
Biomass; vegetation index. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02104naa a2200265 a 4500
001 1974355
005 2020-01-08
008 2013 bl uuuu u00u1 u #d
100 1 $aCOLTRI, P. P.
245 $aCoffee crop's biomass and carbon stock estimation with usage of high resolution satellites images.$h[electronic resource]
260 $c2013
520 $aAbstract-Coffee is one of the most important crops in Brazil. Monitoring the crop is necessary to understand future production and a sound understanding of coffee´s biophysical properties improves such monitoring. Biophysical properties such as dry biomass can be estimated using remote sensing, including the new generation of high-resolution images (GeoEye-1, for instance). In this study we aim to investigate the relationship between vegetation indices (VI) of high-resolution images (GeoEye-1) and coffee biophysical properties, including dry biomass and carbon. The study also aims at establishing an empirical relationship between remote sensing data (vegetation indices), simple field measurements and dry biomass, allowing calculation of coffee biomass and carbon without resorting to destructive methods. Individual GeoEye-1 satellite's bands (NIR, RED and GREEN) showed significant correlation with biomass, but the best correlation occurred with vegetation index. There is a strong correlation between NDVI, RVI, GNDVI and dry biomass, allowing the estimation of coffee crops' carbon stock. RVI had correlation with plant area index (PAI). The empirical correlation was established and the forecast equation of coffee biomass was created.
650 $aBiomass
650 $avegetation index
650 $aBiomassa
650 $aCafé
653 $aBiophysical properties
653 $aCoffee arabica
653 $aÍndice de vegetação
653 $aPropriedades biofísicas
700 1 $aZULLO JÚNIOR, J.
700 1 $aGONÇALVES, R. R. do V.
700 1 $aROMANI, L. A. S.
700 1 $aPINTO, H. S.
773 $tIEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing$gv. 6, n. 3, p. 1786-1795, June 2013.
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Embrapa Agricultura Digital (CNPTIA) |
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