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Registros recuperados : 73 | |
21. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | GHINI, R.; HAMADA, E.; PEDRO JÚNIOR, M. J.; GONÇALVES, R. R. V. Efeito de mudanças climáticas globais sobre o período de incubação da ferrugem do cafeeiro. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 39., 2006, Salvador, BA. Resumos... Salvador, BA: SBF, 2006. Revista Fitopatologia Brasileira, Brasília, DF, v.31, supl., p. S.172, ago. 2006. Biblioteca(s): Embrapa Meio Ambiente. |
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26. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | SANTOS, A. K. V. dos; GONÇALVES, R. R.; REIS, A.; CORREIA, K. C.; MICHEREFF, S. J. Diversidade cultural de isolados de Rhizoctonia solani do grupo de anastomose AG-1 IB associados com a queima-da-saia em alface no Brasil. In: CONGRESSO BRASILEIRO DE FITOPATOLOGIA, 51., 2019, Recife. Anais... Brasília, DF: Sociedade Brasileira de Fitopatologia, 2019. p. 503. Resumo. Biblioteca(s): Embrapa Hortaliças. |
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31. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | GONÇALVES, R. R. V.; NASCIMENTO, C. R.; J. ZULLO JÚNIOR; ROMANI, L. A. S. Relationship between the spectral response of sugar cane, based on AVHRR/NOAA satellite images, and the climate condition, in the state of São Paulo (Brazil), from 2001 to 2008. In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn, 2009. p. 315-322. MultiTemp 2009. Biblioteca(s): Embrapa Agricultura Digital. |
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32. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | GHINI, R.; HAMADA, E.; GONÇALVES, R. R. V.; GASPAROTTO, L.; PEREIRA, J. C. R. Risk analysis of climate change on black sigatoka in banana in Brazil. In: Journal of Plant Pathology, Pisa, v.90, n.2, supl., p.S2.105, Aug. 2008. ICPP 2008 - 9. International Congress of Plant Pathology, 2008, Torino. Abstracts of invited and offered papers. Biblioteca(s): Embrapa Amazônia Ocidental; Embrapa Meio Ambiente. |
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33. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | GHINI, R.; HAMADA, E.; PEDRO JÚNIOR, M. J.; MARENGO, J. A.; GONÇALVES, R. R. V. Risk analysis of climate change on coffee nematodes and leaf miner in Brazil. Pesquisa Agropecuária Brasileira, Brasília, v. 43, n. 2, p.187-194, fev. 2008. Biblioteca(s): Embrapa Meio Ambiente; Embrapa Unidades Centrais. |
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40. | ![Imagem marcado/desmarcado](/consulta/web/img/desmarcado.png) | GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; ROMANI, L. A. S.; NASCIMENTO, C. R.; TRAINA, A. J. M. Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil. International Journal of Remote Sensing, Basingstoke, v. 33, n. 15, p. 4653-4672, Aug. 2012. Biblioteca(s): Embrapa Agricultura Digital. |
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![](/consulta/web/img/deny.png) | Acesso ao texto completo restrito à biblioteca da Embrapa Agricultura Digital. Para informações adicionais entre em contato com cnptia.biblioteca@embrapa.br. |
Registro Completo
Biblioteca(s): |
Embrapa Agricultura Digital. |
Data corrente: |
19/12/2013 |
Data da última atualização: |
08/01/2020 |
Tipo da produção científica: |
Artigo em Periódico Indexado |
Circulação/Nível: |
A - 1 |
Autoria: |
COLTRI, P. P.; ZULLO JÚNIOR, J.; GONÇALVES, R. R. do V.; ROMANI, L. A. S.; PINTO, H. S. |
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. |
Título: |
Coffee crop's biomass and carbon stock estimation with usage of high resolution satellites images. |
Ano de publicação: |
2013 |
Fonte/Imprenta: |
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, v. 6, n. 3, p. 1786-1795, June 2013. |
Idioma: |
Inglês |
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. |
Palavras-Chave: |
Biophysical properties; Coffee arabica; Índice de vegetação; Propriedades biofísicas. |
Thesagro: |
Biomassa; Café. |
Thesaurus NAL: |
Biomass; vegetation index. |
Categoria do assunto: |
-- |
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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