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| Registros recuperados : 73 | |
| 21. |  | 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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| 26. | | HAMADA, E.; GHINI, R.; GONÇALVES, R. R. V.; PEREIRA, D. A. Avaliação do efeito de mudança climática sobre problemas fitossanitários: comparação de métodos de elaboração de mapas. In: CONGRESSO BRASILEIRO DE BIOMETEOROLOGIA, 4., 2006, Ribeirão Preto,SP. [Anais...]. Ribeirão Preto, SP: SBB, IZ, 2006. p. 1-5.| Biblioteca(s): Embrapa Meio Ambiente. |
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| 27. | | GHINI, R.; HAMADA, E.; GONÇALVES, R. R. V.; GASPAROTTO, L.; PEREIRA, J. C. R. Análise de risco das mudanças climáticas globais sobre a sigatoka-negra da bananeira no Brasil. Fitopatologia Brasileira, Brasília, v.32, n.3, p.197-204, 2007.| Biblioteca(s): Embrapa Amazônia Ocidental; Embrapa Meio Ambiente. |
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| 30. | | 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. | | 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. | | 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. | | 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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| Registros recuperados : 73 | |
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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
|
Biblioteca(s): |
Embrapa Agricultura Digital. |
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Data corrente: |
27/02/2012 |
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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 - 2 |
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Autoria: |
GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; ROMANI, L. A. S.; NASCIMENTO, C. R.; TRAINA, A. J. M. |
|
Afiliação: |
RENATA R. V. GONÇALVES, Feagri/Unicamp; JURANDIR ZULLO JÚNIOR, Cepagri/Unicamp; LUCIANA ALVIM SANTOS ROMANI, CNPTIA; CRISTINA R. NASCIMENTO, Feagri/Unicamp; AGMA J. M. TRAINA, ICMC/USP. |
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Título: |
Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil. |
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Ano de publicação: |
2012 |
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Fonte/Imprenta: |
International Journal of Remote Sensing, Basingstoke, v. 33, n. 15, p. 4653-4672, Aug. 2012. |
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Idioma: |
Inglês |
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Conteúdo: |
Brazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international marketplaces. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast. |
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Palavras-Chave: |
Análise de séries temporais; Imagens NDVI; Métodos estatísticos; Modelos de previsão; Monitoramento de cana-de-açúcar. |
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Thesagro: |
Análise Estatística. |
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Thesaurus NAL: |
Models; Statistical analysis; Sugarcane; Time series analysis. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
|
Marc: |
LEADER 02134naa a2200289 a 4500
001 1916734
005 2020-01-08
008 2012 bl uuuu u00u1 u #d
100 1 $aGONÇALVES, R. R. V.
245 $aAnalysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil.$h[electronic resource]
260 $c2012
520 $aBrazil is the largest sugarcane producer in the world and has a privileged position to attend to national and international marketplaces. To maintain the high production of sugarcane, it is fundamental to improve the forecasting models of crop seasons through the use of alternative technologies, such as remote sensing. Thus, the main purpose of this article is to assess the results of two different statistical forecasting methods applied to an agroclimatic index (the water requirement satisfaction index; WRSI) and the sugarcane spectral response (normalized difference vegetation index; NDVI) registered on National Oceanic and Atmospheric Administration Advanced Very High Resolution Radiometer (NOAA-AVHRR) satellite images. We also evaluated the cross-correlation between these two indexes. According to the results obtained, there are meaningful correlations between NDVI and WRSI with time lags. Additionally, the adjusted model for NDVI presented more accurate results than the forecasting models for WRSI. Finally, the analyses indicate that NDVI is more predictable due to its seasonality and the WRSI values are more variable making it difficult to forecast.
650 $aModels
650 $aStatistical analysis
650 $aSugarcane
650 $aTime series analysis
650 $aAnálise Estatística
653 $aAnálise de séries temporais
653 $aImagens NDVI
653 $aMétodos estatísticos
653 $aModelos de previsão
653 $aMonitoramento de cana-de-açúcar
700 1 $aZULLO JÚNIOR, J.
700 1 $aROMANI, L. A. S.
700 1 $aNASCIMENTO, C. R.
700 1 $aTRAINA, A. J. M.
773 $tInternational Journal of Remote Sensing, Basingstoke$gv. 33, n. 15, p. 4653-4672, Aug. 2012.
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