Data/hora: 19/06/2024 13:24:21

Biblioteca(s): 	Embrapa Agricultura Digital.	
Data corrente: 	27/02/2012	
Data da última atualização: 	08/01/2020	
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.	
Título: 	Analysis of NDVI time series using cross-correlation and forecasting methods for monitoring sugarcane fields in Brazil.	
Ano de publicação: 	2012	
Fonte/Imprenta: 	International Journal of Remote Sensing, Basingstoke, v. 33, n. 15, p. 4653-4672, Aug. 2012.	
Idioma: 	Inglês	
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.	
Palavras-Chave: 	Análise de séries temporais; Imagens NDVI; Métodos estatísticos; Modelos de previsão; Monitoramento de cana-de-açúcar.	
Thesagro: 	Análise Estatística.	
Thesaurus Nal: 	Models; Statistical analysis; Sugarcane; Time series analysis.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (16474-1) - UPC - AP - DD -  -  -  - DIS