Data/hora: 21/06/2024 03:54:14

Biblioteca(s): 	Embrapa Agricultura Digital.	
Tipo da produção científica: 	Artigo em Anais de Congresso / Nota Técnica	
Data corrente: 	10/08/2009	
Data da última atualização: 	15/01/2020	
Autoria: 	NASCIMENTO, C. R.; GONÇALVES, R. R. V.; ZULLO JÚNIOR, J.; ROMANI, L. A. S.	
Afiliação: 	C. R. NASCIMENTO, FEAGRI/UNICAMP; R. R. V. GONÇALVES, FEAGRI/UNICAMP; J. ZULLO JÚNIOR, CEPAGRI/UNICAMP; LUCIANA ALVIM SANTOS ROMANI, CNPTIA.	
Título: 	Estimation of sugar cane productivity using a time series of AVHRR/NOAA-17 images and a phenology-spectral model.	
Ano de publicação: 	2009	
Fonte/Imprenta: 	In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 5., 2009, Groton, Connecticut. Proceedings... Storrs: UConn, 2009.	
Páginas: 	p. 365-372.	
Idioma: 	Inglês	
Notas: 	MultiTemp 2009.	
Conteúdo: 	Despite the economic and social importance of agribusiness in Brazil, the accurate estimation of the production of its main agricultural crops, such as sugar cane, is still a big challenge to the Country. Thus this work has the objective to assess a methodology based on the use of a phenology-spectral model proposed by Pellegrino (2001) and a time series of NDVI values. The tests were performed for three crop seasons (2003/2004, 2004/2005 e 2005/2006) and four cities located in the State of Sao Paulo (Jaboticabal, Pitangueiras, Ribeirao Preto and Sertaozinho) that is the main producer of sugar cane in Brazil. Reference values for productivity were provided by the IBGE (National Institute of Geography and Statistics). The methodology can be used to support operational systems of crop monitoring and forecasting since the estimation errors were less than 5% and the anticipation was from 110 to 150 days before harvest.	
Palavras-Chave: 	Georreferenciamento; Image processing; Imagens AVHRR/NOAA-17; Phenology-spectral model; Processamento de imagens NDVI; Séries temporais de valores NDVI; Sistema NAVPro.	
Thesagro: 	Agricultura; Cana de açúcar; Sensoriamento remoto.	
Thesaurus Nal: 	Remote sensing; Sugarcane; Time series analysis.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (13689-1) - UPC - AA - PP -  -  - 2009.00134 - DES
CNPTIA - (13689-2) - UPC - AA - DD -  -  -  - DIS