Data/hora: 02/06/2024 02:30:13

Biblioteca(s): 	Embrapa Agricultura Digital.	
Tipo da produção científica: 	Artigo em Periódico Indexado	
Circulação/Nível: 	A - 2	
Data corrente: 	08/05/2012	
Data da última atualização: 	08/05/2012	
Autoria: 	LAMPARELLI, R. A. C.; JOHANN, J. A.; SANTOS, É. R. dos; ESQUERDO, J. C. D. M.; ROCHA, J. V.	
Afiliação: 	RUBENS A. C. LAMPARELLI, Cepagri/Unicamp; JERRY A. JOHANN, Feagri/Unicamp; ÉDER R. DOS SANTOS, Cooxupé; JULIO C. D. M. ESQUERDO, CNPTIA; JANSLE V. ROCHA, Feagri/Unicamp.	
Título: 	Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants.	
Ano de publicação: 	2012	
Fonte/Imprenta: 	Engenharia Agrícola, Jaboticabal, v. 32, n. 1, p. 184-196, jan./fev. 2012.	
Idioma: 	Inglês	
Conteúdo: 	This study aimed at identifying different conditions of coffee plants after harvesting period, using data mining and spectral behavior profiles from Hyperion/EO1 sensor. The Hyperion image, with spatial resolution of 30 m, was acquired in August 28th, 2008, at the end of the coffee harvest season in the studied area. For pre-processing imaging, atmospheric and signal/noise effect corrections were carried out using Flaash and MNF (Minimum Noise Fraction Transform) algorithms, respectively. Spectral behavior profiles (38) of different coffee varieties were generated from 150 Hyperion bands. The spectral behavior profiles were analyzed by Expectation-Maximization (EM) algorithm considering 2; 3; 4 and 5 clusters. T-test with 5% of significance was used to verify the similarity among the wavelength cluster means. The results demonstrated that it is possible to separate five different clusters, which were comprised by different coffee crop conditions making possible to improve future intervention actions.	
Palavras-Chave: 	Comportamento espectral; Data mining; Mineração de dados; Monitoramento de cultura.	
Thesagro: 	Manejo; Sensoriamento Remoto.	
Thesaurus Nal: 	Crop management; Remote sensing.	
Categoria do assunto: 	X Pesquisa, Tecnologia e Engenharia	
URL: 	http://ainfo.cnptia.embrapa.br/digital/bitstream/item/58965/1/19.pdf	
Registro original: 	Embrapa Agricultura Digital (CNPTIA)	
Exemplares: 	CNPTIA - (16672-1) - UPC - AP - DD -  -  -  - DIS