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Use of data mining and spectral profiles to differentiate condition after harvest of coffee plants REA
Lamparelli,Rubens A. C.; Johann,Jerry A.; Santos,Éder R. dos; Esquerdo,Julio C. D. M.; Rocha,Jansle V..
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...
Tipo: Info:eu-repo/semantics/article Palavras-chave: Crop monitoring; Spectral behavior; Management; Orbital remote sensing.
Ano: 2012 URL: http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0100-69162012000100019
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