Please use this identifier to cite or link to this item: http://repositorio.unicamp.br/jspui/handle/REPOSIP/1963
Type: Artigo de periódico
Title: USE OF DATA MINING AND SPECTRAL PROFILES TO DIFFERENTIATE CONDITION AFTER HARVEST OF COFFEE PLANTS
Author: Lamparelli, Rubens A. C.
Johann, Jerry A.
dos Santos, Eder R.
Esquerdo, Julio C. D. M.
Rocha, Jansle V.
Abstract: 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.
Subject: crop monitoring
spectral behavior
management
orbital remote sensing
Country: Brazil
Editor: Soc Brasil Engenharia Agricola
Citation: Engenharia Agricola. Soc Brasil Engenharia Agricola, v.32, n.1, p.184-196, 2012
Rights: fechado
Date Issue: 2012
Appears in Collections:FEAGRI - Artigos e Outros Documentos

Files in This Item:
There are no files associated with this item.


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.