Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/924115
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dc.contributor.authorLAMPARELLI, R. A. C.pt_BR
dc.contributor.authorJOHANN, J. A.pt_BR
dc.contributor.authorSANTOS, É. R. dospt_BR
dc.contributor.authorESQUERDO, J. C. D. M.pt_BR
dc.contributor.authorROCHA, J. V.pt_BR
dc.date.accessioned2012-05-08T11:11:11Zpt_BR
dc.date.accessioned2012-05-08T11:11:11Zpt_BR
dc.date.available2012-05-08T11:11:11Zpt_BR
dc.date.available2012-05-08T11:11:11Zpt_BR
dc.date.created2012-05-08pt_BR
dc.date.issued2012pt_BR
dc.identifier.citationEngenharia Agrícola, Jaboticabal, v. 32, n. 1, p. 184-196, jan./fev. 2012.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/924115pt_BR
dc.descriptionThis 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.pt_BR
dc.language.isoengeng
dc.rightsopenAccesseng
dc.subjectData miningpt_BR
dc.subjectMineração de dadospt_BR
dc.subjectMonitoramento de culturapt_BR
dc.subjectComportamento espectralpt_BR
dc.titleUse of data mining and spectral profiles to differentiate condition after harvest of coffee plants.pt_BR
dc.typeArtigo de periódicopt_BR
dc.date.updated2012-05-08T11:11:11Zpt_BR
dc.subject.thesagroManejopt_BR
dc.subject.thesagroSensoriamento Remotopt_BR
dc.subject.nalthesaurusCrop managementpt_BR
dc.subject.nalthesaurusRemote sensingpt_BR
riaa.ainfo.id924115pt_BR
riaa.ainfo.lastupdate2012-05-08pt_BR
dc.contributor.institutionRUBENS 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.pt_BR
Aparece nas coleções:Artigo em periódico indexado (CNPTIA)

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