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dc.contributor.authorSCHULTZ, B.pt_BR
dc.contributor.authorLUIZ, A. J. B.pt_BR
dc.contributor.authorSANCHES, I. D. A.pt_BR
dc.contributor.authorFORMAGGIO, A. R.pt_BR
dc.date.accessioned2016-01-26T11:11:11Zpt_BR
dc.date.available2016-01-26T11:11:11Zpt_BR
dc.date.created2016-01-26pt_BR
dc.date.issued2015pt_BR
dc.identifier.citationIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 2357-2364.pt_BR
dc.identifier.urihttp://www.alice.cnptia.embrapa.br/alice/handle/doc/1035208pt_BR
dc.descriptionAbstract: A study has been carried out considering 18 years of papers published in the Simpósio Brasileiro de Sensoriamento Remoto (Brazilian Remote Sensing Symposium) related to the subject of satellite image classification. The aim of the study was to assess the degree of progress made in thematic mapping through developments in classification algorithms, different approaches (per-pixel or object-based) and methods (unsupervised and supervised). The result of 238 reported classification experiments were quantitatively analyzed through Kappa Index (KI) results. Several parameters were used to relate the experiments, as type of approach, method, number of samples and classes, used sensor system, etc. Overall, the results showed that no significant improvement was found in KI results after 18 years SBSR. The mean and KI values was found to be 0.71 and standard deviation of 0.14. Relations between KI results and number of class, type of approach and method could not be found. Thirty one percent of the experiments analyzed did not present sufficient methodological information, thus, they were excluded from the analysis.pt_BR
dc.language.isoporpt_BR
dc.rightsopenAccesspt_BR
dc.subjectAutomatic classificationpt_BR
dc.subjectSBSRpt_BR
dc.subjectMeta-análisept_BR
dc.subjectClassificação automáticapt_BR
dc.titleQualidade da classificação automática de imagens de sensoriamento remoto em trabalhos apresentados nas edições anteriores do SBSR.pt_BR
dc.typeArtigo em anais e proceedingspt_BR
dc.date.updated2016-01-26T11:11:11Zpt_BR
dc.subject.thesagroSensoriamento remotopt_BR
dc.subject.nalthesaurusRemote sensingpt_BR
dc.subject.nalthesaurusMeta-analysispt_BR
riaa.ainfo.id1035208pt_BR
riaa.ainfo.lastupdate2016-01-26pt_BR
dc.contributor.institutionBRUNO SCHULTZ, INPE; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE; ANTONIO ROBERTO FORMAGGIO, INPE.pt_BR
Aparece en las colecciones:Artigo em anais de congresso (CNPMA)

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