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Registro Completo |
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Biblioteca(s): |
Embrapa Meio Ambiente. |
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Data corrente: |
26/01/2016 |
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Data da última atualização: |
19/01/2023 |
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Tipo da produção científica: |
Artigo em Anais de Congresso |
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Autoria: |
SCHULTZ, B.; LUIZ, A. J. B.; SANCHES, I. D. A.; FORMAGGIO, A. R. |
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Afiliação: |
BRUNO SCHULTZ, INPE; ALFREDO JOSE BARRETO LUIZ, CNPMA; IEDA DEL'ARCO SANCHES, INPE; ANTONIO ROBERTO FORMAGGIO, INPE. |
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Título: |
Qualidade da classificação automática de imagens de sensoriamento remoto em trabalhos apresentados nas edições anteriores do SBSR. |
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Ano de publicação: |
2015 |
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Fonte/Imprenta: |
In: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 2357-2364. |
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Idioma: |
Português |
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Conteúdo: |
Abstract: 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. |
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Palavras-Chave: |
Automatic classification; Classificação automática; Meta-análise; SBSR. |
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Thesagro: |
Sensoriamento remoto. |
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Thesaurus Nal: |
Meta-analysis; Remote sensing. |
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Categoria do assunto: |
X Pesquisa, Tecnologia e Engenharia |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/137813/1/2015AA002.pdf
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Marc: |
LEADER 01964nam a2200229 a 4500
001 2035208
005 2023-01-19
008 2015 bl uuuu u00u1 u #d
100 1 $aSCHULTZ, B.
245 $aQualidade da classificação automática de imagens de sensoriamento remoto em trabalhos apresentados nas edições anteriores do SBSR.$h[electronic resource]
260 $aIn: SIMPÓSIO BRASILEIRO DE SENSORIAMENTO REMOTO, 17., 2015, João Pessoa. Anais... São José dos Campos: INPE, 2015. p. 2357-2364.$c2364
520 $aAbstract: 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.
650 $aMeta-analysis
650 $aRemote sensing
650 $aSensoriamento remoto
653 $aAutomatic classification
653 $aClassificação automática
653 $aMeta-análise
653 $aSBSR
700 1 $aLUIZ, A. J. B.
700 1 $aSANCHES, I. D. A.
700 1 $aFORMAGGIO, A. R.
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Embrapa Meio Ambiente (CNPMA) |
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