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 | Acesso ao texto completo restrito à biblioteca da Embrapa Solos. Para informações adicionais entre em contato com cnps.biblioteca@embrapa.br. |
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Registro Completo |
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Biblioteca(s): |
Embrapa Solos. |
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Data corrente: |
12/12/2022 |
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Data da última atualização: |
12/12/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
BASTOS, B. P.; PINHEIRO, H. S. K; CARVALHO JUNIOR, W. de; ANJOS, L. H. C. dos; FERREIRA, F. J. F. |
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Afiliação: |
BLENDA PEREIRA BASTOS, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; HELENA SARAIVA KOENOW PINHEIRO, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; WALDIR DE CARVALHO JUNIOR, CNPS; LÚCIA HELENA CUNHA DOS ANJOS, UNIVERSIDADE FEDERAL RURAL DO RIO DE JANEIRO; FRANCISCO JOSÉ FONSECA FERREIRA, UNIVERSIDADE FEDERAL DO PARANÁ. |
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Título: |
Clustering airborne gamma-ray spectrometry data in Nova Friburgo, State of Rio de Janeiro, southeastern Brazil. |
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Ano de publicação: |
2023 |
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Fonte/Imprenta: |
Journal of Applied Geophysics, v. 209, 104900, Feb. 2023. |
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DOI: |
https://doi.org/10.1016/j.jappgeo.2022.104900 |
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Idioma: |
Inglês |
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Conteúdo: |
The goal of this study was to test different image clustering techniques, using airborne gamma-ray spectrometry data to optimize the interpretation of areas with similar properties in large scale. The methodology applied was based on the comparison of two techniques of data-driven classification (K-means and Gaussian Mixture Models) and a technique of knowledge-driven classification (Simplified RGB) to discriminate domains from the primary variables potassium (K), uranium (eU), and thorium (eTh) obtained from airborne gamma-ray spectrometry surveys. The performance of these three methods was evaluated through pre-processing techniques and post-processing including the best number of clusters/classes, visual interpretation, internal validation, and boxplot analysis. The clustering performance was considered satisfactory through the visual interpretation and comparison with the geological map and the DEM, for all three methods. For a quantitative analysis, the simplest model of unsupervised clustering Gaussian Mixture Models prevailed. |
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Palavras-Chave: |
Data-driven classification; Gamma-ray spectrometry; Geological mapping; Knowledge-driven classification. |
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Categoria do assunto: |
P Recursos Naturais, Ciências Ambientais e da Terra |
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Marc: |
LEADER 01840naa a2200229 a 4500
001 2149458
005 2022-12-12
008 2023 bl uuuu u00u1 u #d
024 7 $ahttps://doi.org/10.1016/j.jappgeo.2022.104900$2DOI
100 1 $aBASTOS, B. P.
245 $aClustering airborne gamma-ray spectrometry data in Nova Friburgo, State of Rio de Janeiro, southeastern Brazil.$h[electronic resource]
260 $c2023
520 $aThe goal of this study was to test different image clustering techniques, using airborne gamma-ray spectrometry data to optimize the interpretation of areas with similar properties in large scale. The methodology applied was based on the comparison of two techniques of data-driven classification (K-means and Gaussian Mixture Models) and a technique of knowledge-driven classification (Simplified RGB) to discriminate domains from the primary variables potassium (K), uranium (eU), and thorium (eTh) obtained from airborne gamma-ray spectrometry surveys. The performance of these three methods was evaluated through pre-processing techniques and post-processing including the best number of clusters/classes, visual interpretation, internal validation, and boxplot analysis. The clustering performance was considered satisfactory through the visual interpretation and comparison with the geological map and the DEM, for all three methods. For a quantitative analysis, the simplest model of unsupervised clustering Gaussian Mixture Models prevailed.
653 $aData-driven classification
653 $aGamma-ray spectrometry
653 $aGeological mapping
653 $aKnowledge-driven classification
700 1 $aPINHEIRO, H. S. K
700 1 $aCARVALHO JUNIOR, W. de
700 1 $aANJOS, L. H. C. dos
700 1 $aFERREIRA, F. J. F.
773 $tJournal of Applied Geophysics$gv. 209, 104900, Feb. 2023.
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Registro original: |
Embrapa Solos (CNPS) |
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Biblioteca |
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Cutter |
Registro |
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URL |
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Registro Completo
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Biblioteca(s): |
Embrapa Gado de Leite. |
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Data corrente: |
17/03/2015 |
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Data da última atualização: |
30/01/2024 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Circulação/Nível: |
A - 1 |
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Autoria: |
SALES, M. L.; FONSECA JUNIOR, A. A.; ORZIL, L.; ALENCAR, A. P.; HODON, M. A.; ISSA, M. A.; SOARES FILHO, P. M.; SILVA, M. R.; LAGE, A. P.; HEINEMANN, M. B. |
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Afiliação: |
M. L. SALES, LANAGRO-MG; A. A. FONSECA JUNIOR, LANAGRO-MG; L. ORZIL, LANAGRO-MG; A. P. ALENCAR, LANAGRO-MG; M. A. HODON, LANAGRO-MG; M. A. ISSA, LANAGRO-MG; P. M. SOARES FILHO, LANAGRO-MG; MARCIO ROBERTO SILVA, CNPGL; A. P. LAGE, UFMG; M. B. HEINEMANN, UFMG. |
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Título: |
Validation of two real-time PCRs targeting the PE-PGRS 20 gene and the region of difference 4 for the characterization of Mycobacterium bovis isolates. |
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Ano de publicação: |
2014 |
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Fonte/Imprenta: |
Genetics and Molecular Research, v. 13, n. 2, p. 4607-16, 2014. |
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Idioma: |
Inglês |
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Palavras-Chave: |
Real-time PCR; Validation. |
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Thesagro: |
Mycobacterium Bovis. |
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Thesaurus NAL: |
bovine tuberculosis. |
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Categoria do assunto: |
L Ciência Animal e Produtos de Origem Animal |
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URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/120486/1/Cnpgl-2014-Genetics-Molecular-Research-Validation-SP-6610.pdf
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Marc: |
LEADER 00850naa a2200265 a 4500
001 2011537
005 2024-01-30
008 2014 bl uuuu u00u1 u #d
100 1 $aSALES, M. L.
245 $aValidation of two real-time PCRs targeting the PE-PGRS 20 gene and the region of difference 4 for the characterization of Mycobacterium bovis isolates.$h[electronic resource]
260 $c2014
650 $abovine tuberculosis
650 $aMycobacterium Bovis
653 $aReal-time PCR
653 $aValidation
700 1 $aFONSECA JUNIOR, A. A.
700 1 $aORZIL, L.
700 1 $aALENCAR, A. P.
700 1 $aHODON, M. A.
700 1 $aISSA, M. A.
700 1 $aSOARES FILHO, P. M.
700 1 $aSILVA, M. R.
700 1 $aLAGE, A. P.
700 1 $aHEINEMANN, M. B.
773 $tGenetics and Molecular Research$gv. 13, n. 2, p. 4607-16, 2014.
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Embrapa Gado de Leite (CNPGL) |
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