| |
|
|
| Registros recuperados : 27 | |
| 6. |  | CHAVES, A. S.; NASCIMENTO, M. L.; TULLIO, R. R.; ROSA, A. do N.; ALENCAR, M. M. de; LANNA, D. P. Relationship of efficiency indices with performance, heart rate, oxygen consumption, blood parameters, and estimated heat production in Nellore steers. Journal of Animal Science, v. 93, n. 10, p. 5036?5046, October 2015| Biblioteca(s): Embrapa Gado de Corte; Embrapa Pecuária Sudeste. |
|    |
| 17. | | RIBEIRO, S. H. A.; PEREIRA, J. C. C.; VERNEQUE, R. da S.; SILVA, M. A.; BERGMAN, J. A. G.; FERREIRA, M. B. D. Efeitos da origem e da linhagem do DNA mitocondrial sobre características produtivas e reprodutivas de bovinos leiteiros da raça Gir. In: REUNIÃO ANUAL DA SOCIEDADE BRASILEIRA DE ZOOTECNIA, 46., 2009, Maringá. Anais... Maringá: SBZ, 2009.| Biblioteca(s): Embrapa Gado de Leite. |
| |
| Registros recuperados : 27 | |
|
|
|
Registro Completo
|
Biblioteca(s): |
Embrapa Territorial. |
|
Data corrente: |
29/04/2004 |
|
Data da última atualização: |
30/03/2015 |
|
Tipo da produção científica: |
Artigo em Periódico Indexado |
|
Circulação/Nível: |
Internacional - B |
|
Autoria: |
LU, D.; MAUSEL, P.; BATISTELLA, M.; MORAN, E. |
|
Afiliação: |
1-2 e 4: Indiana University; 3: Embrapa Monitoramento por Satélite. |
|
Título: |
Comparison of land-cover classification methods in the Brazilian Amazon Basin. |
|
Ano de publicação: |
2004 |
|
Fonte/Imprenta: |
Photogrammetric Engineering & Remote Sensing, v. 70, n. 6, p. 723-731, jun. 2004. |
|
Idioma: |
Inglês |
|
Conteúdo: |
Four distinctly different classifiers were used to analyze multispectral data. Which of these classifiers is most suitable for a specific study area is not always clear. This paper provides a comparison of minimum-distance classifier (MDC), maximumlikelihood classifier (MLC), extraction and classification of homogeneous objects (ECHO), and decision-tree classifier based on linear spectral mixture analysis (DTC-LSMA). Each of the classifiers used both Landsat Thematic Mapper data and identical field-based training sample datasets in a western Brazilian Amazon study area. Seven land-cover classes? mature forest, advanced secondary succession, initial secondary succession, pasture lands, agricultural lands, bare lands, and water?were classified. Classification results indicate that the DTC-LSMA and ECHO classifiers were more accurate than were the MDC and MLC. The overall accuracy of the DTCLSMA approach was 86 percent with a 0.82 kappa coefficient and ECHO had an accuracy of 83 percent with a 0.79 kappa coefficient. The accuracy of the other classifiers ranged from 77 to 80 percent with kappa coefficients from 0.72 to 0.75. |
|
Palavras-Chave: |
Amazonas; Amazonia brasileira; Mapeamento. |
|
Thesagro: |
Bacia Hidrográfica; Floresta Tropical Úmida; Satélite. |
|
Categoria do assunto: |
-- |
|
URL: |
https://ainfo.cnptia.embrapa.br/digital/bitstream/item/105777/1/1146.pdf
|
|
Marc: |
LEADER 01790naa a2200229 a 4500
001 1017039
005 2015-03-30
008 2004 bl uuuu u00u1 u #d
100 1 $aLU, D.
245 $aComparison of land-cover classification methods in the Brazilian Amazon Basin.
260 $c2004
520 $aFour distinctly different classifiers were used to analyze multispectral data. Which of these classifiers is most suitable for a specific study area is not always clear. This paper provides a comparison of minimum-distance classifier (MDC), maximumlikelihood classifier (MLC), extraction and classification of homogeneous objects (ECHO), and decision-tree classifier based on linear spectral mixture analysis (DTC-LSMA). Each of the classifiers used both Landsat Thematic Mapper data and identical field-based training sample datasets in a western Brazilian Amazon study area. Seven land-cover classes? mature forest, advanced secondary succession, initial secondary succession, pasture lands, agricultural lands, bare lands, and water?were classified. Classification results indicate that the DTC-LSMA and ECHO classifiers were more accurate than were the MDC and MLC. The overall accuracy of the DTCLSMA approach was 86 percent with a 0.82 kappa coefficient and ECHO had an accuracy of 83 percent with a 0.79 kappa coefficient. The accuracy of the other classifiers ranged from 77 to 80 percent with kappa coefficients from 0.72 to 0.75.
650 $aBacia Hidrográfica
650 $aFloresta Tropical Úmida
650 $aSatélite
653 $aAmazonas
653 $aAmazonia brasileira
653 $aMapeamento
700 1 $aMAUSEL, P.
700 1 $aBATISTELLA, M.
700 1 $aMORAN, E.
773 $tPhotogrammetric Engineering & Remote Sensing$gv. 70, n. 6, p. 723-731, jun. 2004.
Download
Esconder MarcMostrar Marc Completo |
|
Registro original: |
Embrapa Territorial (CNPM) |
|
|
Biblioteca |
ID |
Origem |
Tipo/Formato |
Classificação |
Cutter |
Registro |
Volume |
Status |
Fechar
|
| Nenhum registro encontrado para a expressão de busca informada. |
|
|
