Use este identificador para citar ou linkar para este item: http://www.alice.cnptia.embrapa.br/alice/handle/doc/1022621
Unidade da Embrapa/Coleção:: Embrapa Monitoramento por Satélite - Artigo em anais de congresso (ALICE)
Data do documento: 25-Ago-2015
Tipo do Material: Artigo em anais de congresso (ALICE)
Autoria: LU, D.
MAUSEL, P.
BATISTELLA, M.
MORAN, E.
Informaçães Adicionais: DENGSHENG LU, INDIANA UNIVERSITY; PAUL MAUSEL, INDIANA STATE UNIVERSITY; MATEUS BATISTELLA, CNPM; EMILIO MORAN, INDIANA UNIVERSITY.
Título: Comparison of land-cover classification methods in the Brazilian Amazon Basin.
Edição: 2003
Fonte/Imprenta: In: ANNUAL CONFERENCE, 2003, Alaska. Proceedings... Alaska: ASPRS, 2003.
Páginas: 11 p.
Idioma: en
Palavras-chave: Minimum distance classifier.
Extraction and classification of homogeneous
Fisher linear discriminant
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.
Ano de Publicação: 2003
Aparece nas coleções:Artigo em anais de congresso (CNPM)

Arquivos associados a este item:
Arquivo Descrição TamanhoFormato 
4553.pdf212,24 kBAdobe PDFThumbnail
Visualizar/Abrir

FacebookTwitterDeliciousLinkedInGoogle BookmarksMySpace