Data/hora: 16/06/2024 07:18:59

Biblioteca(s): | Embrapa Territorial.
Data corrente: | 30/09/2011
Data da última atualização: | 03/05/2019
Autoria: | SILVA, G. B. S. da; MELLO, M. P.; SHIMABUKURO, Y. E.; RUDORFF, B. F. T.; VICTORIA, D. de C.
Afiliação: | GUSTAVO BAYMA SIQUEIRA DA SILVA, CNPM; MARCIO PUPIN MELLO, INPE; YOSIO EDEMIR SHIMABUKURO, INPE; BERNARDO FRIEDRICH THEODOR RUDORFF, INPE; DANIEL DE CASTRO VICTORIA, CNPM.
Título: | Multitemporal classification of natural vegetation cover in Brazilian Cerrado.
Ano de publicação: | 2011
Fonte/Imprenta: | In: INTERNATIONAL WORKSHOP ON THE ANALYSIS OF MULTI-TEMPORAL REMOTE SENSING IMAGES, 6., 2011, Trento, IT. Anais... Trento: IEEE, 2011.
Páginas: | p. 117-120.
Idioma: | Português
Conteúdo: | Spectral-Temporal Analysis by Response Surface (STARS), which utilizes surface response to represent time series spectral-temporal behavior of pixels in satellite images, was used to map and discriminate savanna vegetation classes in portion of Cerrado biome of Mato Grosso State, Brazil, using MODIS data. STARS utilized 16 daily MODIS, cloud-free, images that were collected from September 1st 2008 to August 31st 2009. The Multi-Coefficient Image (MCI) resulted from the STARS was used as input attributes for the three tested classifiers: (i) ML - maximum likelihood; (ii) SVM - support vector machine; and (iii) NN - neural network. The results showed that the NN classifier presented higher kappa coefficient (0.58) and overall accuracy of 68.6%.
Palavras-Chave: | Linear spectral mixture model; Savanna; STARS.
Categoria do assunto: | --
Registro original: | Embrapa Territorial (CNPM)
Exemplares: | CNPM - (3127-1) - UPC - AA - PP - 11/012 - AA - 2011.012 - DIS