Artículos de revistas
Análise da incerteza na representação de classes de cobertura do solo urbano resultantes da aplicação de uma rede neural artificial
Fecha
2007-01-01Registro en:
Boletim de Ciencias Geodesicas, v. 13, n. 1, p. 22-41, 2007.
1413-4853
2-s2.0-36549066884
2-s2.0-36549066884.pdf
1647318644299561
9070577381094673
894715226925471
Autor
Universidade Estadual Paulista (Unesp)
Institución
Resumen
The great diversity of materials that characterizes the urban environment determines a structure of mixed classes in a classification of multiespectral images. In that sense, it is important to define an appropriate classification system using a non parametric classifier, that allows incorporating non spectral (such as texture) data to the process. They also allow analyzing the uncertainty associated to each class from the output alues of the network calculated in relation to each class. Considering these properties, an experiment was carried out. This experiment consisted in the application of an Artificial Neural Network aiming at the classification of the urban land cover of Presidente Prudente and the analysis of the uncertainty in the representation of the mapped thematic classes. The results showed that it is possible to discriminate the variations in the urban land cover through the application of an Artificial Neural Network. It was also possible to visualize the spatial variation of the uncertainty in the attribution of classes of urban land cover from the generated representations. The class characterized by a defined pattern as intermediary related to the impermeability of the urban soil presented larger ambiguity degree and, therefore, larger mixture.