%0 Conference Proceedings
%4 sid.inpe.br/iris@1912/2005/07.20.10.27
%2 sid.inpe.br/iris@1912/2005/07.20.10.28
%F 7859
%T Applicability of neural network architecture by a fuzzy model to identify natural vegetation regrowth in Brazilian Amazonia
%D 1996
%A Santos, Joao Roberto dos,
%A Venturieri, Adriano,
%A Machado, Ricardo Jose,
%A Liporace, Frederico dos Santos,
%B International Congress for Photogrammetry and Remote Sensing, 18.
%C Viena, AU
%8 09-19 July 1996
%P 204-208
%1 ISPRS
%K VEGETACAO, AMAZONIA (REGIAO), MONITORAMENTO, REDES NEURAIS, SEGMENTACAO, MAPEADOR TEMATICO (LANDSAT), MONITORING, VEGETATION, SEGMENTATION, REGROWTH, THEMATIC MAPPER (LANDSAT).
%X The objetive of this study is to present the results of preparation of a neural network trained by a backpropagation algorithm, in order to process TM-Landsat images, used to identify areas under secondary succession, among other landuse classes in Amazonia. Image segmentation techniques by an algorithm of region growth and labelling of these segments by fuzzy-logic were also used for the preparation of the start-up network. The performance of the network to delineate the "initial" and "advanced" regrowth areas, was obtained using both sensitivity and specificity indices and of the MSE (Mean Square Error). Generally, it appears that both spectral, textural (entropy and correlation)and contextual descriptors are effective for the identification of regrowth areas in Amazonia.
%3 1996_santos.pdf