Knowledge discovery from multispectral satellite images

In this paper we propose a method to extract and reduce fuzzy if-then rules from fuzzy neural systems. After training, fuzzy rules are extracted from the fuzzy-neural network by backtracking along the weighted paths through the neural network These rules are then reduced by use of a fuzzy associate memory bank (FAM bank). We used this algorithm to extract classification rules from a multispectral satellite image. The image represents the Mississippi river bottomland In order to verify the rule extraction method measures such as accuracy, overall Kappa, and fidelity are used The results are presented in the paper.