Networks play the role of a high-level language,as is seen in Artificial Intelligence and statistics,because networks are used to build complex model from simple components.These years,Bayesian Networks,one of probabilistic networks,are a powerful data mining technique for handling uncertainty in complex domains.In this paper,we apply Bayesian Networks Augmented Naive Bayes (BAN) to texture classification of High-resolution satellite images and put up a new method to construct the network topology structure in terms of training accuracy based on the training samples.In the experiment,we choose GeoEye-1 satellite images.Experimental results demonstrate BAN outperform than NBC in the overall classification accuracy.Although it is time consuming,it will be an attractive and effective method in the future.