The amount of remotely data images increases rapidly

and the information that the images contain becomes more and more complicated. How to classify remotely sensed images automatically and effectively is a problem needed to be solved. This paper explores the application of Fuzzy ARTMAP neural network in classification of land cover. The adjusting methods of vigilance parameter are summarized. An automatic adjusting algorithm is proposed. The simulation results show that the automatic adjustment algorithm can increase the efficiency of selecting the optimum parameter value. The convergence speed and classification accuracy can also be improved through the automatic adjusting algorithm. The Fuzzy ARTMAP neural network with the automatic adjusting algorithm has shorter training time and higher classification accuracy than maximum likelihood classifier and traditional Fuzzy ARTMAP. A relatively satisfied classification result can be achieved by using Fuzzy ARTMAP in land cover classification.