This study investigates the application of the Rough Set Theory for image classification. The images used for the experiment include multi-temporal Formosat-2 images of the Chiayi area and multi-temporal SPOT images of the Hsinchu area. Gaussian Maximum Likelihood Classification and Back-Propagation neural network are used for comparison. The overall accuracy for Rough Set Theory is 86.947% for Chiayi and 81.44% for Hsinchu. The kappa index is 0.73826 for Chiayi and 0.61448 for Hsinchu. In terms of the classification accuracy, Rough Set Theory is shown to be better than Gaussian Maximum Likelihood Classification but inferior to Back-Propagation neural network for Chiayi and Hsinchu area.