Mapping forest cover types in the boreal ecosystem is important for understanding the processes governing the interaction of the surface with the atmosphere. In this paper, we report the results of the land-cover classification of the SAR (synthetic aperture radar) data acquired during the Boreal Ecosystem Atmospheric Study's intensive field campaigns over the southern study area near Prince Albert, Canada. A Bayesian maximum a posteriori classifier was applied on the National Aeronautics and Space Administration/Jet Propulsion Laboratory airborne SAR images covering the region during the peak of the growing season in July 1994. The results show that SAR images can be classified into dominant forest types such as jack pine, black spruce, trembling aspen, clearing, open water, and three categories of mixed stands with better than 90% accuracy.