A GIS for decision support would normally involve integration of images, spatial layers, attribute information and an inference based on these. The different spatial layers may combine in a nonlinear way, and moreover the information obtained from each layer may be inaccurate or uncertain to various degrees. These uncertainties should be taken into consideration when the various items of information are combined without which the decision making process might lead to inaccurate decisions. Hence, we propose to use fuzzy inferencing to handle uncertainties such as sharp class boundaries, measurement uncertainties, linguistic knowledge, and inherent uncertainty due to mixture of classes.