The detection of ground fog from satellite data is of interest in operational nowcasting applications as well as in studies of the climate sytem. A discrimination between fog at the ground and other low stratus situations from satellite data requires information on cloud vertical geometry to establish whether the cloud touches the ground. This paper introduces a technique that allows for the discrimination between low stratus and (ground) fog on the basis of geostationary satellite imagery. The cloud base height is derived using a subadiabatic model of cloud microphysics. In this model, the cloud base is varied until model liquid water path (LWP) matches that retrieved from satellite data. The performance of this technique is shown to be good in a comparison with METAR data comprising 1030 satellite scenes. With a hit rate of 81% and a threat score of 0.62 the skill is satisfactory.