A mobile system, that has to navigate automatically in an outdoor environment,rnneeds to have knowledge about its surrounding terrain. Laser-range-finders, sometimes combined with cameras, are often used to analyse terrain. Several problems, like missing or noisy data, lead to erroneous identification of environment. The target of this work is to add a context-sensitive classification component and data of other sensors to a procedure, based on 3d-data, obtained by a laser-range-finder. The first upgrade consists of a Markov Random Field, which is used to model the relationships between neighbouring terrainsegments and allows a segmentation of the whole terrain. The second upgrade fuses laserdata with pictures from cameras to obtain additional terrainfeatures.