The use of satellite sensor data can be used to detect discrete slope processes and landforms with a high degree of accuracy. Whereas previous attempts to classify slope features using per pixel spectral response patterns have provided classification accuracies that are less than 60%, it is demonstrated that a combination of high resolution optical imagery, image segmentation and ancillary data derived from a digital elevation model can discriminate some types of mass wasting processes with accuracies of 80% or higher. The spatial resolution of the imagery is critical to the successful classification of such features both in terms of information derived from textural analysis and in the ability to successfully segment landslide features. Furthermore, the data generated in this manner can be used for geomorphic research in terms of characterizing the occurrence of mass wasting within the bounds of the image scene.