The presented paper documents the possibilities to map and monitor the surface mining areas by means of remote sensing techniques. Data pre-processing, visual and digital (semi-supervised) classification approaches arc performed on various types of image data (panchromatic, RGB and IR aerial photographs, CORONA, SPOT-P, LANDSAT TM) in the northern part of Leibnitzer Feld in Styria (Austria). The study focused on developing classification methods to quantify the progress of mining areas by means of remote sensing data. A further aspect was to investigate the different development steps of closed mining areas, respectively their filling and the re-cultivation. With stereoscopic aerial and spaceborne high resolution images it is furthermore possible to map the depth and the volume of mining areas and to generate a digital terrain model of it. This study was aided by the Geological Survey of Austria and the Styrian Government.