Detecting Alpine landforms from remotely sensed imagery. A pilot study in the Bavarian Alps

This study investigates the suitability of remote sensing for detecting rock and sediment storage areas in the Reintal subcatchment (17 km2) east of Zugspitze, Germany. First, characteristic features of Alpine landforms such as curvature, process coupling or type of deposited sediment were compiled. Based on this, a landform classification was performed: topographical information from a digital elevation model (DEM) and spectral data from an ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) satellite scene were classified using a multiscale, object-oriented approach comprising four differently scaled levels. The complex decision-tree hierarchy is based for the most part on fuzzy membership functions and to a lesser extent on the hard nearest neighbour classifier. The results show that both an identification of the present-day pattern of storage types and the classification of geomorphologic units, also with regard to their activity status and complexity, is largely possible. Moreover, the methodology developed in this study permits a first assessment of the upper regions of the study area which could not be included in any previous survey because of their inaccessibility. Coherent landform classification using remote sensing methods, as developed in this study, constitutes a promising scientific approach, especially with regard to the enhanced spatial and spectral resolution of modern satellite systems.