Potential of airborne laser scanning for geomorphologic feature and process detection and quantifications in high alpine environments. Since 2001 airborne laser scanning (ALS), also referred to as LiDAR (Light Detection and Ranging), measurements have been carried out regularly at the Hintereisferner region (Otztal, Tyrol, Austria). This results in a worldwide unique data set, which is primarily used for multi-temporal glacial and geomorphologic analysis. Several methods and tools i) to delineate the glacier boundary, ii) to derive standard glaciological mass balance parameters (e.g. volume changes), iii) to excerpt crevasse zones or iv) to classify glacier surface features (e.g. snow, firn, glacier ice, debris covered glacier ice) have been developed as yet. Furthermore, the available multi-temporal ALS data set offers the opportunity to identify surface elevation changes occurring outside the glacier boundary, which have not been recognized until now. Some of the respective areas are characterized by small height variations (textless0.1 m) of the surface topography from year to year. These changes are primarily caused by cryospheric and geomorphologic processes further initiating secondary gravitative mass movements. The first part of this study aims at quantifying the vertical accuracy of the available multi-temporal ALS data sets. In comparison with differential dGNSS (differential global navigation satellite system) measurements the vertical accuracy of the ALS point data is better than + 0.07 in (mean absolute error), with a standard deviation of +/- 0.07 m for relatively flat and homogeneous areas on the glacier tongue of Hintereisferner. A height error analysis, which is based on 55 cross-combinations of the individual ALS measurement campaigns results in statistically derived slope dependent error margins. We found an increase of the mean absolute standard error with increasing slope angles, but on a very low level (e.g. textless +/- 0.04 m on slope angles smaller than 35 degrees). This ensures the vertical homogeneity of our multi-temporal ALS data set. Including point to raster aggregation errors as well, the cumulative errors (e.g. +/- 0.12 cm in 40 degrees steep and rough terrain) are also promising. Hence, surface elevation changes which exceed these error margins can be assigned to geomorphologic process activities. The second part of the study aims at the identification and quantification of areas which are explicitly related to cryospheric and geomorphologic processes on different time scales (intra-annual, perennial). The corresponding area-averaged elevation changes range from + 0.7 m (fluvial deposit) to more negative than -4.0 m (on glaciers, dead ice and rockfall release area;) within a time period of seven years. Obviously, the measured intra-annual change rates (positive and negative) with approximately 0.10 m for fluvial erosion, fluvial deposit or dead ice melting (showing a maximum at 0.7 m) are much smaller and close to the ALS error margins. We conclude that the analysis of processes with very small elevation change rates have to be based on a sincere error analysis. For that aim the multi-temporal ALS data sets have to be fine-georeferenced (strip adjustment per epoch (reduction of relative height and planar errors per strip) and absolute refinement in respect to a well defined stable coordinate frame (e.g. represented by a set of temporal stable surfaces of a certain reference epoch)). Furthermore, next to the analysis of the height difference the influence of planar errors will be considered.