Digital geomorphological information for alpine hazard studies using laser altimetry data and GIS: With an example from Vorarlberg, Austria

Detailed geomorphological information has proven beneficial for the spatial recognition and delineation of natural hazards such as rock fall, slides and debris flows in alpine ecosystems. New digital (semi-)automated mapping and availability of LiDAR altimetry data may improve the accessibility and accuracy of detailed geomorphological information, which can be used as input in hazard studies. A first improvement is that digital geomorphological maps store both terrain units and attributes which describe color coded landforms, processes and deposits. These terrain units are categorized using a morphogenetic classification scheme to preserve most information displayed in traditional paper geomorphological map. A second improvement is the (semi-) automated extraction of statistical morphometric information derived from digital elevation models, which can be related to the digital landform units recognized in the digital geomorphological map. Existing techniques used for the extraction of geometrical derivatives only focused on deriving slope angle, curvature, altitude and aspect and mostly in homogeneous terrain and not on genetic and process information. High resolution laser altimetry data makes statistical separation of terrain objects derived from LidAR DEMs possible. First results show that integration of expert knowledge rules makes it possible to classify and group individual objects into unique geomorphological terrain units that are related to the genesis of landforms. These two parallel developments result in new information that serves as input in alpine hazard zonation studies. In this study a method for the preparation of digital geomorphological maps in Vorarlberg is presented and it is shown how simple landscape metrics can be used in the semi-automated recognition and classification of geomorphological information from LiDAR information. The methods include digital geomorphological GIS map preparation and visualization using a standardized morphogenetic classification scheme and object oriented classification of a LiDAR dataset combined with zonal statistical analysis in a GIS environment. Direct advantage and improvements over existing methods are improved understanding of landscape process in inaccessible and/or forested areas, increase in mapping accuracy and improved consistency in the objectivity and reproducibility of the mapping methods. Moreover, expert knowledge rules can be added to this process. The resulting information can serve as input into hazard zonation studies and be displayed either as a 'flat' computer screen map in GIS, as a paper map, a "bird's eye view" or alternatively, as an overlay in 'Google Earth'