Das Projekt "Analysis and Spatial Modelling of Permafrost Distribution in Cold-Mountain Areas by Integration of Advanced Remote Sensing Technology" wird vom Umweltbundesamt gefördert und von Universität Zürich, Geographisches Institut durchgeführt. Glaciers and permafrost in cold mountain areas are especially sensitive with respect to changes in atmospheric temperature because of their proximity to melting conditions. The 20th century has seen striking changes in glacierized areas of mountain ranges and, hence, in the extension of glacial and periglacial mountain belts all over the world, causing a corresponding shift in geomorphodynamic processes. In the event of future accelerated warming, the cryosphere components of Alpine environments would most likely evolve at high rates beyond the limits of historical and holocene variability ranges. Such a development would necessarily lead to pronounced disequilibria in the water cycle, in mass wasting processes and sediment flux as well as in growth conditions of vegetation. By consequence, living conditions for humans and animals will likely be affected as well. Empirical knowledge would have to be replaced increasingly by improved process understanding and robust computer models for economic planning, hazard mitigation, landscape protection etc. Thereby, high priority has to be placed on application of modern know-how and technologies for preparing corresponding assessments in combination with improved knowledge about the evolution of glacier- and permafrost-related processes based on appropriate monitoring programmes. An energy balance model that calculates surface and ground temperatures from climatic data has recently been developed in the project area (Corvatsch, Upper Engadin) based on a 3-year time series from a microclimatological station. For the successful spatial application and further development of this one-dimensional model, accurate spatial data fields of key surface characteristics are needed. The development of process-based permafrost models is closely connected to the improvement of statistical models that will be applicable in areas where less information is available. For these models, accurate knowledge of vegetation abundance represents a sensitive independent indicator to be used in evaluation as well as a valuable parameter if included. The present project for the first time employs and explores airborne hyperspectral remote sensing as a source of quantitative spatial information for analysis and numerical modelling of permafrost distribution and evolution in an especially well documented test area of the Swiss Alps. The potential to accurately quantify snow-free albedo and sparse vegetation cover in rugged topography makes hyperspectral remote sensing a promising data source. Collaboration of the Physical Geography Division and Remote Sensing Laboratories (RSL) is expected to help in reducing the gap that commonly exists between development of new sensors and technology and their application in research. The application of established remote sensing techniques and, if necessary, their adaptation to high mountain environments, provides a measurable data-basis for this study. (abridged text)