Harald Stadler, Thomas Bachnetzer, Stephanie E. Metz
Abstract Due to the current rate of glacial erosion in the alpine region, more archaeological and organic remains are revealed than ever before. These finds span the last 10,000 years of human history, creating new and exiting datasets for not only archaeology, but other related subjects as well. Of particular interest have been prehistoric finds, notably at Similaun (“Ötzi the ice man”) in 1991, and more recently at the Schnidejoch and Lötschenpass in the Bernese Oberland of Switzerland. The high level of preservation from having been encased in ice for thousands of years means that these examples and others have helped to shed light on the poorly understood early use of high-alpine landscapes. Thus, the data are of important value for multiple disciplines, namely Forensic Anthropology, Zooarchaeology, Archaeobotany, Glaciology, and Climatology. While the research potential in this field is clear, to date there has been little work done either to understand or protect these critically endangered cultural heritage assets. Indeed, previous academic work has highlighted just how important the development of a methodology is to systematically study the glacial archaeological data in the Austrian alpine region before it disappears. Thus, the aim of the GAAA Project will be the systematic identification of areas of high archaeological potential in the Tyrol and Vorarlberg regions of Austria. To this end, the project will work on a three-tiered level of engagement with the data via development of methodological practice and theory, fieldwork and community outreach/public relations. The very short window of maximum ice melt from August to September necessitates the development of a framework to be able to detect and evaluate potential findspots in advance. With the help of GIS, predictive models will be generated to identify areas of potential interest. These parameters of these models will be based on both cultural and environmental geospatial factors. The framework for these models will ultimately enable a targeted survey of potential findspots which will then be monitored for the appearance of archaeological material.
