DETECTION AND QUANTIFICATION OF ROCK GLACIER CREEP USING HIGH-RESOLUTION ORTHOIMAGES OF VIRTUAL GLOBES

Abstract. Rock glaciers are creep phenomena of mountain permafrost and are composed of ice and rocks. Active rock glaciers move downslope by force of gravity. Maximum creep/flow velocities of individual rock glaciers may vary from a few centimeters up to several meters per year, depending on the underlying terrain, mechanical parameters of the material involved, etc. Inter-annual variation of rock glacier flow has been observed and attributed to various reasons, e.g., climate change. It is believed that the observed warming of the atmosphere accelerates rock glacier flow. This paper proposes a method for detecting active rock glaciers and, where applicable, quantifying their movement relatively or absolutely using multi-temporal image data (i.e., high-resolution orthoimages/orthophotos) of virtual globes, such as Google Maps and Microsoft Bing Maps. The present work was originally triggered by the task of detecting all active rock glaciers of a larger mountain region, i.e., the western part of the Schober Mountains located in the Austrian Hohe Tauern range. In support of this task the proposed method was additionally applied to two well-studied rock glaciers, i.e., Hinteres Langtalkar (eastern part of the Schober Mountains) and Äußeres Hochebenkar (Ötztal Alps, Austria). In this paper we present the results obtained from the two rock glaciers. It can be summarized that change detection and consequently the high-precision measurement of flow velocities of active rock glaciers using image data (screen shots) of virtual globes (geobrowsers) is possible. It must be admitted, however, that the proposed method has some obvious drawbacks: (a) limited availability of high-resolution image data in high mountain areas, (b) limited availability of multi-temporal image data, (c) lack of information about exact acquisition dates or source of image data, (d) lack of information about the accuracy of the image data (orthophotos), and (e) potential legal obstacles to using the image data.