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UAV-based photogrammetry has many applications today. Measuring of snow depth using Structure-from-Motion (SfM) techniques is one of them. Determining the depth of snow is very important for a wide range of scientific research activities. In the alpine environment, this information is crucial, especially in the sphere of risk management (snow avalanches). The main aim of this study is to test the applicability of fixed-wing UAV with RTK technology in real alpine conditions to determine snow depth. The territory in West Tatras as a part of Tatra Mountains (Western Carpathians) in the northern part of Slovakia was analyzed. The study area covers more than 1.2 km2 with an elevation of almost 900 m and it is characterized by frequent occurrence of snow avalanches. It was found that the use of different filtering modes (at the level point cloud generation) had no distinct (statistically significant) effect on the result. On the other hand, the significant influence of vegetation characteristics was confirmed. Determination of snow depth based on seasonal digital surface model subtraction can be affected by the process of vegetation compression. The results also point on the importance of RTK methods when mapping areas where it is not possible to place ground control points.

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The avalanches represent a significant and very dynamic process within the Tatra high-mountain landscape. Undoubtedly avalanche run-out distances play a key role in land use planning within avalanche prone areas. The Žiarska valley and Predné Meďodoly valley are considered as one of the most avalanche prone valleys in Tatra Mts. This environment represents an excellent opportunity for studying and modelling extreme avalanche run-outs. Primarily avalanche release zones were estimated by using an existing model proposed by Hreško (1998). This model was modified and calibrated for both valleys. The alpha-beta regression model developed in Norway has been used to estimate avalanche run-outs. Data processing and model calibration have been elaborated in GIS environment. Avenue script for ArcGIS was written to perform automated runout estimation based on alpha-beta regression model. Model managed to estimate run-outs on some slopes while it failed to model run-ups. Finally the results were visualized by creating the fly-through simulations and 3D views. Comparison between model calculation and avalanche cadastre showed correlation.