Berin Dikic, Thomas Goelles , Christoph Gaisberbger, Birgit Schlager, Stefan Muckenhuber, Pedro Batista Pedro BATISTA, Markus Keuschnig, Markus Schratter

Traditional methods for surveying the spatial and temporal distribution of snow are often time-consuming, costly, and potentially hazardous. To address these challenges, we propose a novel approach utilizing a newly developed sensor system based on cost-effective industrial lidar sensors. This system is designed to be mounted on cable cars, enabling continuous envi- ronmental scanning during regular operations. The system integrates data from the lidar, an Inertial Measurement Unit (IMU), and Global Navigation Satellite System (GNSS), employing a Simultaneous Localization And Mapping (SLAM) algorithm to generate detailed maps of the area. In our initial testing on Hoher Sonnblick, we benchmarked our data against conventional laser scanning and structure-from-motion techniques. Four experimental runs were conducted over a single day using the same cable car equipped with our setup. The SLAM algorithm had some difficulties in areas without many distinct features and aligning two 3D point clouds with- out Ground Control Points (GCPs) was challenging. However, our system achieved precision within the centimeter range, with the error mean of -0.0002m and the standard deviation of 0.0328m, enabling us to accurately detect day to day changes. Despite some operational challenges, the results confirm the feasibility and effectiveness of this innovative method.