POINT CLOUD DATASET AND FEM FOR A COMPLEX GEOMETRY: THE SAN LUZI BELL TOWER CASE STUDY

Snow depth variations caused by wind are an important factor in avalanche danger, but detailed and up-to-date information is rarely available. We propose a monitoring system, using LiDAR and optical sensors, to measure the snow depth distribution at high spatial and temporal resolution. First results show that we can quantify snow depth changes with an accuracy on the low decimeter level or better, and to identify events such as avalanches or displacement of snow during periods of strong winds.