Quantifying snow-cover dynamics from time-lapse photography in the High Tatras (Slovakia)

Abstract

Snow cover is a critical component of the hydrological cycle in mountain regions. Monitoring mountain snow cover has become increasingly urgent due to climate warming. To analyse its seasonal dynamics, manual snow-depth measurements with a snow stake at the Skalnaté Pleso Observatory (1778 m a.s.l.) were complemented by time-lapse trail-camera observations of the surrounding area. Analyses of time-lapse images over four winter seasons (2021/22–2024/25) revealed pronounced interannual variability in snow cover dynamics and showed that the camera reliably captured snow conditions during both continuous-snow and snow-poor winters. In the 2024/25 season, average snow depth was exceptionally low (9.5 cm), while average snow cover remained around 50%, suggesting far-reaching consequences for environmental systems. A clear non-linear relationship was found between snow depth and camera-derived snow cover, with rapid increases in areal cover at low snow depths and saturation at approximately 30–40 cm (R² = 0.76). Time-lapse imagery, after image alignment, mask application, and automatic image classification, proved to be a robust and cost-effective complement to point-based measurements.