Mapping snow in forests is important for understanding the snow cover dynamics in these environments in view of hydrological applications and water resources management. Today, Uncrewed Aerial Vehicles (UAVs) are widely used for snow studies due to their rather cheap and flexible operation. UAV-borne Light detection and ranging (LiDAR) systems are a promising technology for sub-canopy snow mapping at high temporal resolutions, concurrently providing information on both the canopy and the below-canopy snow surface. In this pilot study, we used a UAV-LiDAR system to investigate the snow cover dynamics within two steep forested slopes of opposing aspects in the Swiss Alps at both high spatial resolution and unprecedented temporal resolution. Using a Distance to Canopy Edge (DCE) algorithm to characterize local forest structure, snow depth was analyzed in terms of relative position within variable forest cover. The north-exposed site had higher mean snow depths throughout the season compared to the south-exposed site, especially in canopy gaps. Whereas snow depletion rate was consistent throughout the north-exposed site, snow depletion was much faster in the gaps at the south-exposed slope. Correlation coefficients between snow depths and local canopy closure were weaker at the south-exposed (between −0.5 and − 0.7) than at the north-exposed site (between −0.7 and − 0.9), and rapidly deteriorated right after the peak of winter at the south-exposed slope. This indicates shortwave radiation dominates snowmelt processes at this site, which was thought to be spatially uncorrelated to local canopy cover, unlike accumulation and melt processes on the north-exposed slope that generated snow patterns with a high spatial correlation to local canopy cover throughout the entire season. Calculations of incoming sub-canopy shortwave radiation (SWR) for both sites confirmed this assumption. While our findings encourage the use of UAV-borne LiDAR for further investigations of snow cover dynamics in steep forested slopes, we also outline and discuss technical challenges specific to this application. Our insights allow deriving useful recommendations for future studies using UAV-borne LiDAR over a similar environment.

鉴于水文应用和水资源管理，绘制森林中的积雪对于了解这些环境中的积雪动态非常重要。今天，无人驾驶飞行器 (UAV) 因其相当便宜和灵活的操作而被广泛用于雪地研究。无人机载光探测和测距 (LiDAR) 系统是一种很有前途的技术，可用于以高时间分辨率进行亚冠层积雪测绘，同时提供冠层和冠层下雪面的信息。在这项试点研究中，我们使用 UAV-LiDAR 系统以高空间分辨率和前所未有的时间分辨率研究了瑞士阿尔卑斯山两个相反方向的陡峭森林斜坡内的积雪动态。使用树冠边缘距离 (DCE) 算法来表征局部森林结构，根据可变森林覆盖范围内的相对位置分析积雪深度。与朝南的站点相比，朝北的站点在整个季节的平均积雪深度较高，尤其是在树冠间隙中。虽然整个北露地的积雪速度是一致的，但在朝南斜坡的间隙中积雪的速度要快得多。雪深与局部冠层闭合之间的相关系数在南露点（-0.5 和 -0.7 之间）弱于北露点（-0.7 和 -0.9 之间），并且在冬季高峰之后迅速恶化朝南的斜坡。这表明短波辐射在该地点的融雪过程中占主导地位，这被认为在空间上与当地树冠覆盖无关，与北露坡上的积雪和融化过程不同，该过程在整个季节产生与当地树冠覆盖高度空间相关的雪模式。对两个地点的输入冠层下短波辐射 (SWR) 的计算证实了这一假设。虽然我们的研究结果鼓励使用无人机载激光雷达进一步研究陡峭森林斜坡的积雪动态，但我们还概述和讨论了特定于该应用的技术挑战。我们的见解可以为未来在类似环境中使用无人机载激光雷达的研究提供有用的建议。虽然我们的研究结果鼓励使用无人机载激光雷达进一步研究陡峭森林斜坡的积雪动态，但我们还概述和讨论了特定于该应用的技术挑战。我们的见解可以为未来在类似环境中使用无人机载激光雷达的研究提供有用的建议。虽然我们的研究结果鼓励使用无人机载激光雷达进一步研究陡峭森林斜坡的积雪动态，但我们还概述和讨论了特定于该应用的技术挑战。我们的见解可以为未来在类似环境中使用无人机载激光雷达的研究提供有用的建议。