Forests reduce snow accumulation on the ground through canopy interception and subsequent evaporative losses. To understand snow interception and associated hydrological processes, studies have typically relied on resource-intensive point scale measurements derived from weighed trees or indirect measurements that compared snow accumulation between forested sites and nearby clearings. Weighed trees are limited to small or medium-sized trees, and indirect comparisons can be confounded by wind redistribution of snow, branch unloading, and clearing size. A potential alternative method could use terrestrial lidar (light detection and ranging) because three-dimensional lidar point clouds can be generated for any size tree and can be utilized to calculate volume of the intercepted snow. The primary objective of this study was to provide a feasibility assessment for estimating snow interception volume with terrestrial laser scanning (TLS), providing information on challenges and opportunities for future research. During the winters of 2017 and 2018, intercepted snow masses were continuously measured for two model trees suspended from load-cells. Simultaneously, autonomous terrestrial lidar scanning (ATLS) was used to develop volumetric estimates of intercepted snow. Multiplying ATLS volume estimates by snow density estimates (derived from empirical models based on air temperature) enabled the comparison of predicted vs. measured snow mass. Results indicate agreement between predicted and measured values (R² ≥ 0.69, RMSE ≥ 0.91 kg, slope ≥ 0.97, intercept ≥ -1.39) when multiplying TLS snow interception volume with a constant snow density estimate. These results suggest that TLS might be a viable alternative to traditional approaches for mapping snow interception, potentially useful for estimating snow loads on large trees, collecting data in difficult to access terrain, and calibrating snow interception models to new forest types around the globe.

中文翻译：

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寻求一种新颖的基于激光的雪截距估计方法

森林通过冠层截留和随后的蒸发损失来减少地面上的积雪。为了理解积雪和相关的水文过程，研究通常依赖于资源密集的点规模测量，这些测量来自称重的树木或间接测量，它们比较了林地和附近空地之间的积雪。称重的树木仅限于中小型树木，间接比较可能因积雪的风向重新分布，树枝卸载和疏散大小而混淆。一种潜在的替代方法可以使用地面激光雷达（光检测和测距），因为可以为任何大小的树生成三维激光雷达点云，并且可以将其用于计算拦截的积雪量。这项研究的主要目的是为通过地面激光扫描（TLS）估算积雪量提供可行性评估，提供有关未来研究的挑战和机遇的信息。在2017年和2018年冬季，连续测量了称重传感器上悬挂的两棵模型树的截留雪团。同时，使用自主地面激光雷达扫描（ATLS）来制定拦截雪的体积估计。将ATLS体积估算值乘以雪密度估算值（基于空气温度的经验模型得出）可以比较预测的雪量和实测的雪量。结果表明预测值与测量值之间的一致性（R 提供有关未来研究的挑战和机遇的信息。在2017年和2018年冬季，连续测量了称重传感器上悬挂的两棵模型树的截留雪团。同时，使用自主地面激光雷达扫描（ATLS）来制定截获雪量的估计值。将ATLS体积估算值乘以雪密度估算值（基于空气温度的经验模型得出）可以比较预测的雪量和实测的雪量。结果表明预测值与测量值之间的一致性（R 提供有关未来研究的挑战和机遇的信息。在2017年和2018年冬季，连续测量了称重传感器上悬挂的两棵模型树的截留雪团。同时，使用自主地面激光雷达扫描（ATLS）来制定截获雪量的估计值。将ATLS体积估算值乘以雪密度估算值（基于空气温度的经验模型得出）可以比较预测的雪量和实测的雪量。结果表明预测值与测量值之间的一致性（R 自主地面激光雷达扫描（ATLS）用于制定拦截雪的体积估计。将ATLS体积估算值乘以雪密度估算值（基于空气温度的经验模型得出）可以比较预测的雪量和实测的雪量。结果表明预测值与测量值之间的一致性（R 自主地面激光雷达扫描（ATLS）用于制定拦截雪的体积估计。将ATLS体积估算值乘以雪密度估算值（基于空气温度的经验模型得出）可以比较预测的雪量和实测的雪量。结果表明预测值与测量值之间的一致性（R² ≥0.69，RMSE≥0.91公斤，斜率≥0.97，截距≥-1.39）以恒定的雪密度估计值乘以TLS雪拦截体积时。这些结果表明，TLS可能是替代传统方法来绘制积雪的可行方法，对于估计大树上的积雪量，收集难以访问的地形中的数据以及针对全球新的森林类型校准积雪模型可能很有用。