Virtual laser scanning (VLS), the simulation of laser scanning in a computer environment, is a useful tool for field campaign planning, acquisition optimisation, and development and sensitivity analyses of algorithms in various disciplines including forestry research. One key to meaningful VLS is a suitable 3D representation of the objects of interest. For VLS of forests, the way trees are constructed influences both the performance and the realism of the simulations. In this contribution, we analyse how well VLS can reproduce scans of individual trees in a forest. Specifically, we examine how different voxel sizes used to create a virtual forest affect point cloud metrics (e.g., height percentiles) and tree metrics (e.g., tree height and crown base height) derived from simulated point clouds. The level of detail in the voxelisation is dependent on the voxel size, which influences the number of voxel cells of the model. A smaller voxel size (i.e., more voxels) increases the computational cost of laser scanning simulations but allows for more detail in the object representation. We present a method that decouples voxel grid resolution from final voxel cube size by scaling voxels to smaller cubes, whose surface area is proportional to estimated normalised local plant area density. Voxel models are created from terrestrial laser scanning point clouds and then virtually scanned in one airborne and one UAV-borne simulation scenario. Using a comprehensive dataset of spatially overlapping terrestrial, UAV-borne and airborne laser scanning field data, we compare metrics derived from simulated point clouds and from real reference point clouds. Compared to voxel cubes of fixed size with the same base grid size, using scaled voxels greatly improves the agreement of simulated and real point cloud metrics and tree metrics. This can be largely attributed to reduced artificial occlusion effects. The scaled voxels better represent gaps in the canopy, allowing for higher and more realistic crown penetration. Similarly high accuracy in the derived metrics can be achieved using regular fixed-sized voxel models with notably finer resolution, e.g., 0.02 m. But this can pose a computational limitation for running simulations over large forest plots due to the ca. 50 times higher number of filled voxels. We conclude that opaque scaled voxel models enable realistic laser scanning simulations in forests and avoid the high computational cost of small fixed-sized voxels.

虚拟激光扫描 (VLS) 是在计算机环境中模拟激光扫描，是包括林业研究在内的各个学科的野外活动规划、采集优化以及算法开发和敏感性分析的有用工具。有意义的 VLS 的一个关键是感兴趣对象的合适 3D 表示。对于森林的 VLS，树木的构造方式会影响模拟的性能和真实性。在这篇文章中，我们分析了 VLS 可以在多大程度上重现森林中单个树木的扫描。具体而言，我们研究了用于创建虚拟森林的不同体素大小如何影响源自模拟点云的点云指标（例如高度百分位数）和树木指标（例如树高和树冠基部高度）。体素化的细节水平取决于体素大小，这会影响模型的体素单元的数量。较小的体素尺寸（即，更多的体素）增加了激光扫描模拟的计算成本，但允许对象表示中的更多细节。我们提出了一种方法，通过将体素缩放到较小的立方体，将体素网格分辨率与最终的体素立方体尺寸解耦，其表面积与估计的归一化局部植物面积密度成正比。体素模型是从地面激光扫描点云创建的，然后在一种机载和一种无人机载模拟场景中进行虚拟扫描。使用空间重叠的地面、无人机和机载激光扫描场数据的综合数据集，我们比较了从模拟点云和真实参考点云得出的指标。与具有相同基础网格大小的固定大小的体素立方体相比，使用缩放体素大大提高了模拟和真实点云度量和树度量的一致性。这在很大程度上可以归因于减少的人工遮挡效果。缩放的体素可以更好地代表树冠中的间隙，从而实现更高、更逼真的树冠穿透。类似地，可以使用具有显着更精细分辨率（例如 0.02 允许更高和更逼真的牙冠穿透。类似地，可以使用具有显着更精细分辨率（例如 0.02 允许更高和更逼真的牙冠穿透。类似地，可以使用具有显着更精细分辨率（例如 0.02 米。但这可能会对在大型森林图上运行模拟造成计算限制。填充体素的数量增加了 50 倍。我们得出结论，不透明的缩放体素模型能够在森林中进行逼真的激光扫描模拟，并避免小尺寸固定体素的高计算成本。