1. Terrestrial lidar data are known to be useful for estimating the three‐dimensional (3D) distribution of leaf area in forests. This type of product holds great potential for modelling canopy reflectance and light interception to study the links between structure and function. However, little is currently known about its potential and limits in dense forests. Higher leaf area density implies that more laser pulses emitted by the ground‐based instrument are intercepted in lower canopy levels, and the implications of such occlusion effects on radiative transfer simulations are unknown. Occlusion effects can be minimized by increasing the number of locations lidar data is acquired from; how many locations are required for a forest with a given structure? This paper aims to address these knowledge gaps.
2. We acquired terrestrial lidar data using a very high density of scanning positions (5 m between positions) over four dense forest 60 m × 60 m plots along a structural gradient. Occlusion effects were quantified, and the 3D distribution of leaf area density was mapped using voxels (cubic volumes) for four different scan densities (one original and three downsampled). The voxel arrays were then input into a radiative transfer model to simulate bidirectional reflectance factors and vertical fraction of absorbed radiation.
3. We found that the summation of leaf area estimates for all voxels within the plot provided leaf area index (LAI) values close to LAI values estimated using traditional methods at each site. Occluded areas occurred mostly at the top of bottom heavy canopies. Radiative transfer simulations suggest that modelling small scale (<1 m) bidirectional reflectance factors (BRF) and light interception requires the highest scan position density used (5 m between scan positions), particularly at bottom heavy sites, and that 10 m between scan positions can be used for plot scale BRF simulations in forests with foliage density and vertical profiles similar to those tested here.
4. This work establishes some initial guidelines for establishing terrestrial lidar survey protocols for mapping leaf area density in forests. The leaf area density voxel arrays derived are among the most accurate plot‐level 3D characterizations of foliage arrangement produced to date.

中文翻译：

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从多视角地球激光雷达测绘森林叶面积密度

1. 已知地面激光雷达数据可用于估计森林叶片面积的三维（3D）分布。这种类型的产品具有巨大的潜力，可用于建立树冠反射率和光拦截模型，以研究结构与功能之间的联系。但是，目前对于在茂密森林中的潜力和限制知之甚少。较高的叶面积密度意味着地面仪器发出的更多激光脉冲会在较低的树冠层被拦截，并且这种遮挡效应对辐射传输模拟的影响尚不清楚。可以通过增加从中获取激光雷达数据的位置数量来最大程度地减少遮挡效果；具有给定结构的森林需要多少个位置？本文旨在解决这些知识空白。
2. 我们使用沿结构梯度在60 m×60 m的四个茂密森林地块上以很高的扫描位置密度（位置之间5 m）采集地面激光雷达数据。量化了遮挡效果，并使用体素（立方体积）对四种不同的扫描密度（一个原始扫描和三个下采样）绘制了叶面积密度的3D分布图。然后将体素阵列输入到辐射转移模型中，以模拟双向反射系数和吸收辐射的垂直部分。
3. 我们发现，该图中所有体素的叶面积估计值的总和提供了接近每个站点使用传统方法估计的LAI值的叶面积指数（LAI）值。遮挡区域主要发生在底部较重的树冠顶部。辐射传输模拟表明，对小规模（<1 m）双向反射系数（BRF）和光拦截进行建模需要使用所使用的最高扫描位置密度（扫描位置之间为5 m），特别是在底部较重的位置，扫描位置之间的距离为10 m可用于森林密度和垂直剖面类似于此处测试的森林中的地块比例BRF模拟。
4. 这项工作建立了一些初步的指导方针，以建立用于确定森林叶面积密度的地面激光雷达测量协议。得出的叶面积密度体素阵列是迄今为止生产的最准确的叶子排列的图级3D表征之一。