Wang Jianmin, Choi Dennis H, LaRue Elizabeth, Atkins Jeff W, Foster Jane R, Matthes Jaclyn H, Fahey Robert T, Fei Songlin, Hardiman Brady S
Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA.
Department of Biological Sciences, The University of Texas at El Paso, El Paso, Texas, USA.
Sci Data. 2024 Oct 29;11(1):1174. doi: 10.1038/s41597-024-04018-0.
Structural diversity (SD) characterizes the volume and physical arrangement of biotic components in an ecosystem which control critical ecosystem functions and processes. LiDAR data provides detailed 3-D spatial position information of components and has been widely used to calculate SD. However, the intensive computation of SD metrics from extensive LiDAR datasets is time-consuming and challenging for researchers who lack access to high-performance computing resources. Moreover, a lack of understanding of LiDAR data and algorithms could lead to inconsistent SD metrics. Here, we developed a SD product using the Discrete-Return LiDAR Point Cloud from the NEON Aerial Observation Platform. This product provides SD metrics detailing height, density, openness, and complexity at a spatial resolution of 30 m, aligned to the Landsat grids, for 211 site-years for 45 Terrestrial NEON sites from 2013 to 2022. To accommodate various ecosystems with different understory heights, it includes three different cut-off heights (0.5 m, 2 m, and 5 m). This structural diversity product can enable various applications such as ecosystem productivity estimation and disturbance monitoring.
结构多样性（SD）表征生态系统中生物组分的体积和物理排列，这些生物组分控制着关键的生态系统功能和过程。激光雷达数据提供了组分的详细三维空间位置信息，并已被广泛用于计算结构多样性。然而，从大量激光雷达数据集中密集计算结构多样性指标对于缺乏高性能计算资源的研究人员来说既耗时又具有挑战性。此外，对激光雷达数据和算法缺乏了解可能导致结构多样性指标不一致。在此，我们利用来自NEON航空观测平台的离散回波激光雷达点云开发了一种结构多样性产品。该产品提供了结构多样性指标，详细说明了2013年至2022年期间45个陆地NEON站点211个站点年的高度、密度、开放性和复杂性，空间分辨率为30米，与陆地卫星网格对齐。为了适应不同林下高度的各种生态系统，它包括三种不同的截止高度（0.5米、2米和5米）。这种结构多样性产品可实现各种应用，如生态系统生产力估计和干扰监测。
