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NEON-SD: A 30-m Structural Diversity Product Derived from the NEON Discrete-Return LiDAR Point Cloud
Jianmin Wang1, Dennis H Choi1, Elizabeth LaRue2
1Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA.
Abstract:
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.
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