biostudies-literatureWang JUnited States Department of Agriculture | National Institute of Food and Agriculture (NIFA)National Science Foundation (NSF)United States Department of Agriculture | National Institute of Food and AgricultureNational Science Foundation1174https://www.ebi.ac.uk/biostudies/studies/S-EPMC11522374biostudies-literatureUnknown11(1)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 resoluScientific dataNEON-SD: A 30-m Structural Diversity Product Derived from the NEON Discrete-Return LiDAR Point Cloud.PMC115223741926538192645419264422023-68012-38992Choi DHMatthes JHAtkins JWFei SHardiman BSFoster JRLaRue EFahey RTWang JfalseNEON-SD: A 30-m Structural Diversity Product Derived from the NEON Discrete-Return LiDAR Point Cloud.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 resolu2024-01-01T00:00:00Z2024 Oct2026-07-15T17:45:40.812Z2025-04-04T03:01:02.983ZS-EPMC115223743947244710.1038/s41597-024-04018-0