NEON-SD: A 30-m Structural Diversity Product Derived from the NEON Discrete-Return LiDAR Point Cloud.

Autor: Wang J; Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA., Choi DH; Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA., LaRue E; Department of Biological Sciences, The University of Texas at El Paso, El Paso, Texas, USA., Atkins JW; USDA Forest Service, Southern Research Station, New Ellenton, South Carolina, USA., Foster JR; USDA Forest Service, Southern Research Station, Tennessee, Knoxville, USA.; Rubenstein School of Environment and Natural Resources, University of Vermont, Burlington, Vermont, USA., Matthes JH; Harvard Forest, Harvard University, Petersham, Massachusetts, USA., Fahey RT; Department of Natural Resources and the Environment and Center for Environmental Sciences and Engineering, University of Connecticut, Storrs, Connecticut, USA., Fei S; Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA., Hardiman BS; Department of Forestry and Natural Resources, Purdue University, West Lafayette, Indiana, USA. hardimanb@purdue.edu.; Department of Environmental and Ecological Engineering, Purdue University, West Lafayette, Indiana, USA. hardimanb@purdue.edu.
Jazyk: angličtina
Zdroj: Scientific data [Sci Data] 2024 Oct 29; Vol. 11 (1), pp. 1174. Date of Electronic Publication: 2024 Oct 29.
DOI: 10.1038/s41597-024-04018-0
Abstrakt: 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.
(© 2024. The Author(s).)
Databáze: MEDLINE
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