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

Area of Science:

• Ecology
• Remote Sensing
• Geospatial Analysis

Background:

• Structural diversity (SD) is crucial for ecosystem functions but challenging to compute from LiDAR data.
• Existing methods require high-performance computing and can lead to inconsistent metrics due to data and algorithm complexities.

Purpose of the Study:

• To develop an accessible Structural Diversity (SD) product using Discrete-Return LiDAR data.
• To provide standardized SD metrics for ecological research and applications.

Main Methods:

• Utilized the NEON Airborne Observation Platform's Discrete-Return LiDAR Point Cloud data.
• Calculated SD metrics (height, density, openness, complexity) at 30m resolution, aligned with Landsat grids.
• Incorporated three cut-off heights (0.5m, 2m, 5m) to account for varying understory vegetation.

Main Results:

• Generated a comprehensive SD product covering 211 site-years across 45 NEON terrestrial sites (2013-2022).
• The product offers detailed spatial information on ecosystem structure.
• Metrics are standardized and aligned with existing remote sensing grids for broader usability.

Conclusions:

• The developed SD product democratizes the analysis of ecosystem structural complexity.
• Enables diverse applications including ecosystem productivity estimation and disturbance monitoring.
• Facilitates consistent and efficient ecological research without requiring specialized computational resources.