NSW Forest Plot Network: Ground-Based LiDAR and Ecological Measurements from 2021 Pilot
Updated 1mo ago
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Description
Fourteen native forest plots in New South Wales, Australia, measured in April 2021. The data includes tree height, diameter, canopy cover, species composition, coarse woody debris, fuel hazard, and Biodiversity Assessment Method structure, along with raw and processed terrestrial LiDAR scans. It was collected as a pilot for the NSW Forest Monitoring and Improvement Program and is provided by the Terrestrial Ecosystem Research Network's Data Discovery.
Use Cases
Model forest biomass and carbon stocks based on tree height and diameter measurements.
Classify forest structure and habitat types based on canopy cover and Biodiversity Assessment Method data.
Assess wildfire fuel hazard risk based on recorded fuel hazard and coarse woody debris metrics.
Calibrate airborne or satellite LiDAR models using the ground-based terrestrial LiDAR point clouds.
Analyze species diversity and composition within native forest plots.
Strengths
Includes raw and processed data from terrestrial LiDAR scans, providing detailed 3D structural information.
Covers fourteen distinct forest plots, offering a spatial sample for analysis.
Integrates multiple ecological metrics (e.g., species, fuel hazard, structure) with LiDAR data in a single collection.
Data is from a defined pilot study conducted in April 2021, providing temporal specificity.
Limitations
Row count and dataset size are unknown, which may limit suitability assessment.
Column-level documentation is absent; field semantics must be inferred after download.
The dataset represents a pilot study with fourteen plots, which may limit generalizability.
Provenance
Source
Terrestrial Ecosystem Research Network's Data Discovery
Collection Method
Ground-based field measurements and terrestrial LiDAR scans collected during a pilot study.
Time Range
April 2021
Freshness
Last updated 2026-06-13 11:51:40.602163; freshness should be verified.
Geography
New South Wales, Australia
License is unknown; terms of use should be verified before application.