Forest Fuel Point Clouds And FDS Simulation Inputs From Oregon

Five segmented LAS point clouds represent different fuel classes from a 40 x 40 meter Pinus ponderosa forest plot in Oregon, USA. The dataset includes associated Bulk Density Files and Fire Dynamics Simulator input files for three separate wildfire simulations. Resources were collected in summer 2019 using a Riegl-VZ400i lidar scanner.

Use Cases

• Classify forest fuel types using the five segmented LAS point clouds for fire behavior modeling.
• Configure Fire Dynamics Simulator (FDS) wildfire simulations using the provided input files.
• Calculate fuel bulk density metrics for different fuel classes using the associated BDF files.
• Model fire spread in a Pinus ponderosa ecosystem by integrating point cloud geometry with FDS simulation parameters.

Strengths

• Contains five distinct, segmented LAS point clouds for different fuel classes.
• Includes complete FDS input configuration files for three separate simulations.
• Data is geospatially specific to a 40 x 40 meter forest plot in Oregon, USA.
• Point clouds were captured with a high-precision Riegl-VZ400i terrestrial lidar scanner.

Limitations

• Limited spatial scope to a single 40x40 meter plot, reducing generalizability.
• Temporal coverage is restricted to summer 2019, lacking seasonal or multi-year data.
• Dataset size and row/column counts are unknown, complicating resource planning.

Provenance

Source

Environmental Information Data Centre

Collection Method

Terrestrial lidar scanning with a Riegl-VZ400i and manual configuration of FDS simulation files.

Time Range

Summer 2019

Freshness

Data collected in 2019; metadata last updated in 2026.

Geography

Sycan Marsh, Oregon, USA