Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona

International Journal of Wildland Fire
By: , and 

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Abstract

Background

Fuel monitoring data are essential to evaluate wildfire risk, plan management activities and evaluate fuel treatment effects. Terrestrial light detection and ranging (lidar) is a field-based 3D scanning technology with great potential to reduce labor-intensive field measurements and provide new depths of vegetation structure data.

Aims

To facilitate the integration of terrestrial lidar into fuel monitoring programs, we developed a model, training process, and Python program that produces canopy fuel, surface fuel and terrain metrics commonly used in fire behavior and fire risk modeling.

Methods

We estimated canopy and surface fuel metrics from terrestrial lidar using a semi-empirical model incorporating physically based modeling of leaf area density and occlusion and a non-destructive model calibration process leveraging Bayesian regression. We compared lidar-derived fuel estimates with conventional fuel estimates across diverse conditions in semi-arid shrubland, woodland and forest in Arizona. We also compared estimates using single- and multiple-scan modes.

Key results

In single-scan mode, our lidar-derived fuel estimates were significantly related to conventional estimates of total canopy fuel load, maximum canopy bulk density, downed surface fuel load and standing surface fuel load.

Implications

Our methods provide opportunities to increase the scalability of fuel monitoring to better understand wildfire risk and treatment effectiveness.

Publication type Article
Publication Subtype Journal Article
Title Canopy and surface fuels measurement using terrestrial lidar single-scan approach in the Mogollon highlands of Arizona
Series title International Journal of Wildland Fire
DOI 10.1071/WF24221
Volume 34
Issue 7
Publication Date June 13, 2025
Year Published 2025
Language English
Publisher CSIRO Publishing
Contributing office(s) Southwest Biological Science Center
Description WF24221, 15 p.
Country United States
State Arizona
Other Geospatial Mogollon Highlands
Additional publication details