Generating fuel consumption maps on prescribed fire experiments from airborne laser scanning

T. Ryan McCarley; Andrew T. Hudak; Benjamin C. Bright; James Cronan; Paige Eagle; Roger D. Ottmar; Adam C. Watts

doi:10.1071/WF23160

RESEARCH ARTICLE (Open Access)

Previous Contents Vol 33(8)

Generating fuel consumption maps on prescribed fire experiments from airborne laser scanning

T. Ryan McCarley

^A , Andrew T. Hudak ^B ^* , Benjamin C. Bright ^B , James Cronan ^C , Paige Eagle ^D , Roger D. Ottmar ^C and Adam C. Watts ^C

+ Author Affiliations

- Author Affiliations

^A University of Idaho, College of Natural Resources, Moscow, ID 83844, USA.

^B U.S. Department of Agriculture Forest Service, Rocky Mountain Research Station, Moscow, ID 83843, USA.

^C U.S. Department of Agriculture Forest Service, Pacific Northwest Research Station, Seattle, WA 98103, USA.

^D University of Washington, School of Environmental and Forest Sciences, Seattle, WA 98195, USA.

^* Correspondence to: andrew.hudak@usda.gov

International Journal of Wildland Fire 33, WF23160 https://doi.org/10.1071/WF23160

Submitted: 3 October 2023 Accepted: 21 June 2024 Published: 5 August 2024

© 2024 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of IAWF. This is an open access article distributed under the Creative Commons Attribution 4.0 International License (CC BY).

Abstract

Background

Characterisation of fuel consumption provides critical insights into fire behaviour, effects, and emissions. Stand-replacing prescribed fire experiments in central Utah offered an opportunity to generate consumption estimates in coordination with other research efforts.

Aims

We sought to generate fuel consumption maps using pre- and post-fire airborne laser scanning (ALS) and ground measurements and to test the spatial transferability of the ALS-derived fuel models.

Methods

Using random forest (RF), we empirically modelled fuel load and estimated consumption from pre- and post-fire differences. We used cross-validation to assess RF model performance and test spatial transferability.

Key results

Consumption estimates for overstory fuels were more precise and accurate than for subcanopy fuels. Transferring RF models to provide consumption estimates in areas without ground training data resulted in loss of precision and accuracy.

Conclusions

Fuel consumption maps were produced and are available for researchers who collected coincident fire behaviour, effects, and emissions data. The precision and accuracy of these data vary by fuel type. Transferability of the models to novel areas depends on the user’s tolerance for error.

Implications

This study fills a critical need in the broader set of research efforts linking fire behaviour, effects, and emissions.

Keywords: airborne laser scanning (ALS), emission source, FASMEE, fire, Fishlake National Forest, fuel beds, fuel consumption, Monroe Mountain, prescribed fire, stand-replacing.

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