A dynamic and evidence-based approach to mapping burn potential
Richard van Dongen A * , Jaume Ruscalleda-Alvarez A B and Carl R. Gosper A
+ Author Affiliations
- Author Affiliations
A Biodiversity and Conservation Science, Department of Biodiversity, Conservation and Attractions, 17 Dick Perry Avenue, Kensington, WA 6151, Australia.
B Great Victoria Desert Biodiversity Trust, Perth, WA 6000, Australia.
* Correspondence to: ricky.vandongen@dbca.wa.gov.au
International Journal of Wildland Fire 32(2) 164-177 https://doi.org/10.1071/WF22077
Submitted: 20 May 2022 Accepted: 19 November 2022 Published: 9 December 2022
© 2023 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-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND)
Abstract
Background: Fire management is a crucial part of managing ecosystems. The years since last burn (YSLB) metric is commonly used in fire planning to predict when an area might be suitable to burn; however, this metric fails to account for variable recovery due to climate variability.
Aim: The aim of this study was to develop a predictor of when an area may be able to ‘carry’ fire based on observed patterns of vegetation recovery and fire occurrence that is responsive to climate variability.
Methods: Fire history maps and Landsat satellite imagery within the Great Victoria Desert of Australia were used to map vegetation recovery following fire. Burn potential models were then created by calculating the distributions of YSLB and vegetation recovery values for areas that subsequently burnt.
Key result: A burn potential model based on vegetation recovery is a better predictor of when an area is likely to burn than a model based on YSLB.
Conclusions: A burn potential model based on vegetation recovery provides an evidence-based and dynamic assessment of whether an area is likely to burn.
Implications: This approach provides a model that is responsive to climate variability that can assist fire managers in burn planning and assessing fire risk.
Keywords: fire management, fire mapping, fire planning, fire recovery, high-resolution imagery, Landsat, LiDAR, vegetation cover.
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