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Nationally consistent mapping of wildland fuel types across Australia using satellite-derived vegetation structural data

Rakesh Chandra Joshi, Miguel Cruz , Randall Donohue

Abstract

Background: Knowledge of the distribution of wildland fuels across the landscape is necessary for the appropriate use of models to support a broad range of fire management activities. Aims: To develop an automated and nationally consistent method that generates up-to-date spatial fuel type information across Australia. Methods: Data from various space-borne broad-band optical, lidar and radar sensors were combined with land use data to generate structural descriptions of vegetation that were then converted into fuel types. Key results: An Australian fuel type spatial layer was generated using the Bushfire Fuel Classification fuel typology. Evaluation against field measurements revealed accuracies of 89% and 71% for native forest and non-forest fuel types, respectively. This product provides a higher level of spatial and structural detail than previously obtained by other national-level fuel classification approaches in Australia. The data are available and can be readily used in research applications. Implications: This up-to-date fuel type layer will have implications to a range of fire management applications, such as fire behaviour prediction, fire danger forecasting, and risk assessment.

WF24224  Accepted 07 April 2025

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