Predicting the behaviour and severity of fires requires detailed information about the different types, amounts, moisture content, and spatial arrangement of fuels across the landscape, besides information on terrain and weather conditions. Fuel properties vary both in space and time as they reflect changes in vegetation composition, structure or productivity, and respond to seasonal weather and climate or recover after fire. This makes it difficult, for example, to predict whether fuels in particular locations will be dry enough to burn during the week ahead, or are of a kind that may generate dangerous fire behaviour and pose particular challenges to firefighters.
Current state-wide mapping of fuel properties is relatively coarse-scale and does not account for the fine-scale, short-term, variation that drives actual fire behaviour or determines the success or failure of hazard reduction burns.
Researchers will use combinations of field observations and remote sensing to develop new models for the prediction of landscape-scale variation in fuel types, fuel loads and moisture content across the diverse environments of New South Wales (NSW). This will help fire managers to better quantify fire risks for communities, infrastructure, biodiversity and carbon stocks, and provides input for more informed decision-making on prescribed burning and other management measures.
This research will provide fire managers with the tools to predict the types, quantities and moisture content of fuels across the diverse landscapes of NSW
Dynamic mapping of fire regimes, past present and future
Greenhouse gasses, particulate emissions and air quality
Fire regime guidelines for conservation of threatened species
Indigenous cultural burning: Exploring the links between cultural revitalisation and wellbeing
Optimising cost-effective bushfire risk mitigation via planned burning
Chief Investigator, Western Sydney University
Lead Researcher, Western Sydney University
PhD student , Western Sydney University
