Bushfires are an important aspect of the Australian landscape, but also one of our most destructive and costly natural hazards. As populations grow and expand, more people, assets and infrastructure are exposed to bushfire threats.
The effects of climate change further increase the likelihood and severity of such fires, compounding their overall impact on the community. Consequently, there is an urgent need to identify current areas of bushfire risk and how these are likely to change into the future. Better understanding the spatial and temporal distribution of bushfire likelihood, and its relation to population, infrastructure and ecological assets, will help deliver the most effective risk reduction strategies.
To support the decisions that underpin these strategies, spatially explicit and temporally dynamic information is required to accurately reflect landscape hazard and impact characterisation. Remotely sensed earth observations (EO) can help facilitate provision of this information, as they provide a rich source of synoptic, continuous, and repeatable empirical measures of the landscape.
The core aim of this project is to demonstrate how the use of EO data can assist with identifying how bushfire likelihood can change in space and time, allowing more informed and transparent decision-making for reducing bushfire risk. The project will develop an analytical tool – the Adaptive Analytical Bushfire Likelihood (AABL) Tool – that utilises EO data such as vegetation, soil moisture, meteorological and climatic variables as inputs to a model to map the spatial and temporal distribution of bushfire likelihood.
Working with our end users – the SA and WA government – the tool will deliver a new suite of analytical and modelling capabilities and information dashboards that can integrate with and support these State Governments’ Bushfire planning strategy.
P3.23
Project Leader:
Dr Holger Maier, University of Adelaide