Scientists frequently build statistical models to explain aspects of bushfire risk, such as fire frequency, fire severity and seasonality. However, these models are often developed for specific case study areas and are generally not maintained or evaluated on an ongoing basis. This Melbourne Centre for Data Science-funded project aims to develop a flexible bushfire risk modelling system, capable of dynamically exploring the relationships between wildfire, prescribed fire, vegetation, terrain, landuse and climate. Users will be able to select areas and variables of interest. The system will also have an evaluation capacity, creating predictions based on existing models and comparing these to observations.
Project timeline: 01/2024 – 12/2024