Primary goal
Map fire risk probability, predict fire points and model fire spread across flammable forest areas in Australia to develop a fire risk probability model using a two-step analytic hierarchy process approach with cross-validations of support vector machine model outputs.
Key outcomes
- A fire risk probability model will be developed using a two-step analytic hierarchy process approach, with cross validation of support vector machine (SVM) model outputs.
- Fire points will be predicted using an SVM model, incorporating data layers such as elevation, slope, aspect, soil moisture, land surface temperature, and vegetation type for training.
- Meteorological data from a Weather Research and Forecasting model will be integrated into the fire spread model to enhance prediction accuracy.
Progress
This project commenced in 2022 and was completed in July 2025.
Lead researchers
- Sanjeev Srivastava
- Mauricio Acuna
- Tom Lewis
- Ruth Luscombe
- Harikesh Singh
Project funded by
SmartSat Cooperative Research Centre
Sustainable Development Goals
This project works towards these UN Sustainable Development Goals:
- SDG 9: Industry, Innovation and Infrastructure
- SDG 15: Life on Land
Learn more about this project.