The Challenge
The efficient national monitoring of fuel conditions is critical to understand bushfire behaviour and risk as highlighted by the Bushfire Earth Observation Taskforce, the NSW Bushfire Inquiry and the National Royal Commission for Natural Disaster Arrangements.
The Approach
This work has contributed towards compiling and sharing existing field and remote sensing observations of fuel attributes such as fuel load, structure and moisture in a national database. This national database is being used to improve remote sensing products and is publicly available to support other research programs. The national fuel attributes databases directly benefit bushfire planning and response, as the fuel data is readily available for assessing bushfire risk, predicting fire behaviour, informing suppression efforts and planning prescribed burns.
This project uses, contributes to and validates the harmonised and aggregated datasets from 2 other Bushfires Data Challenges projects:
- Aggregated and Harmonised Burnt Extent Fire History Data on a National Scale, led by Geoscience Australia
- Aggregating and Harmonising Fuel Data on a National Scale, led by TERN.
In addition, it details the standard protocols to collect information on the key fuel attributes in the field with remote sensing data.
The Outcomes
This project has contributed validated and more reliable data on fuel moisture to the Australian Flammability Monitoring System (AFMS). AFMS is the first national-scale, pre-operational fuel and soil moisture content and flammability monitoring system in Australia, delivering accurate spatial information in near-real time and providing a clear picture of vegetation and soil dryness across the Australian landscape. Access AFMS and learn more about the system.
The dataset is available as follows:
- Abdollahi, A. (2024). Aboveground Biomass Density – International Space Station, LIDAR, L4A and L4B Models, Australia Coverage, 2020. Version 2020. Terrestrial Ecosystem Research Network. (Dataset). https://portal.tern.org.au/metadata/TERN/d173aed1-50f0-4936-9dee-64d23ea1a501
Provision of reliable fuel load remote sensing products will further enhance bushfire response and strategic planning.
The project has also resulted in various publications:
- Abdollahi, A., & Yebra, M. (2023). Identifying Primary Fuel Attributes Known to Influence the Fire Behavior Processes. https://doi.org/10.5281/zenodo.10807374
- Abdollahi A, Yebra M, Forest fuel type classification: Review of remote sensing techniques, constraints and future trends, https://doi.org/10.1016/j.jenvman.2023.118315
- Abdollahi, A., & Yebra, M. (2024). National Aboveground Biomass Estimation in Australia: Fine-grained Examination of Machine Learning Algorithms and Open-access Earth Observation Products, Remote Sensing of Environment (Under submission).
- Abdollahi, A., & Yebra, M. (2025). Challenges and Opportunities in Remote Sensing-Based Fuel Load Estimation for Wildfire Behavior and Management: A Comprehensive Review, https://doi.org/10.3390/rs17030415.
- Abdollahi, A., & Yebra, M. (2023, July 9-14). Remote sensing and machine learning techniques for above-ground biomass estimation on a regional scale. 25th International Congress on Modelling and Simulation, Darwin, NT, Australia. https://doi.org/10.36334/modsim.2023.abdollahi
- Abdollahi, A., & Yebra, M. (2023, August 22-25). Combining satellite data (optical and SAR) for regional above-ground biomass extinction. AFAC23, Brisbane, Qld, Australia. https://media.licdn.com/dms/image/v2/D5622AQHStfkpTJ6qjA/feedshare-shrink_1280/feedshare-shrink_1280/0/1692750694687?e=1730332800&v=beta&t=qJy1YYuR-vMyiV11nT-edIhuBNY-3NbmhHyE4JftD3I
- Abdollahi, A., & Yebra, M. (2024). Harnessing Earth Observation Data and Machine Learning for National Aboveground Biomass Assessment in Australia, Fire Behavior and Fuels Conference, April 15th – 19th, 2024, Canberra, Australia (Oral presentation). https://doi.org/10.5281/zenodo.10807396
The Project Manager, Arnick Abdollahi, has been named finalist for 2 of the 2024 Australian AI Awards in part for his work in this project:
- AI Academic/Researcher of the Year
- AI Rising Star of the Year – Enterprise.
He was also nominated Scientist of the Year in the 2024 Australian Space Awards in part for his work in this project.
Who Will Benefit
This project adds to:
- the Australian Flammability Monitoring System (AFMS) through validated and more reliable data on fuel moisture
- bushfire response and strategic planning by land planning and emergency service authorities through reliable fuel load remote sensing products.
Watch a presentation (DC003) from Arnick Abdollahi, Project Manager, at the November 2023 Bushfire Data Challenges Forum, which described the project’s work in the following areas:
- machine learning models for estimating biomass from remote sensing data
- using GEDI data for lidar-based measurements of vegetation height and structure.
The Partners
- ANU
- Terrestrial Ecosystems Research Network (TERN)
- Department of Climate Change, Energy, the Environment and Water (DCCEEW)
- CSIRO
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