Improving Remote Sensing of Fuel Data on a National Scale

Compiling and sharing existing remote sensing and field observations of fuel attributes such as fuel load, structure and moisture in a national database
A firefighter is trying to put out a bushfire
Who will benefit
State and territory government fire departments, researchers, and the general public through improved decision making from disaster response authorities

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: 

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.

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. A comprehensive report on current methods to retrieve fuel parameters (field-based and remote sensing). https://doi.org/10.5281/zenodo.10807374

  • Adollahi 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). Challenges and Opportunities in Remote Sensing-based Fuel Load Estimation: A Comprehensive Review, International Journal of Applied Earth Observation and Geoinformation (Under review).
  • 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).

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 from Abolfazl 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

  • Terrestrial Ecosystems Research Network (TERN)
  • Department of Climate Change, Energy, the Environment and Water (DCCEEW)
  • CSIRO

Contact the ARDC

  • This field is for validation purposes and should be left unchanged.

Timeframe

August 2021 to December 2023

Current Phase

Complete

ARDC Co-investment

$200,000

Project lead

Australian National University (ANU)