Scion’s Fire team take part in Bushfires DataQuest 2020

Members of Scion’s Rural Fire Research team have been taking part in an Australasian bushfires data quest research challenge.

This Data Quest seeks to answer the question, “Can we use Machine Learning to help prevent, detect, control, mitigate and better recover from wildfires?” Four Data Quest teams are focused on three related challenges – Improved fuel assessment, Early fire detection, and Improved fire behaviour models using machine learning.

The Data Quest is organised in collaboration with Frontier Developments and local partners that include the Minderoo Foundation, NSW Government and ANU Institute for Space. Data Quests aim to solve difficult problems using artificial intelligence and machine learning, often combining multiple types of data (such as remote sensing) and operating on the forefront of technology. The Data Quest is structured as a research sprint, where teams of experts in machine learning come together with subject matter experts, in this case on bushfires and remote sensing, for an intensive focussed week-long quest on the problem at hand.

Scion’s Ilze Pretorius and Kate Melnik are part of the team working on the Early fire detection problem. Tara Strand is also a member of the Science Advisory faculty for the Challenge.

The Bushfires Data Quest began on July 27, with the main research sprint taking place from August 7-14. It concludes with an online showcase of results on September 16, which is open to anyone to attend.

More information on the Bushfire Data Quest Challenge can be found at

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