Lightning-strike sensors help stop bushfires before they start
A US-developed smart sensing system that detects the lightning strikes most likely to start a fire is being fine-tuned to Australian conditions, as part of a collaborative NSW Smart Sensing Network (NSSN) Grand Challenge project. Sensors in the system can detect the component of lightning responsible for ignition; when combined with satellite data on forest fuel load and vegetation moisture levels across Australia, the system can predict if a bushfire is likely to start.
The aim of the project is to provide the earliest possible warning and accurate location of lightning strikes at the greatest risk of starting a fire. The work followed the devastating Australian bushfires in the summer of 2019–20, as a large proportion of these fires were ignited by lightning strikes and extensive areas were burnt largely because of an inability to detect and extinguish ignitions in remote areas before the fires spread and became uncontrollable.
The project is being led by the ANU-Optus Bushfire Research Centre of Excellence — directed by Associate Professor Marta Yebra — in collaboration with Western Sydney University’s Hawkesbury Institute for the Environment, government partners, and Florida-based company Fire Neural Network (FNN). FNN’s goal as a company is to identify the small portion of lightning strikes (less than 10%) that are actually capable of starting a fire, and to do so quickly and accurately.
FNN has developed its onsite lightning detectors to allow for real-time fire ignition tracking with an accuracy of 40 metres within just 40 seconds. Information about the lightning strike and environmental data are fed into the company’s proprietary neural network to determine if the strike was a high-risk lightning strike or not, which firefighting services can rely on to efficiently allocate their resources for containment. The detectors use multiple bands to differentiate between regions of cloud and no-cloud to allow for higher accuracy.
As explained by FNN co-founder and CEO Dr Istvan Kereszy, the NSSN project enabled FNN to develop a fully autonomous high-risk-lightning detector that has its own power supply and internet. He noted, “This approach uses solar power and Starlink internet technology, and it means that the detectors can be quickly deployed anywhere in Australia.”
Yebra said the FNN-developed High-Risk-Lightning Precision Detection System was found to show promise, having successfully identified high-risk lightning strikes near fires ignited by lightning in the Canberra region in February 2023. “While there’s room for refinement, our findings suggest potential for more accurate risk assessment in the future,” Yebra said.
The project has also developed a model that can predict the probability of lightning-caused fire occurrence based on identified key drivers. As explained by ANU’s Dr Colleen Bryant, “Ultimately, the risk of lightning ignition is related to how much moisture is in the system — in the atmosphere and in the fuels.
“Decreasing humidity, soil and fuel moisture, and increasing daily maximum temperatures in the lead-up to thunderstorm activity, are important predictors of lightning fires.”
NSSN Natural Hazards Theme Leader Peter Runcie said the work has been an excellent example of a project funded by the NSSN’s Grand Challenge program, with the project partners now applying for funding to demonstrate the system in a longer bushfire season.
“It has enabled collaborators from government, academia and business to work together to progress the development of new technology solutions for detecting bushfires,” Runcie said.
“Combining lightning detection with the analysis of lightning characteristics and fuel conditions will provide authorities with an improved ability to identify potential bushfire ignitions as they occur.”
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