Vision for the project
To develop a system that accurately detects lightning strikes, and provides useful data on the probability of ignition through analysis of lightning characteristics, and vegetation and climate analysis.
Research
Six Fire Neural Network smart lightning detectors have been successfully installed in the ACT. These detectors are able to detect lightning strikes with high temporal and spatial accuracy, and measure lightning characteristics that are responsible for heating and fire ignition.
The installed lightning detectors are part of a system that also uses vegetation and climate data to analyse risk of ignitions from lightning strikes. This system has been used to successfully identify High-Risk Lightning strikes at several actual fires. This and other data are used to validate and further develop the system for the Australian context.
Research is verifying the performance of the lightning detection system and dashboard, including locational accuracy and implications for lightning fire surveillance. Case studies are prepared for each lightning ignition.
Modelling for lightning ignition risk is being further refined, including assessment of the impact of new environmental variables on risk of ignition.
Research is also advancing the understanding of early fire processes, including the windows of opportunity for early fire detection.
Chief Investigator
![](https://brcoe.org/wp-content/uploads/2024/02/Marta-Yebra-aspect-ratio-1-1-3.jpg)
Project Team
Dr Li Zhao