David Taylor

End-user
About
David Taylor

Lead end user

Over six years, the project used cutting-edge technology to produce near-real-time spatial information on fuel condition, fire hazard and impact to support a wide range of fire risk management and response activities such as hazard reduction burning and pre-positioning firefighting resources and, in the longer term, the new Australian Fire Danger Rating System. Based on the research findings, the researchers have produced the Australian Flammability Monitoring System, an interactive map of immediate fire danger associated with landscape dryness, which uses satellites to collect information about moisture content in trees, shrubs and grass, and assists with prescribed burning efforts and assessment of firefighting resources.
Research team:
This project seeks to optimise the use of earth observing systems for active fire monitoring by exploring issues of scale, accuracy and reliability, and to improve the mapping and estimation of post-fire severity and fuel change through empirical remote sensing observations. Outcomes will enable satellite measures of fire activity to be made, which in turn have the potential to inform or support efforts in bushfire response planning and fire rehabilitation efforts. A particular focus is on the analysis of data obtained from Himawari-8, which is able to provide updated imagery on a 10 minute basis.
This project examined the use of detailed land surface models, satellite measurements and ground-based observations for the monitoring and prediction of landscape dryness. The research team developed a standalone prototype land surface modelling system, called Joint UK Land Environment Simulator based Australian Soil Moisture Information (JASMIN) to produce daily soil moisture analyses at 5km resolution and 4 soil layers. Verification against ground-based soil moisture observations shows that this prototype system is significantly more skilful than both the Keetch–Byram Drought Index and Soil Dryness Index. This project also aimed to improve applications such as fire danger mapping that may require soil moisture information at higher spatial resolution due to the large spatial variability of soil moisture in the landscape, and developed a simple yet skilful model to predict live fuel moisture content for the whole of Australia.

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