Description:

This project will examine how topographic factors influence the spatial distribution of lightning ignitions. Quantitative analyses of lightning ignition and topographic (and other) data will be used to derive models that relate lightning ignition location to variables related to terrain, such as slope, aspect, scaled elevation residual, local relief, etc. These models will complement other ignition detection systems being developed to enable more efficient and effective fire detection filtering of ignition data. It can also be used to assist with targeting prescribed burning and to inform ensemble fire spread prediction. 

Research objectives

Topography has an influence on the atmosphere well above the surface layer and affect storm tracks and lightning patterns. Topography can also affect whether an ignition will develop into a running bushfire. However, the relationship between topographic features and bushfires ignited by lightning is still not understood. This project will used data-driven techniques accomplish the following research objectives: 

  • Investigate the statistical relationship between topography and lightning ignition. 
  • Identify the most significant topographic factors influencing lightning ignitions. 
  • Develop a model to predict the most likely location of lightning ignition based on topographic, and other relevant drivers. 

In addition, the project will deliver a comprehensive dataset of lightning ignitions and a suite of derived topographic variables such as local relief, ruggedness and (multi-scale) elevation residual. These data will form a catalogue that can be added to over time to support ongoing analyses of lightning ignition patterns. 

 

 

Supervisor(s):

Jason Sharples

School

School of Science

Research Area

Applied & Industrial Mathematics | Environmental Geography | Resilient Infrastructure