Evolving Marked Point Processes with Application to Wildland Fire Regime Modeling

Why Study Wildland Fires?

Our environment is evolving. High-profile wildfires have heightened awareness and concern surrounding wildland fires on populated landscapes. It is important to understand how biotic feedback, climate, the weather, and fire suppression interact to impact fire risk. 

Canadian forest fire management agencies keep detailed historical records on fires, weather and fire suppression. These large and complex spatio-temporal data sets provide a rich set of information for investigation. 

Spatially and temporally-explicit methods are needed that quantify and map the risk of:

• large fires,
• spread events,
• variation in fire severity,
• local concentrations of fires,
• and the potential for a suppressed fire to escape initial attack.

Through the development and application of sophisticated statistical methodology, we can produce future fire regimes that are data-driven and effective.

Areas of Exploration

Marked Point Processes

Includes using marked point process (MPP) methods to model fire ignition points in historical data from Alberta and other provinces. This takes into account weather conditions and features of the natural and built environments. 

Interacting Particle Systems

Includes investigating how best to model smouldering and fire spread using underlying interacting particle systems (IPS).

Fire Regime Models

Includes developing visualization tools for fire managers and property insurers. This is an important outcome of the collaboration with provincial ministries and with the Institute for Catastrophic Loss Reduction (a non-profit institute affiliated with the University of Western Ontario).

Solving Global Challenges

Research Team’s Goal

To develop statistical methods for quantifying and mapping fire risk. Specifically, to model MPP data aggregated over moderate to large temporal and spatial scales.