[Truncated abstract] In this thesis, I address the modelling and computer simulation of spatial, eventdriven systems from a computer science perspective. Spatially explicit models of wildland fire (wildfire) behaviour are addressed as the specific application domain. Wildfire behaviour is expressed as a formal model and the associated simulations are compared to existing models and implementations. It is shown that the in- teracting spatial automata formalism provides a general framework for modelling spatial event-driven systems and is appropriate to wildfire systems. The challenge adressed is that of physically realistic modelling of wildfire behaviour in heterogeneous environments . . . Many current models do not incorporate the influence of a neighbourhood (the geometry of the fire front local to an unburnt volume of fuel, for example), but rather determine the propagation of fire using only point information. Whilst neighbourhood-based influence of behaviour is common to cellular automata theory, its use is very rare in existing models of wildfire models. In this thesis, I present the modelling technique and demonstrate its applicability to wildfire systems via a series of simulation experiments, where I reproduce known spatial wildfire dynamics. I conclude that the interacting spatial automata formalism is appropriate as a basis for constructing new computer simulations of wildfire spread behaviour. Simulation results are compared to existing implementations, highlighting the limitations of current models and demonstrating that the new models are capable of greater physical realism.

Wildfires are a natural process critical to the health of forests around the world. However, recent decades have witnessed unprecedented wildfire seasons in many forested regions, leading to a range of unprecedented socio-economic, environmental, and human health impacts. Mitigating these impacts relies in part on fire behaviour prediction systems, which provide information to assist operational wildfire managers with addressing wildfire risk and prioritizing wildfire fighting efforts. A key aspect of fire behaviour prediction systems are rate of spread models that rely on observational and experimental fire behaviour data from naturally occurring wildfires and prescribed burns, respectively. Given the challenge with observing and measuring wildfires in situ, rate of spread models typically rely on a small set of data inputs that are not always representative of the range of wildfires occurring in certain forest types. Furthermore, existing fire behaviour models often lack empirical data on forests that have more recently experienced significant compositional shifts due to climate change or various ecological or anthropogenic disturbances. To address these shortcomings, the objective of this thesis is to establish a method of acquiring empirical fire behaviour data to enhance fire behaviour prediction science through two distinct studies. The first evaluates the utility of monophotogrammetry to extract fire behaviour data from oblique aerial wildfire photographs. The results demonstrate how this approach can provide new and accurate fire spread observations to inform fire behaviour prediction or other aspects of wildland fire science where databases of such wildfire photos exist. The second study is an empirical wildfire spread analysis in forest stands affected by mountain pine beetle (MPB), and utilizes the method of monoplotting to acquire spread rate data from wildfire photographs of grey-attack MPB-affected forest stands. Results from this study further demonstrate the efficacy of the previously established monoplotting technique while providing novel empirical evidence of fire behaviour in grey attack MPB-affected forest stands. Overall, the research results presented in this thesis demonstrate the potential of monophotogrammetry for the acquisition of fire behaviour data and evaluating the results derived from fire behaviour prediction systems in different ecological contexts. This thesis exhibits the potential for this method to expand into other areas of fire behaviour, such as flame or smoke plume dimensions, spotting, and the relationship between fire behaviour and disturbance events such as pest insect outbreaks. / Graduate / 2023-04-14