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