The devastating effects of wildfires cannot be overlooked; these include massive resettlement of people, destruction of property and loss of lives. The considerable distances over which wild fires spread and the rates at which these fires can spread is a major concern as this places considerable challenges on the evacuation mechanisms that need to be put in place. It is therefore crucial for personnel, involved in evacuation planning, to obtain reliable estimates of evacuation times faster than real time, to assist their decision making in response to actual unfolding of events. In this work, we present a hybrid approach, which we refer to as the Hybrid Spatial Discretisation (HSD) for large scale evacuation simulation. The HSD integrates the three spatial representation techniques typically used for representing space usage in evacuation models; namely Coarse regions, Fine nodes and Continuous regions. In this work, we describe the core models constituting the HSD coupled with the approaches used for representing the transition of agents across the different spatial types. Using a large scale case, we demonstrate how the HSD can be used to obtain higher resolution of results where it is most required while optimising the use of available computational resources for the overall simulation. The HSD is seen to provide improvements in run times of more than 40% when compared to modelling the whole area using just the Fine node method.