Integrated wildfire risk assessment of natural and anthropogenic ecosystems based on simulation modeling and remotely sensed data fusion

Even though wildfires constitute a natural phenomenon, fires of high intensity may provoke profound ecological and socioeconomic implications. Primary aim of the paper constitutes the integrated wildfire risk assessment of a fire-prone region in Greece through the simulation modeling of burn probability (BP) and fire intensity to natural and anthropogenic resources (forests, birds' habitats, built-up areas, agricultural fields, energy networks etc.), as well as the identification of resources response to fires of differentiated intensity. So, fire modeling constitutes the primary input to wildfire effects determination through the contribution of fire and resources specialists. The predicted fire effects were quantified and mapped through a spatial index of Net Value Change which aggregates the total predicted change in terms of area gained (e. g. forest regeneration) or lost due to fire impacts. The greatest loss from the total area of each resource/asset was predicted to electricity and renewable energy sources networks (-0.48%), followed by mixed forests (-0.47%), residential buildings and assets (-0.43%), coniferous forests (-0.43%), shrubs (-0.4%), broad-leaved forests (-0.27%) and agricultural crops (-0.19%). The mapping of this index demonstrated that the resources which are at high risk are located close to compact flammable material, following the pattern of increased fire intensity and BP. Hence, this framework can strategically and operationally be used to establish a hierarchical priority-based model for optimal allocation of fire resources. This two-stage of analysis allows for an objective quantification of fire effects to a spatial level (i.e. prefecture) where many biophysical attributes might heavily affect the fire modeling outcomes enhancing the credibility of results.