Strongly affected by the escalating impacts of climate change, wildfires have been increasing in frequency and severity around the world. The primary aim of this study was the development of specific territorial measures—estimating the optimal locations of firefighting resources—to enhance the spatial resilience to wildfires in the fire-prone region of Chalkidiki Prefecture in northern Greece. These measures focus on the resistance to wildfires and the adaptation of strategies to wildfire management, based on the estimation of burn probability, including the effect of anthropogenic factors on fire ignition. The proposed location schemes of firefighting resources such as vehicles consider both the susceptibility to fire and the influence of the topography on travel simulation, highlighting the impact of road slope on the initial firefighting attack. The spatial scheme, as well as the number of required firefighting forces is totally differentiated due to slope impact. When we ignore the topography effect, a minimum number of fire vehicles is required to achieve the maximization of coverage (99.2% of the entire study area) giving priority to the most susceptible regions (that is, employing 18 of 24 available fire vehicles). But when we adopt more realistic conditions that integrate the slope effect with travel time, the model finds an optimal solution that requires more resources (that is, employing all 24 available fire vehicles) to maximize the coverage of the most vulnerable regions within 27 min. This process achieves 80% of total coverage. The proposed methodology is characterized by a high degree of flexibility, and provides optimized solutions to decision makers, while considering key factors that greatly affect the effectiveness of the initial firefighting attack.
CITATION STYLE
Sakellariou, S., Sfougaris, A., Christopoulou, O., & Tampekis, S. (2023). Spatial Resilience to Wildfires through the Optimal Deployment of Firefighting Resources: Impact of Topography on Initial Attack Effectiveness. International Journal of Disaster Risk Science, 14(1), 98–112. https://doi.org/10.1007/s13753-023-00464-3
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