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One of the most effective methods of preventing large-scale wildfires is creating fuelbreaks, buffer zones whose purpose is to stop or delay the spread of the fire, providing firefighters an opportunity to control the fire. Fuelbreaks are already applied in several countries and have proven their effectiveness. However, creating fuelbreaks involves deforestation, so the length of the fuelbreaks should be minimized as much as possible. In this paper, we propose the implementation of a greedy Dijkstra-based fuelbreak planning algorithm which identifies locations in which fuelbreaks could significantly reduce the risk of large wildfires, at a relatively low deforestation cost. We demonstrate the stages and output of the algorithm both on artificial forests and on actual forests in Israel. We discuss the factors which determine the cost effectiveness of fuelbreaks from a tree-economy perspective and demonstrate how fuelbreaks’ effectiveness increases as large wildfires become more frequent.
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Shmuel et al. (2023) studied this question.
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