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<p>Forest fires, one of the largest natural disasters, have had negative consequences for centuries. Today, these damages continue due to various negligences or climate influences. In large cities, this danger brings along significant problems. This study focuses on the Izmir region, a metropolitan city in Türkiye, where the ecosystem and biodiversity are damaged by fire every year. In order to prevent these fires, it is necessary to identify areas with high fire potential and develop fire management strategies there. In this context, the aim of the study is to obtain a comprehensive fire risk map in GIS and routes for early fire detection with the help of UAVs. The risk map was created by combining 14 maps, including topographic, meteorological, human-induced, historical fire data, and vegetation data. As a result of the findings, single and multi-center routes were obtained using K-Means and LCP methods with UAVs divided into three categories of high, medium and low cost in high fire risk points. It has been found that more efficient results are achieved with a multi-center approach and medium-cost UAVs. This holistic approach proposed within the scope of forest fire management helps develop more effective strategies.</p>

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A GIS-based forest fire risk mapping and UAV deployment planning: the case of Izmir

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年1月22日

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  • K. Okta,
  • M. Oturakçı,
  • D. T. Eliiyi,
  • E. Ekinci,
  • U. Eliiyi

摘要

Forest fires, one of the largest natural disasters, have had negative consequences for centuries. Today, these damages continue due to various negligences or climate influences. In large cities, this danger brings along significant problems. This study focuses on the Izmir region, a metropolitan city in Türkiye, where the ecosystem and biodiversity are damaged by fire every year. In order to prevent these fires, it is necessary to identify areas with high fire potential and develop fire management strategies there. In this context, the aim of the study is to obtain a comprehensive fire risk map in GIS and routes for early fire detection with the help of UAVs. The risk map was created by combining 14 maps, including topographic, meteorological, human-induced, historical fire data, and vegetation data. As a result of the findings, single and multi-center routes were obtained using K-Means and LCP methods with UAVs divided into three categories of high, medium and low cost in high fire risk points. It has been found that more efficient results are achieved with a multi-center approach and medium-cost UAVs. This holistic approach proposed within the scope of forest fire management helps develop more effective strategies.