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<p>In the dynamic landscape of urban safety and emergency management, the strategic siting of fire stations emerges as a critical factor for enhancing operational efficiency and public safety. This study introduces a groundbreaking approach based on the Evaluation-Reallocation-Planning (E-R-P) method, tailored for Yanbu Industrial City in Saudi Arabia. This method transforms the decision-making process for fire station placement, offering a blend of current site evaluations, strategic station reallocation, and forward-thinking service planning. At the heart of this research lies the integration of fuzzy logic with Geographic Information System technology and location-allocation models, crafting a robust evaluation framework. The spectrum of algorithms was delved into to dissect the insights from fuzzy logic operations, focusing on three pivotal criteria: socioeconomic dynamics, infrastructure, and urban planning. The findings unveil a stark reality: Yanbu's current fire station network covers 24.8% of the city's structures. However, applying the E-R-P model boosts this coverage by an impressive 18.6%, reshaping the city's emergency response landscape. The fuzzy SUM operator emerged as a critical tool in pinpointing prime locations for new fire stations, which marked a significant stride in disaster readiness. This study redefines emergency service deployment in Yanbu and sets a precedent for other burgeoning cities worldwide. It offers a scalable, data-centric framework for optimizing fire station locations, enhancing urban safety, and streamlining city management.</p>

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Advanced GIS and fuzzy logic integration for strategic fire station placement in Yanbu industrial city, Saudi Arabia

  • 期刊论文

  • 发表日期：

    2025年2月27日

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  • Tamer Ali Al-Sabbagh,
  • Maram M. Almuqataf,
  • Ehab L. Elsaed,
  • Ahmed M. El Kenawy,
  • Ali Younes,
  • Mohamed R. Elkadeem,
  • Kotb M. Kotb

摘要

In the dynamic landscape of urban safety and emergency management, the strategic siting of fire stations emerges as a critical factor for enhancing operational efficiency and public safety. This study introduces a groundbreaking approach based on the Evaluation-Reallocation-Planning (E-R-P) method, tailored for Yanbu Industrial City in Saudi Arabia. This method transforms the decision-making process for fire station placement, offering a blend of current site evaluations, strategic station reallocation, and forward-thinking service planning. At the heart of this research lies the integration of fuzzy logic with Geographic Information System technology and location-allocation models, crafting a robust evaluation framework. The spectrum of algorithms was delved into to dissect the insights from fuzzy logic operations, focusing on three pivotal criteria: socioeconomic dynamics, infrastructure, and urban planning. The findings unveil a stark reality: Yanbu's current fire station network covers 24.8% of the city's structures. However, applying the E-R-P model boosts this coverage by an impressive 18.6%, reshaping the city's emergency response landscape. The fuzzy SUM operator emerged as a critical tool in pinpointing prime locations for new fire stations, which marked a significant stride in disaster readiness. This study redefines emergency service deployment in Yanbu and sets a precedent for other burgeoning cities worldwide. It offers a scalable, data-centric framework for optimizing fire station locations, enhancing urban safety, and streamlining city management.