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Journals / Recep Tayyip Erdoğan Üniversitesi Fen ve Mühendislik Bilimleri Dergisi / 2025 / Cilt: 6 Sayı: 3

Data-Driven Methodology for Emergency Rescue Station Placement: Geographic Information Systems based Multi Criteria Decision Making Approach

Acil Kurtarma İstasyonu Alan Seçimi için Veri Odaklı Metodoloji: Coğrafi Bilgi Sistemleri Tabanlı Çok Kriterli Karar Verme Yaklaşımı

Ömer Kaya(ERZURUM TEKNİK ÜNİVERSİTESİ)0000-0003-1037-5546
Pages
659–684
Publication Date
2025-12-31
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The results show that, in Erzurum, ERS must definitely be established in Yakutiye between the central three districts.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Emergency vehicles are distributed to the scene in order to minimize the damage caused by accidents.
📊
Key Findings & Data:The unpredictable occurrence and timing of accidents generate a complex task in the strategic realization of distribution.
💡
Conclusion & Impact:The results show that, in Erzurum, ERS must definitely be established in Yakutiye between the central three districts.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Acil kurtarma istasyonu · acil yardım aracı · trafik kazası

Abstract

Emergency vehicles are distributed to the scene in order to minimize the damage caused by accidents. The unpredictable occurrence and timing of accidents generate a complex task in the strategic realization of distribution. To overcome the current problem, in thias study, site selection analysis of emergency rescue station (ERS) is provided by Geographic Information Systems (GIS) based multi-criteria decision-making (MCDM) method. To do so, a three-step solution methodology is developed: (i) creating eight different accident categories (AC) by taking into account the accident black spots in order to better understand and analyse the uncertainty occurrence of traffic accidents, (ii) determining the weight values of ACs using the Best-Worst-Method (BWM) and determining the weights of social and transportation criteria with Multi-Influence Factor (MIF) technique, (iii) spatial analysis of ACs via GIS and obtaining a suitability map for potential ERSs, (iv) assignment of alternative ERSs and network analysis of emergency vehicles from ERSs in possible accident scenario. The proposed methodology is applied for Erzurum, one of the provinces with the largest surface area in Türkiye as a case study. The results show that, in Erzurum, ERS must definitely be established in Yakutiye between the central three districts.

Özet

Kazaların neden olduğu zararları en aza indirmek için acil durum araçları olay yerine dağıtılmaktadır. Kazaların öngörülemeyen oluşumu ve zamanlaması, dağıtımın stratejik gerçekleştirilmesinde karmaşık bir zorluk oluşturur. Mevcut sorunun üstesinden gelmek için bu çalışmada, Coğrafi Bilgi Sistemleri (CBS) tabanlı çok kriterli karar verme (ÇKKV) yöntemi ile acil kurtarma istasyonu (ERS) yer seçimi analizi sağlanmıştır. Bunu yapmak için üç adımlı bir çözüm metodolojisi geliştirilmiştir: (i) trafik kazalarının belirsizliğini daha iyi anlamak ve analiz etmek için kaza kara noktalarını dikkate alarak sekiz farklı kaza kategorisinin (AC) oluşturulması, (ii) En İyi-En Kötü-Yöntemi (BWM) kullanılarak AC'lerin ağırlık değerlerini belirlenmesi ve Çoklu Etki Faktörü (MIF) tekniği ile sosyal ve ulaşım kriterlerinin ağırlıklarını belirlenmesi, (iii) AC'lerin CBS ile mekansal analizinin yapılması ve potansiyel ERS'ler için uygunluk haritası elde edilmesi, (iv) olası kaza senaryosunda alternatif ERS'lerin atanması ve ERS'lerden acil durum araçlarının ağ analizinin yapılması. Önerilen metodoloji, Türkiye'nin en büyük yüzölçümüne sahip illerinden biri olan Erzurum için bir vaka çalışması olarak uygulanmıştır. Sonuçlar, Erzurum'da, Yakutiye'de merkez üç ilçe arasında ERS'nin kesinlikle kurulması gerektiğini göstermektedir.

🔖

Cite This Article

Kaya, Ö. (2025). Data-Driven Methodology for Emergency Rescue Station Placement: Geographic Information Systems based Multi Criteria Decision Making Approach. Recep Tayyip Erdoğan Üniversitesi Fen ve Mühendislik Bilimleri Dergisi, Cilt: 6 Sayı: 3, 659–684. https://doi.org/10.53501/rteufemud.1611414

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