Journals / GSI Journals Serie C: Advancements in Information Sciences and Technologies / 2026 / Cilt: 8 Sayı: 2

GIS-Based Network Analyses for the Optimization of Natural Gas Distribution Field Operations: A Case Study of Eskişehir

CBS Tabanlı Ağ Analizleri ile Doğal Gaz Dağıtım Saha Operasyonlarının Optimizasyonu: Eskişehir Örneği

Fulya Akan(ESKİŞEHİR TEKNİK ÜNİVERSİTESİ)0009-0009-0007-8645
Pages
4–18
Publication Date
2026-10-29
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

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

The results demonstrate that GIS-based network analyses provide a robust framework for optimising both emergency response and routine field operations in natural gas distribution systems from operational and economic perspectives.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Effective planning of emergency response and routine field operations in natural gas distribution is critical to ensuring service quality, operational efficiency, and cost control.
📊
Key Findings & Data:This study examines, through an applied case study, how Geographic Information Systems (GIS)-based network analyses can be integrated into a comprehensive decision-support framework for natural gas distribution operations.
💡
Conclusion & Impact:The results demonstrate that GIS-based network analyses provide a robust framework for optimising both emergency response and routine field operations in natural gas distribution systems from operational and economic perspectives.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Coğrafi Bilgi Sistemleri (CBS) · Ağ Analizi · Rota Optimizasyonu

Abstract

Effective planning of emergency response and routine field operations in natural gas distribution is critical to ensuring service quality, operational efficiency, and cost control. This study examines, through an applied case study, how Geographic Information Systems (GIS)-based network analyses can be integrated into a comprehensive decision-support framework for natural gas distribution operations. The study focuses on the Tepebaşı and Odunpazarı districts of Eskişehir, Turkey, and is based on natural gas network inventory data, the urban road network (ESRI Network Dataset), and real-world operational field data. Service area analysis was employed to evaluate the accessibility of emergency response teams, while location-allocation analysis was used to assess the spatial adequacy of existing and candidate emergency response centres in relation to demand distribution. Closest facility analysis was applied to highlight the significance of network-based travel time in emergency response decision-making. For routine field operations, route analysis and the vehicle routing problem (VRP) were implemented, enabling a comparative evaluation of team numbers and route configurations under different service time, team capacity, and cost scenarios. The results demonstrate that GIS-based network analyses provide a robust framework for optimising both emergency response and routine field operations in natural gas distribution systems from operational and economic perspectives. The proposed approach offers a transferable, integrated decision-support framework that can be effectively adopted by utility companies and infrastructure management authorities.

Özet

Doğal gaz dağıtım faaliyetlerinde acil müdahale ve rutin saha operasyonlarının etkin biçimde planlanması, hizmet kalitesi, operasyonel verimlilik ve maliyet yönetimi açısından kritik öneme sahiptir. Bu çalışmada, doğal gaz dağıtım süreçlerinde Coğrafi Bilgi Sistemleri (CBS) tabanlı ağ analizlerinin bütünleşik bir karar destek çerçevesi içerisinde nasıl kullanılabileceği uygulamalı olarak ele alınmıştır. Çalışma alanı olarak Eskişehir ili Tepebaşı ve Odunpazarı ilçeleri seçilmiş; analizlerde doğal gaz dağıtım şebekesi envanteri, kentsel yol ağı (ESRI Network Dataset) ve gerçek saha operasyonlarına ait veriler kullanılmıştır. Çalışma kapsamında, servis alanı analizi ile acil müdahale ekiplerinin erişilebilirliği değerlendirilmiş; yer-tahsisi analizi ile mevcut ve aday acil ekip merkezlerinin talep yapısına göre mekânsal yeterliliği incelenmiştir. En yakın tesis analizi, acil çağrılara müdahalede ağ temelli erişim süresinin belirleyici rolünü ortaya koymak amacıyla uygulanmıştır. Rutin saha operasyonları için ise güzergâh ve araç rotalama problemi (VRP) analizleri gerçekleştirilmiş; farklı servis süresi, ekip kapasitesi ve maliyet senaryoları altında ekip sayısı ve rota yapıları karşılaştırılmıştır. Elde edilen bulgular, CBS tabanlı ağ analizlerinin doğal gaz dağıtım faaliyetlerinde acil müdahale ve günlük saha operasyonlarının hem operasyonel hem de ekonomik açıdan optimize edilmesine olanak sağladığını göstermektedir. Çalışma, uygulayıcı kurumlar için genellenebilir ve bütüncül bir karar destek yaklaşımı sunmaktadır.

🔖

Cite This Article

Akan, F. (2026). GIS-Based Network Analyses for the Optimization of Natural Gas Distribution Field Operations: A Case Study of Eskişehir. GSI Journals Serie C: Advancements in Information Sciences and Technologies, Cilt: 8 Sayı: 2, 4–18. https://ajindex.com/articles/1667986

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (17)

  1. Al-Hassani, H. S., & Al-Shaikh, A. A. (2018). A GIS-based model for risk assessment of urban gas pipeline networks. Journal of Loss Prevention in the Process Industries, 52, 1–10. https://doi.org/10.1016/j.jlp.2018.01.006
  2. BP. (2022). Statistical review of world energy 2022. BP p.l.c. https://www.bp.com/statisticalreview
  3. Church, R. L., & Murray, A. T. (2009). Business site selection, location analysis, and GIS. John Wiley & Sons.
  4. Curtin, K. M. (2007). Network analysis in geographic information science: Review, assessment, and projections. Cartography and Geographic Information Science, 34(2), 103–111. https://doi.org/10.1559/152304007781002163
  5. Enerji Piyasası Düzenleme Kurumu. (2022). Doğal gaz piyasası 2022 yılı sektör raporu. https://www.epdk.gov.tr
  6. Erden, T., & Coşkun, M. Z. (2016). CBS tabanlı ağ analizleri ile acil servis planlaması. Harita Dergisi, 155, 1–12.
  7. Fischer, M. M. (2003). GIS and network analysis. In D. A. Hensher & K. J. Button (Eds.), Handbook of transport geography and spatial systems (pp. 391–408). Elsevier.
  8. International Energy Agency. (2023). World energy outlook 2023. https://www.iea.org
  9. Liu, Y., Luo, J., & Li, Z. (2018). GIS-based vehicle routing optimisation for urban infrastructure service operations. Computers, Environment and Urban Systems, 69, 1-12.
  10. Ma, L., Cheng, S., & Li, M. (2013). Quantitative risk analysis of urban natural gas pipeline networks using GIS. Journal of Loss Prevention in the Process Industries, 26(4), 637–646. https://doi.org/10.1016/j.jlp.2013.03.010
  11. Miller, H. J., & Shaw, S.-L. (2001). Geographic information systems for transportation: Principles and applications. Oxford University Press.
  12. Rahman, M. S., & Smith, D. K. (2019). GIS-based spatial optimisation for emergency response facility location planning. International Journal of Disaster Risk Reduction, 38, 101197.
  13. Sarıkaya, Y., Yanalak, M., & Karaman, H. (2022). GIS-based location selection of natural gas emergency response team centers: The case of Istanbul. Journal of Urban Planning and Development, 148(4), 04022047. https://doi.org/10.1061/(ASCE)UP.1943-5444.0000829
  14. Toth, P., & Vigo, D. (2014). Vehicle routing: Problems, methods, and applications (2nd ed.). SIAM. https://doi.org/10.1137/1.9781611973594
  15. U.S. Energy Information Administration. (2023). International energy outlook 2023. https://www.eia.gov/international/
  16. Wang, J., & Cheng, T. (2015). A spatial–temporal vehicle routing problem with time-dependent travel speeds. Transportation Research Part C: Emerging Technologies, 52, 30–45.
  17. Yomralıoğlu, T. (2010). Coğrafi bilgi sistemleri: Temel kavramlar ve uygulamalar (5. baskı). Nobel Akademik Yayıncılık.