Şanlıurfa'da Kentsel İnşaat Mühendisliği Bağlamında Coğrafi Bilgi Sistemleri (CBS) Destekli AHP Kullanılarak Telekomünikasyon Altyapısı İçin Saha Uygunluğunun Değerlendirilmesi

Abstract

Mobil cihazlarla iletişimi sağlamak amacıyla kule, direk, çatı ve bina yüzeylerine yerleştirilen alıcı, verici ve güç ünitelerinden oluşan baz istasyonları, mobil ağların temel bileşenleridir. Özellikle kırsal ve dağlık alanlarda kurulum süreçleri, zorlu arazi koşulları nedeniyle çok kriterli kararlar gerektiren karmaşık bir mühendislik problemi haline gelmektedir. Bu bağlamda, saha uygunluk analizi kentsel altyapı planlaması ve saha seçimi mühendisliğinde kritik bir rol oynamaktadır. Bu çalışmada, Şanlıurfa ili genelinde baz istasyonlarının yerleştirilmesi için en uygun yerleri belirlemek amacıyla Coğrafi Bilgi Sistemleri (CBS) ve Analitik Hiyerarşi Süreci (AHP) yöntemleri birlikte kullanılmıştır. Yer seçimi sürecinde yağış, toprak tipi, eğim, arazi kullanımı, jeoloji ve drenaj yoğunluğu gibi çevresel parametreler, kule mesafesi, yüksekliği ve iletişim kapsama alanı gibi teknik mühendislik kriterleriyle birlikte değerlendirilmiştir. AHP yöntemi sonucunda bu kriterler ağırlıklandırılmış, kule mesafesine %30, yüksekliğe %25, arazi kullanımına %20, eğime %15 ve drenaj yoğunluğuna %10 önem verilmiştir. Elde edilen saha uygunluk haritası, Şanlıurfa ilindeki alanın yaklaşık %45'inin baz istasyonu kurulumuna uygun olduğunu ortaya koymuştur. Bu çalışma, inşaat mühendisliği alanında saha seçimi, altyapı planlaması ve çevresel etki analizi konularında karar desteği sağlayan bir mühendislik yaklaşımı sunmaktadır. Elde edilen bulgular yalnızca teorik olmakla kalmayıp, aynı zamanda yerel yönetimler ve telekomünikasyon sektörü için altyapı projelerinin fizibilite ve uygulama süreçlerine entegre edilebilecek içgörüler de sunmaktadır.

Keywords

• AHP Metodu
• CBS
• Çok Kriterli Karar Verme
• Baz İstasyonu Yer Seçimi
• Telekomünikasyon Altyapısı
• Çevresel Parametreler

Evaluation of Site Suitability for Telecommunications Infrastructure Using GIS-Supported AHP in the Context of Urban Construction Engineering in Sanliurfa

Abstract

Base station site selection is a critical engineering problem that requires the integration of technical, environmental, and geographical factors to ensure efficient and sustainable telecommunication infrastructure. This study aims to identify the most suitable locations for base station deployment in Şanlıurfa Province, Türkiye, by integrating Geographic Information Systems (GIS) with the Analytic Hierarchy Process (AHP) and the Bayesian Best–Worst Method (BBWM) to improve the reliability of multi-criteria decision-making. A GIS-based multi-criteria decision-making framework was established using six environmental and engineering evaluation criteria, namely precipitation, soil type, slope, land use, geological structure, and drainage density. Criterion weights obtained from AHP and BBWM were integrated into a GIS-based weighted overlay analysis to generate a spatial suitability map for base station installation. The results indicate that 48% of the study area was classified as highly suitable for base station deployment, including 7% (1,346.94 km²) identified as the most suitable and 41% (7,889.22 km²) as suitable. Additionally, 20% (3,848.40 km²) of the area was classified as moderately suitable, while the remaining 32% (6,157.44 km²) exhibited low suitability. The findings demonstrate that the proposed GIS-based multi-criteria framework provides an effective decision-support tool for optimizing telecommunication infrastructure planning and site selection while considering environmental constraints and engineering feasibility. The proposed approach also supports sustainable urban infrastructure planning and informed land-use decision-making in regions with similar geographical and environmental characteristics.

Keywords

• AHP Method
• GIS
• Multi Criteria Decision Making (MDCM)
• Base Station Sitting
• Site Suitability Analysys
• Telecommunication Infrastructure
• Enviromental Parameters

References

1. [1] Ahmadi, H., Kaya, O. A., Babadagi, E., Savas, T., & Pekkan, E. (2020). GIS-based groundwater potentiality mapping using AHP and FR models in central antalya, Turkey. Environmental Sciences Proceedings, 5(1), 11. https://doi.org/10.3390/IECG2020-08741
2. [2] Aslan, V., Sepetcioglu, M. Y., & Yasar, A. O. (2022). Evaluation of Sanliurfa Concrete Technology with GIS Supported AHP Method as a Useful Tool in Tecnical Measurement. Turkish Hydraulics Journal, 6(2), 14-21. http://www.dergipark.org.tr
3. [3] Aslan, V. (2023). Evaluation of Sanliurfa Karakopru basin groundwater potential for sustainability with GIS-based AHP and TOPSIS methods. Sustainable Water Resources Management, 9(3), 77.https://doi.org/10.1007/s40899-023-00844-z
4. [4] Celik, R. (2024). Spatial Prediction of Groundwater Potential of Upper Tigris Basin Mapping in Türkiye with GIS-Based Multicriteria Decision Making (MCDM) Method. Turkish Journal of Civil Engineering, 35(5), 29-49. https://doi.org/10.18400/tjce.1358155
5. [5] Demirtas, M., & Ahmet, B. I. B. I. (2017). Development of an Interface for Real-Time Recording of Base Station Measurements Depending on Location. Journal of Information Technologies, 10(4), 451-460. https://doi.org/10.17671/gazibtd.316658
6. [6] Erdogan Yuksel, E., Karan, O. F., & Akay, A. E. (2024). Spatio-Temporal Analysis of Erosion Risk Assessment Using GIS-Based AHP Method: A Case Study of Doğancı Dam Watershed in Bursa (Türkiye). Forests, 15(7), 1135. https://doi.org/10.3390/f15071135
7. [7] Gazete, R. (2018). Regulation Amending the Regulation on Determination, Control and Supervision of Exposure Limit Values of Electromagnetic Field Intensity Originating from Electronic Communication Devices According to International Standards, (29497), https://www.resmigazete.gov.tr
8. [8] Guzel, A. (2012). Evaluation Of “1927 Urfa Annual” Based On Its Historical Geography Features. Gaziantep University Journal of Social Sciences, 11(1), 233-262. https://dergipark.org.tr/en/pub/jss/issue/24240/256978

9. [9] Khan, M. S. A., Etonyeaku, L. C., Kabir, G., Billah, M., & Dutta, S. (2022). Bridge infrastructure resilience assessment against seismic hazard using Bayesian best worst method. Canadian Journal of Civil Engineering, 49(11), 1669-1685. https://doi.org/10.1139/cjce-2021-050
10. [10] Karaaslan, A., & Aydin, S. (2020). Evaluation of renewable energy sources with multi-criteria decision making techniques: The example of Turkey. Ataturk University Journal of Economics and Administrative Sciences, 34(4), 1351-1375. https://doi.org/10.16951/atauniiibd.749466
11. [11] Khodakarami, L., Hussein, S. S., Sabir, S., Salam Aziz, R., Salih, M., & Adnan, H. (2025). An integrated GIS–visibility–AHP-TOPSIS framework for assessing and optimizing mobile tower siting in mountainous rural regions. Spatial Information Research, 33(5), 1-14. https://doi.org/10.1007/s41324-025-00639-8
12. [12] Liang, M., Li, W., Ji, J., Zhou, Z., Zhao, Y., Zhao, H., & Guo, S. (2022). Evaluating the comprehensive performance of 5G base station: a hybrid MCDM model based on Bayesian best-worst method and DQ-GRA technique. Mathematical Problems in Engineering, 2022, 1-15. https://doi.org/10.1155/2022/4038369
13. [13] Mohammadi, Majid, and Jafar Rezaei. "Bayesian best-worst method: A probabilistic group decision making model." Omega 96 (2020): 102075.
14. [14] Mustafa, I. S., Din, N. M., Ismail, A., Omar, R. C., & Khalid, N. H. N. (2015). Site suitability analysis for landslide monitoring base station using GIS-based multicriteria evaluation technique. In 2015 5th National Symposium on Information Technology: Towards New Smart World (NSITNSW) (pp. 1-6). IEEE. Doi: 10.1109/Nsıtnsw.2015.7176414
15. [15] Ozcanli, M. (2015). The impact of spatial development of Sanliurfa city on the surrounding agricultural lands. Journal of Turkish Studies, 10(6). Doi: 10.7827/turkishstudies.7890
16. [16] Saaty, T. L., & Vargas, L. G. (2012). Models, methods, concepts & applications of the analytic hierarchy process (Vol. 175). Springer Science & Business Media. https://doi.org/10.1007/978-1-4614-3597-6
17. [17] Saaty, T. L., Ozdemir, M. S., & Shang, J. S. (2015). The rationality of punishment—measuring the severity of crimes: An AHP-based orders-of-magnitude approach. International Journal of Information Technology & Decision Making, 14(01), 5-16. https://doi.org/10.1142/S0219622014500850
18. [18] Tayal, S., Garg, P. K., & Vijay, S. (2020). Optimization models for selecting base station sites for cellular network planning. In Applications of Geomatics in Civil Engineering: Select Proceedings of ICGCE 2018 (pp. 637-647). Springer Singapore. Doi:10.1007/978-981-13-7067-0_52
19. [19] Tohma, K., Aydin, M. N., & Turgut, I. A. (2015). Improving the LEACH protocol on wireless sensor network. In 2015 23nd Signal Processing and Communications Applications Conference (SIU) (pp. 240-243). IEEE. Doi: 10.1109/SIU.2015.7129804