Assessment and mapping of the seismic vulnerability of Tabriz city using the Fuzzy logic

Document Type : Original Article


Department of Earth Sciences, Faculty of Natural Sciences, University of Tabriz, Iran



The present study aimed to investigate and zonate Tabriz city, Iran in terms of vulnerability to earthquake hazard using the GIS software. Due to the geographical location of Tabriz over the North Tabriz Fault as an active and seismic fault from the north of the city, the necessity of this issue is highlighted. Based on the 10 most important influential factors in the vulnerability of cities to earthquake (geological and environmental factors), the seismic vulnerability zoning maps were developed by the ARC GIS software using the Fuzzy logic. By the integration of the layers using the Fuzzy method, the final map of the vulnerability of Tabriz city in equilibrium earthquakes was prepared in five zones with very high, high, moderate, low, and very low vulnerability. According to the zoning maps, Tabriz is not well positioned in terms of the occurrence of earthquakes, and most of the populated areas (especially the northern and central parts of the city) have higher vulnerability.


1. Yariyan P, Avand M, Soltani F, Ghorbanzadeh O, Blaschke T. Earthquake vulnerability mapping using different hybrid models. Symmetry 2020; 12(3): 405.
2. Jena R, Pradhan B, Beydoun G. Earthquake vulnerability assessment in Northern Sumatra province by using a multi-criteria decision-making model. Int J Disaster Risk Reduct 2020; 46: 101518.
3. Yariyan P, Zabihi H, Wolf ID, Karami M, Amiriyan S. Earthquake risk assessment using an integrated Fuzzy Analytic Hierarchy Process with Artificial Neural Networks based on GIS: A case study of Sanandaj in Iran. Int J Disaster Risk Reduct 2020; 50: 101705.
4. ┼×en Z. Supervised fuzzy logic modeling for building earthquake hazard assessment. Expert Syst Appl 2011; 38(12): 14564-73.
5. Nowruzi AA, Adeli H, Mohajer Ashjaee A. Seismicity coefficients and areas of relative intensity of earthquakes in Iran. J College Engineering 1981; 42(0): 93-105. [In Persian]
6. Faraji A, Qarakhlo M. Earthquake and Urban Crisis Management (Case Study: Babol). Geography (Scientific Research Quarterly of the Iranian Geographical Society) 2011; 8(25): 143-64. [In Persian]
7. Roostaiee SH. Zoning the risk of Tabriz fault for different usages of urban lands with GIS. Geogr Dev 2011; 9(21): 27-41.
8. Asadi Y, Samany NN, Ezimand K. Seismic vulnerability assessment of urban buildings and traffic networks using fuzzy ordered weighted average. J Mt Sci 2019; 16(3): 677-88.
9. Guo X, Kapucu N. Assessing social vulnerability to earthquake disaster using rough analytic hierarchy process method: A case study of Hanzhong City, China. Saf Sci 2020; 125: 104625.
10. Gök R, Sandvol E, Türkelli N, Seber D, Barazangi M. Sn attenuation in the Anatolian and Iranian plateau and surrounding regions. Geophys Res Lett 2003; 30(24): 8042.
11. Berberian M. Active faulting and tectonics of Iran. Zagros Hindu Kush Himalaya Geodynamic Evolution. Washington, D.C.: American Geophysical Union; Boulder, Colo.: Geological Society of America, 1981.
12. Allen MB, Saville C, Blanc EP, Talebian M, Nissen E. Orogenic plateau growth: Expansion of the Turkish-Iranian Plateau across the Zagros fold-and-thrust belt. Tectonics 2013; 32(2):171-90.
13. Badri SA, Asgary A, Eftekhari AR, Levy J. Post-disaster resettlement, development and change: a case study of the 1990 Manjil earthquake in Iran. Disasters 2006; 30(4): 451-68.
14. Einali J, Mohamady Yeganeh B, Cheraghi M, Feyzolahpour M. Evaluating the effects of reconstruction of the damaged villages in the 2002 earthquake in Avaj, Iran. Int J Disast Risk Re 2020; 43: 101373.
15. Hosseini KA, Izadkhah YO. From “Earthquake and safety” school drills to “safe school-resilient communities”: A continuous attempt for promoting community-based disaster risk management in Iran. Int J Disast Risk Re 2020; 45: 101512.
16. Delavar MR, Sadrykia M. Assessment of enhanced Dempster-Shafer theory for uncertainty modeling in a GIS-based seismic vulnerability assessment model, case study—Tabriz city. ISPRS Int J Geo-Inf 2020; 9(4): 195.
17. Zadeh LA. Fuzzy logic—a personal perspective. Fuzzy Sets Syst 2015; 281: 4-20.
18. Bathrellos GD, Skilodimou HD, Chousianitis K, Youssef AM, Pradhan B. Suitability estimation for urban development using multi-hazard assessment map. Sci Total Environ 2017; 575: 119-34.
19. Martins VN, e Silva DS, Cabral P. Social vulnerability assessment to seismic risk using multicriteria analysis: the case study of Vila Franca do Campo (São Miguel Island, Azores, Portugal). Nat Hazards 2012; 62(2): 385-404.
20. Aghataher R, Delavar MR, Nami MH, Samnay N. A fuzzy-AHP decision support system for evaluation of cities vulnerability against earthquakes. World Appl Sci J 2008; 3(1): 66-72.
21. Jena R, Pradhan B, Beydoun G, Nizamuddin, Ardiansyah, Sofyan H, et al. Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia. Geosci Front 2020; 11(2): 613-34.
22. Alizadeh M, Alizadeh E, Asadollahpour Kotenaee S, Shahabi H, Beiranvand Pour A, Panahi M, et al. Social vulnerability assessment using artificial neural network (ANN) model for earthquake hazard in Tabriz city, Iran. Sustainability 2018; 10(10): 3376.
23. Hu J, Chen J, Chen Z, Cao J, Wang Q, Zhao L, et al. Risk assessment of seismic hazards in hydraulic fracturing areas based on fuzzy comprehensive evaluation and AHP method (FAHP): A case analysis of Shangluo area in Yibin City, Sichuan Province, China. J Petrol Sci Eng 2018; 170: 797-812.
24. Alizadeh M, Hashim M, Alizadeh E, Shahabi H, Karami MR, Beiranvand Pour A, et al. Multi-criteria decision making (MCDM) model for seismic vulnerability assessment (SVA) of urban residential buildings. ISPRS Int J Geo-Inf 2018; 7(11): 444.