Seismic zoning of urban areas considering the effect of physical conditions using Fuzzy logic theory: case study of Tehran’s 7th region

Document Type : Original Article


1 PhD Student, Faculty of Environment and Energy, Science and Research Branch, Islamic Azad University, Tehran, Iran

2 Professor, Department of Civil Engineering, Iran University of Science & Technology, Tehran, Iran

3 Associate Professor, School of National Surveying Organization, Tehran, Iran

4 Assistant Professor, Civil Engineering, Water and Environment, Shahid Beheshti University, Tehran, Iran

5 School of Civil Engineering, Iran University of Science and Technology, Tehran, Iran


One of the most important steps in designing seismic rehabilitation programs for urban areas in metropolises is determining the region’s risk level. There is no doubt of cast that the implementation of a seamless seismic rehabilitation program can secure urban areas against seismic damages. However, these plans face some difficulties in most cases. For instance, their execution costs are very high, or, they are really time-consuming in some cases. It is obvious that a coherent rehabilitation strategy will be effective if it can distinguish executive priorities by identifying areas with high level of risk, and focusing primarily on improving the general condition of these areas. In this paper, the seismic vulnerability of the 7th region of Tehran is studied. For this purpose, the main parameters that affect the vulnerability of the region are identified first. Then, considering the uncertainties in these parameters, their impact on the vulnerability of the region is determined. ArcGIS software is used not only to model the impact of these parameters, but also for data training. The results of this study show the vulnerability level of different parts of Tehran's 7th region. In fact, this study provides a comprehensive and meaningful overview of the current status of the studied region, which can helps the engineers to design suitable seismic rehabilitation programs. The obtained results are presented as a map which reveals the vulnerability level of the region. Based on such a map, neighborhoods or areas with high seismic hazard are identified. Considering these classification, the seismic rehabilitation techniques can be offered purposefully.


[1] Zangiabadei, A., Mohamadei, G., Safaei, H., Gaedrahmati, S. (2008). Vulnerability indicators assessment of urban housing against the earthquake hazard; case study: Isfahan housing. Geography and Development Iranian Journal, 6 (12), 61-79. (in Persian)
[2] Jaika (2001). Final Report of Greater Tehran Seismic Sub-Zoning Project. (in Persian)
[3] Khakpour, B.A., Zomorrodian, M., Sadeghi, S., Moghaddami, A. (2011). The analysis of physical–structural vulnerability of the Ninth District of Mashhad from a seismological perspective. Journal of Geography and Regional Development, 9 (16), 1-34. (in Persian)
[4] Silavi, T., Delavar, M., Malek, M., Kamalian, N. (2005). Seismic vulnerability mapping using multi-criteria decision-making methods based on interval mathematics and spatial information systems. In: 1st International Conference on Integrated Natural Disaster Management. Tehran, Iran. (in Persian)
[5] Habibi, K., Pourahmad, A., Meshkini, A., Askari, A., Nazari Adli, S. (2008). Determining the structural/building factors affecting the vulnerability of the old structures of the city of Zanjan using Fuzzy Logic & GIS. Honar-Ha-Ye-Ziba, 10, 27-33. (in Persian)
[6] Ghodrati Amiri, G., Asmari Saad Abad, S., Zare Hosseinzadeh, A. (2013). Earthquake risk assessment using fuzzy inference systems and its application in seismic rehabilitation studies. Modares Civil Engineering Journal, 13 (3), 71-84. (in Persian)
[7] Vojoudi, M., Zare, M. (2006). Fuzzy inference model for seismic hazard analysis. In: 2nd International Conference on Integrated Natural Disaster Management, Tehran, Iran. (in Persian)
[8] Pourahmad, A., Habibi, K., Zahraei, S., Nazari Adli, S. (2007). Utilizing Fuzzy algorithm and GIS to locate the urban equipment. Journal of Environmental Studies, 33 (42), 31-42. (in Persian)
[9] Sadrykia, M., Delavar, M.R., Zare, M. (2017). A GIS-based Fuzzy decision making model for seismic vulnerability assessment in areas with incomplete data. International Journal of Geo-Information, 6, doi:10.3390/ijgi6040119.
[10] Demir, V., Kisi, O. (2016). Flood hazard mapping by using Geographic Information System and hydraulic model: Mert River, Samsun, Turkey. Advances in Meteorology, 2016, 4891015.
[11] Taramelli, A., Melelli, L., Pasqui, M., Sorichetta, A. (2008). Estimating hurricane hazards using a GIS system. Natural Hazards and Earth System Sciences, 8, 839-854.
[12] Statistical Center of Iran. (2006). The general population and housing census results.
[13] Housing and Urban Development in Tehran. (2006). The detailed design maps of District 7, Tehran.
[14] Shahrdari Region 7, Tehran. [Online] Available at:
[15] Zebardast, A. (2001). The application of analytical hierarchy process in urban and regional planning. Honar-Ha-Ye-Ziba, 10, 13-21. (in Persian).