Assessment of Urban Resilience against Natural Hazards with an Emphasis on Earthquake and Using Fuzzy Logic and GIS (A Case Study of Urmia City)

Document Type : مقاله پژوهشی


1 Bozorgmehr University of Qaenat

2 University of Tabriz

3 tabriz


Nowadays, metropolitan cities in various parts of the world are exposed to natural hazards for various reasons. These hazards are very deathful and have many financial implications, and need preventive and immediate action (Sasanpour & Mostafavand, 2010). Earthquakes are one of the major disasters that can cause physical, economic and social damage around the world (Delavar, Sardarikya, & Zare, 2017). Over the last century, more than 1,000 devastating earthquakes have occurred in several countries around the world and killed millions of people and left huge economic losses and the important thing is that the earthquake death rate is very high in urban areas (Paknejhad, Inanlo, Ardakani, & Ebrahimi 2013). Given that cities are more vulnerable to disasters because of high population density, buildings and infrastructure, the significance of seismic vulnerability assessment in urban areas is greater (Montoya, 2005). A simple framework for assessing the risk of earthquakes is calculating the seismic hazard for the places and linking them to the vulnerability of buildings, infrastructure, communities and facilities at risk (Banica, Rosu, L., Muntele, L., & Grozavu 2017). The physical and structural assessment of the city in terms of resilience to the hazards and especially to the earthquake is extremely important and today in various scientific studies, urban vulnerability to hazards has become a fundamental concept. Accordingly, in this study, the physical resilience of Urmia city against earthquake hazard has been investigated.

Materials and Methods

This research is an applied one and documentary and library methods of data collection are used. This research has been carried out using ArcGIS software based on location-based data using fuzzy logic. The fuzzy logic theory focuses on the presentation and management of ambiguous information. A fuzzy set is essentially a set that has members with membership degrees between 0 and 1. For this purpose, 10 criteria including population density, construction density, number of building floors, urban land use, distance from faults, urban roads network, electricity, highway network, access to open spaces, access to health centers, and access to relief centers have been selected as research criteria. Having applyed some fuzzy functions such as Linear, Large and Small, these maps are standardized. Finally, weighted maps are integrated together using Fuzzy Gamma 0.9 operator.

Results and Discussion

In this study, we first mapped the criteria of the survey using different functions of the GIS, and then, in order to standardize these maps, fuzzy functions were applied based on the nature of the layers, the final map has been achieved through overlaying the layers. According to this map, it is known that a large part of the city is in the high-risk areas and it can be said that these areas have less resilience to earthquake hazard. Accurately, 37.8 percent of the total area of ​​the city with a total area of ​​31.5 square kilometers is among high-risk areas. Accordingly, 65% of district 4 with a historical texture and high population is exposed to high risk and districts 2, 3 and 1 with 42, 31 and 30 percent are more resilient against earthquake hazard.


Urban resilience is a complex concept in modern cities that have the ability to change with new situations, crises, and challenges. This concept has various economic, socio-cultural, environmental, and infrastructural dimensions and it has always overwhelmed the current and future levels of urban people in various ways. unsuitable position of the city skeleton such as inefficient street network, inadequate distribution of open spaces, high urban density, incompatibility of  land use and worn-out buildings,  are effective in increase of the vulnerability, and increase  improvement time of the city. The results of the present research indicate that about 38% of the urban area has a moderate to low resilience, and therefore, they can be called high-risk areas.
Regarding urban areas, Zone 4 has the lowest resilience (35%) and Zone 1 with 70% has the highest resilience with regard to ​​earthquake risk. Based on the results, it can be said that improving the level of resilience in the studied area is one of the basic needs of urban management.


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