|
|
|
|
|
|
|
|
|
Urban Earthquake Vulnerability Assessment Using GIS and Fuzzy Modeling (Case Study: Izeh City)
|
Majid Goodarzi *  , Zahra Soltani , Aezam Ebrahimi |
| Shahid Chamran University of Ahvaz , m.goodarzi@scu.ac.ir |
|
|
Abstract: (116 Views) |
Introduction
Earthquakes are among the most destructive natural hazards, posing serious threats to urban areas due to their sudden occurrence and extensive physical, social, and economic impacts. Rapid urbanization, population growth, and unplanned spatial development have significantly increased urban exposure and vulnerability to seismic hazards. Urban vulnerability is a multidimensional concept that reflects the susceptibility of urban systems to damage, influenced by physical, spatial, and environmental factors. Among these, physical and spatial characteristics such as proximity to active faults, geological structure, slope, land use patterns, and accessibility to open spaces play a decisive role in determining the severity of earthquake impacts. Iran is located within the Alpine–Himalayan seismic belt and is characterized by numerous active faults, making many of its cities highly prone to earthquake hazards. The city of Izeh, situated in the Zagros mountainous zone and in close proximity to the Main Zagros Fault, represents one of the urban areas with considerable seismic risk. Despite this exposure, comprehensive spatial assessments of seismic vulnerability in Izeh remain limited. Recent advancements in Geographic Information Systems (GIS) and fuzzy logic modeling have provided effective tools for analyzing complex spatial phenomena and managing uncertainty in vulnerability assessment. Therefore, this study aims to evaluate and map urban seismic vulnerability in Izeh using a GIS-based fuzzy modeling approach, with the objective of identifying high-risk areas and supporting informed decision-making in urban planning and disaster risk reduction.
Method
This study adopts a descriptive–analytical approach based on spatial analysis and multi-criteria decision-making techniques. A GIS-based framework integrating fuzzy logic and the Analytic Network Process (ANP) was employed to assess urban vulnerability to earthquake hazards. Spatial data used in this research include a 30-meter resolution Shuttle Radar Topography Mission (SRTM) digital elevation model, a 1:100,000 geological map, land use data, road networks, fault lines, and open space layers. Based on a review of previous studies, expert knowledge, and regional characteristics, six key criteria influencing seismic vulnerability were selected: distance to active faults, lithology, slope, land use, distance to open spaces, and distance to main roads. All criteria were prepared as raster layers and standardized using fuzzy membership functions, assigning values between 0 and 1 to represent varying degrees of vulnerability. The relative importance of the criteria was determined using the ANP method, which accounts for interdependencies among factors. Pairwise comparison matrices were completed by experts, and the final weights were calculated using Super Decisions software. The weighted fuzzy layers were integrated using the fuzzy gamma operator to balance the effects of fuzzy AND and OR operators. After evaluating different gamma values, a gamma value of 0.7 was selected. The final vulnerability map was classified into five vulnerability levels.
Results
The results of the GIS-based fuzzy modeling indicate a heterogeneous spatial distribution of seismic vulnerability across the city of Izeh. The final vulnerability map reveals that a considerable proportion of the urban area is classified within moderate to high vulnerability levels, reflecting the combined effects of tectonic, geological, and spatial factors. Highly vulnerable zones are predominantly concentrated in areas located near the Main Zagros Fault, confirming the significant influence of tectonic proximity on urban vulnerability. The ANP weighting results further demonstrate that distance to the main fault is the most influential criterion, outweighing other factors such as slope, lithology, and land use. Although slope contributes to vulnerability in certain areas, its role is less dominant compared to fault proximity, distinguishing Izeh from mountainous rural regions such as the Oraman area, where steep slopes constitute the primary vulnerability factor. Additionally, areas with unfavorable lithological conditions and limited access to open spaces exhibit higher vulnerability levels, as these factors can exacerbate structural damage and hinder evacuation and emergency response. The results are consistent with previous national and international studies that emphasize the importance of integrating multiple spatial criteria in seismic vulnerability assessment. Overall, the findings highlight the effectiveness of combining GIS, fuzzy logic, and ANP in identifying high-risk urban zones and capturing spatial variations in vulnerability.
Conclusions
The findings of this study demonstrate that the integration of GIS-based spatial analysis, fuzzy logic, and multi-criteria decision-making provides a robust framework for assessing urban seismic vulnerability. The case study of Izeh confirms that proximity to the Main Zagros Fault is the dominant factor influencing seismic vulnerability, underscoring the critical role of tectonic conditions in earthquake risk assessment. The heterogeneous vulnerability pattern observed across the city highlights the necessity of spatially differentiated risk management strategies. These results are consistent with previous studies conducted in seismically active regions of Iran and elsewhere, while also emphasizing that dominant vulnerability factors may vary depending on local geomorphological and tectonic settings. The study underscores the importance of incorporating vulnerability maps into urban development plans, land-use regulation, and disaster preparedness strategies. By identifying high-vulnerability zones, decision-makers can prioritize mitigation measures such as enforcing seismic building codes, enhancing open spaces for emergency evacuation, and strengthening infrastructure resilience. Furthermore, the methodological framework applied in this research can be adapted to other urban areas with similar seismic conditions. Overall, the study contributes to improving earthquake risk management and enhancing urban resilience through informed, spatially explicit decision-making.
Author Contributions
All authors contributed equally to the conceptualization of the article and writing of the original and subsequent drafts.
Data Availability Statement
Data available on request from the authors.
Acknowledgements
The authors would like to thank all participants of the present study.In this section, you can acknowledge any support given which is not covered by the author contribution or funding sections. This may include administrative and technical support, or donations in kind (e.g., materials used for experiments).
The authors would like to thank all participants of the present study.
Ethical considerations
The authors avoided data fabrication, falsification, plagiarism, and misconduct.
Funding
This research did not receive financial support from any organization.
Conflict of interest
According to the authors, this article has no conflicts of interest.
|
|
| Keywords: Urban vulnerability, Earthquake, Fuzzy logic, Analytic Network Process (ANP), Izeh City. |
|
|
|
Type of Study: Research |
Subject:
سکونتگاههای شهری و روستایی
Received: 2025/11/14 | Accepted: 2026/06/10
|
|
|
|
|
|
|
| Send email to the article author |
|
|
|
| Add your comments about this article |
|
|
|
|
|
|
|
|
|
|
|
