Investigating Urban Vulnerability against Earthquakes Using GIS and BWM Model (Case Study: A Part of the Tabriz Metropolis)(Case study: a part of the Tabriz city)

Document Type : Original Article

Authors

Surveying and Geomatics Engineering Department, Faculty of Civil Engineering, Tabriz University, Tabriz, Iran

Abstract

Introduction: Earthquakes are natural hazards that often cause significant loss of life and property due to their unexpected nature. Urbanization has led to increased population density in cities, along with greater building density and more facilities, which has heightened vulnerability to earthquakes and put more lives and property at risk. While earthquakes cannot be prevented, identifying vulnerable areas can help mitigate their impact. This study assesses the earthquake vulnerability in Tabriz.
Material and Methods: The study is located in district 2 of Tabriz Metropolitan Municipality. District 2 is notable in Tabriz for its social, economic, and physical characteristics. The criteria affecting the vulnerability of the urban fabric to earthquakes were identified, and relevant information was collected to determine the level of vulnerability. These criteria include the age of the buildings, type of materials, quality of the buildings, number of floors, population density, distance from faults, roads, open spaces, and building area. The most and least important criteria were identified, and their weights were assigned using the best-worst model, a modern method for multi-criteria decision-making. This method requires fewer comparisons and yields more stable results than analytic hierarchy process (AHP), and was addressed in this study using the Simplex linear programming method. A map for each criterion was prepared in a GIS environment. The value of each parcel was calculated using the best-worst method, considering the research objective.
Discussion: The criteria weights were carefully determined by the process of prioritizing building quality as the most important factor and building area as the least important factor, thereby yielding weights with an inconsistency ratio of 0.06, which is considered acceptable and reflects a reasonable level of consistency in the decision-making process. By calculating the weight of each parcel and computing their average in each area, the safest and most vulnerable areas were determined for each criterion. Other areas were compared against these two areas across each criterion. Final values and rankings were determined by accounting for the weight of each criterion and the weight of each area within it. This study identified the best and worst areas for each criterion using spatial analysis and calculation results, unlike the conventional Best-Worst Model, which typically relies on expert opinions to define them. This method was chosen because it best suited the specific requirements of the problem. Areas 6 and 2 show the lowest and highest vulnerability to earthquakes, respectively. The high sensitivity is related to the weights assigned to the distance from open spaces and roads. Increasing these weights by 2.5×10^-5 and 3.5×10^-5, respectively, would result in a change in the current solution.
Conclusion: Earthquakes represent a natural hazard that constantly threatens our country. Assessing urban seismic vulnerability and planning can significantly reduce earthquake losses in lives and property. This study assessed the earthquake vulnerability of a section in the municipal district 2 of Tabriz. The results indicate that Area 2 is the most earthquake-vulnerable region, centrally located within the studied area. This area was the most vulnerable of the nine areas regarding build quality, age of buildings, materials used, and access to open spaces. Area 2 covers approximately 16% of the total area and comprises 1,815 parcels, most classified as high or very high-vulnerable. This study determined not only the weights of the criteria but also their allowable change. Within sensitivity analysis, determining the allowable change of these weights informs decision-makers about the flexibility of variable values.

Keywords

References

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