Towards Urban Resilience: A Multi-Criteria Analysis of Seismic Vulnerability in Iasi City (Romania)

Abstract

When relating to hazards such as earthquakes, a primary task of a resilience approach is to evaluate vulnerability in an integrative manner by taking into account the most relevant indicators. Focused on Iasi, one of the major Romanian cities which are exposed to the earthquakes originating in Vrancea area, this study aims to assess seismic vulnerability using a multi-criteria analysis of buildings infrastructure and social vulnerability. Several indicators are taken into account, such as physical (related to the characteristics of buildings and terrain) and social indicators (related to population and economic income), as well as the accessibility from/to emergency services/hospitals. The indicators were processed by standardization (Z score), processed and correlated using the principal components analysis (PCA) and integrated within an Analytical Hierarchy Process (AHP). By summing the weighted values of the standardized indicators, a (integrated) seismic vulnerability index was obtained. It is a pre-assessment of the seismic vulnerability in Iasi City and also a prerequisite for the identification of the necessary prevention measures to be taken in compliance with the identified spatial patterns of vulnerability as a part of a resilient approach.

Earthquake Vulnerability Mapping Using Different Hybrid Models

“…Many studies have also used only a limited number of criteria and have carried out a one-dimensional seismic vulnerability assessment, including: [17], which assessed the economic damages of highway bridges in Campania, Italy and has used statistical methods of updating ground motion prediction and fragility (their results show that the structural dependence of land movement is an important factor in the economic damage caused by earthquakes); [18], which used an expert system containing specialized knowledge for masonry structures in assessing the seismic vulnerability of old buildings in Sri Lanka; [19], which performed a seismic vulnerability assessment by focusing on one of the Romanian cities subject to earthquake, using multi-criteria analysis and a number of physical and social criteria, the results of which identified 385 earthquake-prone structures, as well as the decision-making process to reduce the damage. Other methods and models have been used to map natural hazard vulnerability in some current studies, including certainty factors (CF) [20], ANN [21,22], logistic regression (LR) [23], support vector machine (SVM) [24][25][26], convolutional neural network (CNN) [27], ordered weight averaging (OWA) [4], fuzzy quantifier algorithm [28], adaptive neuron-fuzzy inference system (ANFIS) [29,30], and different multiple criteria decision analysis (MCDA) models [31] such as the analytic hierarchy process (AHP) [32][33][34] and the analytical network process (ANP) [35,36].…”

Qualitative Assessment of Social Vulnerability to Flood Hazards in Romania

“…The only limitation of the method is that it attributes equal weights to all factors influencing social vulnerability, although there are always certain processes-depending on the analysed region-which can have a stronger impact on shaping social vulnerability. In order to avoid this limitation, most of the research results which have seen the light of day in the last years have focused either on applying different weighting methods [21,22] or on developing completely new methodologies [23,24].…”

A Contribution to a UHS-Based Seismic Risk Assessment in Croatia—A Case Study for the City of Osijek

“…The proposed algorithm for a detailed risk assessment was applied to a database and is currently in its initial stage.Sustainability 2020, 12, 1796 2 of 24 to estimate the losses. These losses can be assessed in a material form, through the damage of the building stock or non-structural elements of buildings, or in the form of casualties or injuries during the earthquake [10,11]. The last step is to analyze uncertainties, costs, decision-making criteria, etc.…”