ARTICLE INFO

Article Type

Original Research

Authors

Khayambashi   E. (1)
Taghvaei   M. (*1)
Varesi   H. (1)






(1) Department of Geography and Urban Planning, Faculty of Geographical Sciences and Planning, University of Isfahan, Isfahan, Iran

Correspondence

Address: Department of Geography and Urban Planning, Faculty of Geographical Sciences And Planning, University of Isfahan, University Boulevard, Azadi Square, Isfahan, Iran Postal Code: 8174673441
Phone: +98 (31) 37933087
Fax: -
m.taghvaei@geo.ui.ac.ir

Article History

Received:  October  23, 2019
Accepted:  March 17, 2020
ePublished:  March 18, 2021

BRIEF TEXT


The salient feature of the resilient city theory is its comprehensive attitude toward all elements of survival besides the crisis incidence and control factors especially human factors with a futuristic approach that uses mathematical modeling to evaluate how different factors are related to and influenced by the monitoring of foresight process of resilience.

The prevailing attitude of vulnerability reduction in crisis management has gradually shifted to the increase of resilience to encounter the disasters since the 1980s [Turner, 2010]. Rajab Shaw (2009) analyzed the main indices in institutional and organizational, physical, economic and social dimensions in 9 Asian cities to evaluate the resilience to climate disasters. He presented the resilience of each city according to the "balanced future of indicators" in each resilience dimension [Shaw & IEDM Team, 2009]. Abbasi et al in an article (Analysis of the drivers explaining the resilience of the city in the metropolis of Mashhad" detected six main resilience drivers which were the most significant in the resilience of Mashhad [Abbasi et al, 2019]. According to the previous research of the author, the current situation of the city should be estimated in the first step and then the realistic and most desirable goals of the city resilience should be prepared [Khayambashi & Zarabi, 2018].

This study aimed to evaluate the current resilience, detect the main factors and determine the influence of each one in the improvement of Isfahan metropolitan resilience using modeling.

This is a descriptive-analytical study that is basic and applied in terms of the purpose.

This research is carried out in Isfahan metropolitan and the initial questionnaire of Delphi was consulted with a group of elites from the University and Isfahan managerial organizations including municipality, water and sewage Company, telecommunication organization, electricity and gas companies, Police, crisis management organization, treatment and medical science organization and local government.

50 elites from Isfahan were chosen for this research.

The interview with the chosen elites using the Delphi method was used to make the dimensions and indicators of the research more accurate so as to evaluate the resilience. Data were analyzed using SPSS software and R programming. Eventually, the results were presented in the form of a predictive Multivariate Regression Model.

Linear multivariate regression is a common method in multivariate analysis in which a linear model's parameters are estimated using an objective function and the amount of the variables. In this research, the dependent variable is "the resilience of Isfahan" in the estimation of the resilience of the whole city and "the resilience in each dimension" in the evaluation of each dimension. Hence, resilience indicators in each dimension are" independent or descriptive variables". Accordingly, "the resilience in each dimension" is a descriptive variable for the response variable i.e. "the resilience of Isfahan". While evaluating the current situation in the EDRI framework, the model resulted from multivariate regression can estimate the trend of future events by changing the descriptive variables, cost/opportunities and resources to improve the city resilience more efficiently. The assumption of the normality of the remaining of each model is an important assumption which should be evaluated before modeling. Kolmogrov-Smirnov and Shapiro-Wilk tests were used for this purpose. While checking the normality of data, the distribution of data is assumed to be normal and the error level is 0.05 according to the null hypothesis. According to table 3, the distribution of both dimensions and parameters chosen for Isfahan resilience are normal.In tables 4 to 7 that are called "regression coefficient table" in senary dimensions of resilience. The coefficients of each predictive variable in the linear model in two situations with and without intercept are extracted from the amount of (B) and (Beta), respectively. Each independent variable and each constant will be in the final model on the condition that its significance level (P) is less than the defined error level (0.05). According to the information in table 4, the regression model in the social dimension with the written intercept is the most suitable one (Equation1): D1=0.596+0.282D_(1-1)+0.512D_(1-2) According to the results of regression coefficients table 4, the model written with intercept is the most suitable model prepared in equation 2: D2=1.015+0.601 Considering the significance level (P) in table 5, the null hypothesis of the first, second and third indices in the physical dimension of the predictive resilience model is not rejected in α=0.05. Then, the step-by-step regression approach was used to find a suitable regression model. Accordingly, the most suitable model is presented below:Equation3) D3=1.009+0.306D_(3-1)+0.356D_(3-4) Two main indices of the resilience regression model in environmental dimension are evaluated according to the environmental, geological and climatic features and the geographical location, potential threats and the history of the previous disasters. Considering the results of table 5, the most suitable model with the intercept is like equation 4: D4=0.916+0.52D_(4-1)+0.166D_(4-2) According to the information of economic dimension in regression coefficients of resilience model table (table 6), the null hypothesis for the first, second, fifth and sixth indices is not rejected. The most suitable model using step-by-step regression is presented as below:Equation 5) D5=0.994+0.408 D_(5_3 )+0.195 D_(5_4 )+0.137D_(5_5 ) The regression model of resilience in the institutional-legal dimension evaluates different managerial, legal and governmental aspects of Isfahan resilience using three main indices including some relevant sub-indices. According to the given information in table 7, the model with intercept is the most suitable one which is presented in Equation 6: Equation 6) D6=0.924+0.147D_(6-1)+0.301D_(6-2)+0.227D_(6-3) After the extraction of the resilience model for each dimension, the last step is to prepare "the general predictive resilience model in Isfahan metropolitan". Statistical methods of "multi-model" were used for this purpose. The resilience relationship with its dimensions fits their correlation. Then, according to the multi model mathematical rules, the following logic is approved: the influence of each dimension of resilience can be calculated by multiplying the relational portion of resilience dimensions (R_adj^2 ) in a constant coefficient (α) so as to be able to form multi models. Hence in a general situation, the model will be like this: Resilience(tot)=∝+0.732aD_1+0.674aD_2+0.643aD_3+0.625aD_4+0.738aD_5+0.852aD_6 In the perfect situation, the following equation is true: Equation 8) 0.732a+0.674a+0.643a+0.625a+0.738a+0.852a=1 0.732a+0.674a+0.643a+0.625a+0.738a+0.852a=1 (4.264)a=1 a=0.235 Final regression multi-model of resilience dimensions can be calculated by putting the amount of calculated α in the initial formula: Equation 9) Resilience(tot)=0.172D_1+0.158D_2+0.151D_3+0.147D_4+0.173D_5+0.200D_6 In this model, institutional dimension weighing 0.200 is the most influential dimension and natural environment weighting 0.147 is the least influential dimension in the resilience of Isfahan metropolitan.

Rezaei's research (Explanatory of resilience urban community for Decrease of Natural Disasters Effects (Earthquake)) in Tehran and Farzad Behtash in his Ph.D. thesis in Tabriz approved the importance of dimensions and indices in the analysis of resilience in Isfahan. On the other hand, these studies confirmed the undesirable (but near the medium) resilience of the main metropolises in Iran. They, moreover approved all mentioned cities are far better in cultural and social dimensions of resilience [Rezaei et al, 2013; Farzad Behtash et al, 2013]. Hatami Nejad et al (2017) evaluated influential dimensions in resilience using the Interpretive Structural Modeling technique (ISM) according to 15 elite's opinion in urban management sectors and Ahvaz municipal managers. Economic, physical, institutional-managerial, infrastructural, social and environmental dimensions are respectively the most to the least important dimensions which are almost similar to the results of the current research [Hatami Nejad et al, 2017].

There is no suggestion reported.

There is no suggestion reported.

The results of the innovative EDRI model which is derived from Rajab Shaw model in climate disasters are used in this research and show the current resilience situation of Isfahan with six dimensions. Besides, the predictive "Regression Resilience Model" elaborates the importance of each dimension and its indices in the improvement of the resilience and makes the planning more efficient. The results effectively answer the main research question about the influential factors in the risk of disasters in Isfahan. Six main dimensions and their indices are directly influential in current situation of the resilience and its improvement which approves the first research hypothesis. Although the highest resilience belongs to the cultural dimension, with 3.08, the most influential resilience dimension is the institutional-legal dimension (with the coefficient 2.00), then, the second hypothesis is rejected. The economic dimension is the weakest dimension in Isfahan's resilience which approves the third hypothesis. Finally, the medium resilience of Isfahan hypothesis, with 2.87 in EDRI, is almost approved.

The authors appreciate the cooperation of the Delphi team elite in this research.

None.

None.

This paper is extracted from a Ph.D. thesis "the analysis of resilient city indicators for strategic planning of seismic risk management. Case study: Isfahan metropolitan".

TABLES and CHARTS

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