Quantitative Spectrum of the Urban Vulnerability against Earthquake (Case Study: Yazd City)

Document Type : Research article

Authors

1 MA in Architecture, Faculty of Architecture and Urban Planning, Jundi-Shapur University of Technology, Dezful, Iran

2 Assistant Professor of Architecture, Faculty of Architecture and Urban Planning, Jundi-Shapur University of Technology, Dezful, Iran

3 Master Student of Architecture, Isfahan University of Art, Isfahan, Iran

4 Associate Professor of Architecture, Faculty of Architecture and Urban Planning, Jundi-Shapur University of Technology, Dezful, Iran

5 Professor of Geography, Shahid Chamran University of Ahvaz, Iran

Abstract

Introduction
In recent decades, urban planners have undergone dramatic changes in their fields of expertise through the advent of technology and urban globalization. One of the issues that urban planners consider in this area is urban health, as one of the most fundamental preconditions of the global community for human-centered planning. In this research, the earthquake is an example of a daily practical experience of the urban crisis. The purpose of the research is to increase the variable to reduce the damage to the urban crisis.
Therefore, because of the need for further information to reduce the crisis, it involves uncertainty in the occurrence of many unforeseen events. Therefore, as much as the degree of uncertainty increases, the complexity of the goals increases. Consequently, our perceptions continue to increase the complexity of knowledge and insights. In this research, the most important problem is to reduce the error factor for crisis management using a modeling method. The second issue is to control the complexity of issues that has been examined by the COPRAS method.
One of the topics of interest to urban planners is "safety planning" issues in cities. This is one of the most basic assumptions of the international community for human-centered planning. Reducing vulnerability to natural hazards in critical areas has become a principal issue in crisis management.
Methodology
This present study is a developed-applied approach with combined research methods including library, field, descriptive, and analytical techniques. It should be noted that this research has been done to simulate the Bootstarp pattern in two software VPLS and AMOS-SPSS. The SmartPlS software has also been used to model structural equations in social-physical elements. The COPRAS statistics were used to measure vulnerability (VI). It should be noted that GRAFER, EQS, EXCEL and ArcGIS software have been used to complete the analysis of the findings.
In this research, the Bootstrap sample was initially used by bootstrap statistical references with the software EQS and PLS 1000. The frequency) of repetition has been calculated using the method. It is worth mentioning 26 variables with B repeat times, separated by all three urban areas of Yazd.
Results and discussion
Based on the explanation and efficiency of the bootstrap simulation model, the results show that using the simulation of the given data, the possibility of determining the vulnerability in both (social and physical) indicators reduces the error. An expression increases the confidence coefficient. One of the benefits of Bootstrap simulation is a good way to control the stability of the results. In the study, the data weights in relation to the regions obtained a higher reliability coefficient using simulations. Thus, the area of Yazd city using the BootStrap has a confidence coefficient of 0.95.
Table 1. Factors and their weight




Factor Loading, Residual and Weights




Construct


Mean


Stdev


Residual


Weight




R1


7493.770385


27219.511234


0.000000


1.000000




R2


11116.646154


31694.163768


0.000000


1.000000




R3


12325.575769


37154.044446


0.000000


1.000000




W


0.027917


0.044263


0.000000


1.000000




Source: Writer; R: Yazd urban area; W: weight.
 
 
Fig. 1. Structural Equation Grid and BootStrap Simulation
In the complex of structural variables and their facade, the least dispersion, the index is not spaced apart in this set. The structure shows the variables of buildings with the symbol of brick and stone.
In the complex of structural variables in terms of physical-physical damage, calculations show that the variables of buildings with an area of less than 100 to 200 square meters have no distribution and dispersion. In average, they indicate the vulnerability of this index in Yazd. The variables combine gender and literacy social vulnerability of the complex variables.
Conclusion
The results show that the vulnerability of building physical variables with an area of 100 to 200 square meters does not have any distribution and dispersion. They show the vulnerability of mean index in the Yazd. The variables of living in social vulnerability represent the lowest coefficient of dispersion and habitat variables in the group. The results weighted in relation to the areas with the use of simulators have gained more confidence.  

Keywords


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