نوع مقاله: مقاله پژوهشی
نویسندگان
1 دانشجوی دکتری جغرافیا و برنامه ریزی شهری دانشگاه تهران
2 استاد جغرافیا و برنامه ریزی شهری، دانشکده جغرافیا، دانشگاه تهران
3 دانشجوی دکتری جغرافیا و برنامه ریزی شهری، دانشگاه تربیت مدرس
4 دانشجوی دکتری جغرافیا و برنامه ریزی شهری، دانشگاه تهران
چکیده
کلیدواژه‌ها
عنوان مقاله [English]
نویسندگان [English]
Extended Abstract:
Introduction: Natural disasters have always been considered to be a great challengefor sustainable development throughout the world. Consequently, the paths to this development through the vulnerability reduction patterns are very important. Therefore, it is particularly important to reduce the risks of these disasters and necessary to consider a proper position in the national policy-making of countries in order to provide an appropriate condition for the effective reduction of the risks in different levels. Most of the plans made in the field of earthquake management are limited to the time interval during and after the occurrence of the crisis and less attention is paid to the pre-disaster planning. Among the plans for the risk reduction, resilience can be considered a more accurate and successful plan due to its consideration of social, institutional, economic, and physical aspects of a city. In fact,it aims to reduce the vulnerability of the communities and prepare people to face the risks caused by natural disasters. The management of natural disasters requires understanding their nature, accurate assessments, planning and finally providing proper strategies. Hence, it is very important to explain the relationship between resilience in natural disasters (such as earthquake) and reducetheir impact given the results that it might have and the emphasis of this analysis on the aspect of resilience.
Materials & Methods:The present study is an applied study in terms of purpose and is adescriptive survey type in terms of research method. Documentary method based on library studies and survey approach with a questionnaire tool was used to collect the research data. The assessment criteria for the resilience of urban communities were first determined in the present study. Then, a questionnaire was designed and distributed among the residents of Nourabad and Maskan-e Mehr in order to prepare the initial matrix for these criteria. The study population consists of the residents of Nourabad and Maskan-e Mehr of this city. Cochran's formula was used to estimate the sample size. According to the initial results of the census conducted in 2016, the population of Nourabad, including the residents of Maskan-e Mehr, was 66417. Therefore,given this population, the sample size was obtained to be 384 for the city of Nourabad using Cochran’s formula and the sample size for Maskan-e Mehr was obtained to be 500 households with household dimension of 5.5, given the number of households settled in Maskan-e Mehr until the end of 2017. The sample size was estimated to be 340 people for Maskan-e Mehr using Morgan’s table,. The scoring basis of the criteria was based on Likert 5-point scale with1 representing very low, 2 low, 3 medium, 4 high, and 5 very high. Finally, the average point of this questionnaire was considered as the initial matrix for VIKOR model. In the proposed method, the final weight of the criteria was determined based on AHP pair-wise comparison matrix. Finally, the criteria were ranked based on VIKOR technique procedure. In general, the findings of the current research were analyzed through hierarchy analysis and integration of the indices using VIKOR technique.
Results & Discussion:In the first step, the raw data of each criterion associated with the resilience of Nourabad County and Maskan-e Mehr, which were extracted from the questionnaire, were used and the decision-making matrix was created. In the second step, Equation (1) was used to obtain the weight normalization matrix for Nourabad and Maskan-e Mehr. In the third step, AHP method was used for the weighting of the normalized matrix and determining the weight of the indices. The weights of the proposed indices were determined by the residents of Nourabad County and Maskan-e Mehr and were calculated using the AHP method in Excel 2013 software and were assigned to each index. After determining the weight of the criteria, the values of the normalized matrix for each option was multiplied by the weight of the criteria and consequently, the weighted normalized matrix was obtained. In order to determine the best and worst values for the criteria, equations (2) and (3) i.e. determining the positive and negative ideal points were used. Equations (4) and (5) were used to calculate the distance of the options from the ideal solution. Finally, VIKOR index (Qi) was used to rate the resilience of Nourabad County and Maskan-e Mehr based on the distance from the ideal solution. Generally, the views of the residents of Nourabad and Maskan-e Mehr were combined through VIKOR method to determine the value and importance of the criteria and the final weights of the criteria were determined using the AHP method. Applying the obtained weight on the initial values of the criteria and combining the weight indices, Nourabad County and Maskan-e Mehr were prioritized in terms of resilience.
Conclusion:The results obtained from VIKOR technique showed that this method, as one of the multi-criteria decision-making method, has capabilities including multi-attribute utility theory or non-ranking methods. On this basis and after calculating the weights through hierarchy analysis process and using VIKOR technique, the difference in the resilience of Nourabad County and Nourabad Maskan-e Mehr was determined. Based on the calculations and the associated indices, Nourabad County has the highest resilience level with S=0.763, R=0.49, and Q=0.966, whilethe Maskan-e Mehr of this city has the lowest resilience with indices S=0.666, R=0.272, and Q=0.626. Given the Q index, Nourabad County (pre-created communities) has a more favorable condition in terms of resilience against natural disasters (earthquakes) compared to the Maskan-e Mehr of this city (planned communities) in social, institutional, economic, and physical aspects.
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