چکیده:
خسارات بسیار جانی و مالی ناشی از سوانح طبیعی در کلان‌شهرها ضرورت ارزیابی و ارتقای تاب‌آوری پیش از وقوع حادثه را نشان می‌دهد. کلانشهر تهران که مستعد زمین‌لرزه است، نیز از این امر مستثنا نیست. لذا در مقاله حاضر، مجموعه‌ای از شاخص‌های تاب‌آوری از سه مدل ۱BRIC، ۲CRI و ۳CDRI، شناسایی‌شده و جهت ارائه شاخص ترکیبی چندبعدی تاب‌آوری کلانشهر تهران مورداستفاده قرارگرفته است. بامطالعه ۳۶۸ محله تهران و با استفاده از روش تحلیل عاملی اکتشافی، ابعاد تاب‌آوری در پنج بعد اجتماعی، بعد زیرساختی، بعد عملکرد اقتصادی، بعد جامعه‌ای–روابط همسایگی و بعد جامعه‌ای-مشارکت- تعریف‌شده‌اند. توزیع فضایی تاب‌آوری و ابعاد آن در سطح کلانشهر تهران نشان می‌دهد که محلات غربی و جنوبی شهر تهران و برخی از محلات در شمال شرقی وضعیت نامطلوبی ازنظر تاب‌آوری دارند. درصورتی‌که میزان تاب‌آوری در محلات مرکزی و شرقی به نسبت بیشتر است. در میان ابعاد تاب‌آوری نیز بعد زیرساختی بیشترین تأثیر منفی را بر محلات با وضعیت نامطلوب تاب‌آوری داشته است.
چکیده انگلیسی:
Different models of disaster resilience have been conducted to evaluate or promote resilience of cities prone to disasters. By considering resilience as a set of adaptive capacities, pre-event capacities influence resilience. Therefor providing a methodology and a set of indicators to measure the present conditions influencing disaster resilience within communities is the focal argument in assessment of resilience to natural hazards. As the resilience has different dimensions, one of the quantitative approaches to measure city disaster resilience is to construct a composite index. The composite index, which encompasses a set of resilience indicators, can help in resilience quantitative evaluation, comparison between geographic units in terms of resilience, and elucidate resilience spatial distribution or assess resilience in a specific place in different periods of time. Tehran Metropolis, the capital of Iran, is located at the southern foot of Alborz Mountains, and surrounded by several fault lines. High vulnerability to disasters of Tehran Metropolis as well as the increasing population and the accumulation of resources in the capital highlight the importance of assessing the disaster resilience of this city in order to take appropriate measures to compensate for the shortcomings before the natural events occur. Based on the context represented here, the main objective of this study is to construct a composite indicator for evaluating inherent community disaster resilience for Tehran metropolis. In this regard, a set of resilient indicators extracted from three evaluation models -Baseline Resilience Indicators for Communities (BRIC), Community Resilience Index (CRI) and Community Disaster Resilience Index (CDRI) -were used to evaluate and construct a resilient composite index for Tehran metropolis. Taking into consideration indicators’ feasibility, operation-ability as well as data-accessibility, 34 of the 143 identified indicators from the three models were selected at the neighborhood level (for the 368 neighborhoods of the City). By using exploratory factor analysis, the inherent resilience dimensions are shown in five social, infrastructure, economic performance, community-neighborhood relations and community-participatory domains. The Kaiser–Meyer–Olkin (KMO) measure was 0.785, indicating that the correlation between the data is suitable for factor analysis and the cumulative variance of 5 factors explain 71.687 percent of the data variance. The spatial distribution of composite disaster resilience and its dimensions in Tehran metropolis indicate that the western and southwestern neighborhoods of the city have the least inherent resilience. The northern and central neighborhoods are in a better position than the southern neighborhoods in terms of resilience. Among the resilience dimensions, the infrastructure dimension has had the most negative impact on the neighborhoods with an adverse resilience situation. To conclude, the quantitative disaster resilience evaluation provides a clear picture of the status quo. Therefore, by assessing resilience in different geographic units, it is possible to compare and identify differences between areas, reduce shortcomings, and take advantage of opportunities. Besides, by measuring the resilience in different periods of time, one can understand any increase or decrease in resilience of a place and improve this quality before the events, especially in cities with high population density and prone to earthquakes like Tehran.
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