تحلیل فضایی تاب آوری مسکن در برابر مخاطرات طبیعی با تأکید بر زلزله، مطالعه موردی: مناطق جنوبی کلان شهر تهران (مقاله علمی وزارت علوم)
درجه علمی: نشریه علمی (وزارت علوم)
آرشیو
چکیده
کلان شهر تهران به دلیل موقعیت جغرافیایی در نزدیکی گسل های فعال، تراکم جمعیت و عوامل محیطی در معرض آسیب های ناشی از زلزله قرار دارد. هدف این پژوهش، تحلیل تاب آوری مسکن در مناطق جنوبی تهران (مناطق 15، 16، 19 و 20) در برابر زلزله است. این پژوهش از نوع کاربردی و به روش توصیفی-تحلیلی انجام شده و داده ها با روش های کتابخانه ای و پیمایشی گردآوری و با استفاده از مدل بهترین-بدترین (BWM) و نرم افزارهای Excel و ArcGIS تحلیل شده اند. در ابتدا، 24 معیار کلیدی با مطالعه پیشینه تحقیق شناسایی و سپس وزن دهی و ضریب اهمیت آن ها با روش (BWM) تعیین شد. لایه های اطلاعاتی با بهره گیری از عملگر گامای فازی ترکیب شده و نقشه تاب آوری مناطق موردمطالعه تهیه شد. نتایج نشان داد که 43 درصد مناطق تاب آوری بسیار پایین و 12 درصد تاب آوری پایین دارند، درحالی که تنها 7 درصد از نظر کالبدی-محیطی تاب آوری بسیار پایین و 22 درصد تاب آوری بسیار بالا دارند. به طورکلی، 50 درصد مناطق جنوبی دارای تاب آوری بسیار پایین بوده و نیاز به مداخلات فوری دارند. نوآوری این پژوهش در تلفیق شاخص های اجتماعی-اقتصادی و کالبدی-محیطی، استفاده از روش (BWM) برای دقت در وزن دهی معیارها و بهره گیری از گامای فازی برای مدل سازی تاب آوری است. یافته ها بر اهمیت پرداختن به عوامل اجتماعی-اقتصادی در برنامه ریزی تاب آوری تأکید می کنند و پیشنهاد می کنند که یک رویکرد جامع، ترکیبی از شاخص های اجتماعی-اقتصادی و کالبدی- محیطی، برای افزایش تاب آوری مسکن در برابر زلزله در مناطق جنوبی تهران ضروری است.Spatial Analysis of Housing Resilience Against Natural Hazards with an Emphasis on Earthquakes: A case study of Southern Regions of Tehran Metropolis
The possibility of the Tehran metropolis's vulnerability due to seismic activities, location near fault lines, dense population, and various environmental factors is undeniable. Accordingly, this study investigated the resilience of housing in the southern regions of the Tehran metropolis (Regions 15, 16, 19, and 20) against seismic activities. This research is practical and descriptive-analytical in terms of purpose and method, respectively. The required data and information were collected through library and survey methods and analyzed using the best-worst (BWM) method and Excel and Arc GIS software. For this purpose, by studying the background of the research, 24 critical criteria were identified, then using the (BWM) weighting method, and their importance coefficient was determined. Finally, the layers were combined using the fuzzy gamma operator to create a resilience map for the studied regions. The results showed that 43% of southern regions showed very low resilience, and 12% showed low resilience. On the contrary, in the physical-environmental index, 7% of the regions had very low resilience, and 22% had very high resilience. Overall, 50% of the regions showed low resilience, emphasizing the urgent need for targeted interventions. The findings emphasize the importance of addressing socio-economic factors in resilience planning and suggest that a comprehensive approach, a combination of socio-economic and physical-environmental indicators, is necessary to increase housing resilience against earthquakes in southern regions of Tehran.
Extended Abstract
Introduction
Rapid global urbanization is leading to unprecedented expansion in urban areas, with projections indicating a potential growth exceeding 200% by 2100, primarily driven by developments in emerging economies. Urban areas are increasingly vulnerable to various natural and environmental hazards, particularly earthquakes, which have doubled in frequency and intensity over the past four decades. These seismic events are of particular concern due to their potential to cause significant loss of life, economic disruption, and widespread damage, especially in densely populated urban centers. Earthquake-related disasters are further exacerbated by secondary effects such as landslides, liquefaction, and tsunamis, which can magnify the destruction and challenges in recovery efforts. Urban resilience has emerged as a crucial approach to mitigating the impact of such natural disasters. Resilience in this context refers to the capacity of urban systems to anticipate, resist, and recover from a range of shocks and stresses, encompassing both physical and social dimensions of urban environments. This approach advocates for more dynamic and adaptive urban systems that can absorb disturbances while maintaining functionality. Resilience is critical in earthquake-prone regions, where effective disaster risk reduction (DRR) strategies are vital for minimizing damage, safeguarding lives, and ensuring rapid recovery. Given the high seismic risk and vulnerability of Tehran, the capital of Iran, due to its proximity to fault lines, dense population, and various environmental factors, the resilience of housing structures in the city, particularly in its southern regions, is critical. This study aims to analyze the resilience of houses in the southern regions of the Tehran metropolis against earthquakes, focusing on identifying key indicators that influence resilience and measuring the overall resilience levels in these regions.
Methodology
This research adopts a descriptive-analytical approach, classified as applied research due to its focus on practical outcomes. The study identifies research dimensions through a comprehensive literature review and collects official data, including 2015 statistical blocks and existing city maps. The analysis combines multi-criteria decision-making methods with spatial analysis to assess resilience. The Best-Worst Method (BWM), introduced by Rezaei in 2015, was employed to weigh decision-making factors and criteria. Subsequently, a digital map of earthquake risk probability was created using Euclidean distance from fault layers in ArcGIS software. The study normalized and weighted 24 socio-economic and physical-environmental criteria, combining them using the Fuzzy Gamma operator to produce a resilience map for the study area. The research evaluates 11 socio-economic sub-criteria and 13 physical-environmental sub-criteria, ranging from population density and household size to distance from fault lines and access to critical infrastructure.
Results and discussion
The study's findings indicate significant variability in resilience levels across the southern regions of Tehran. The socio-economic resilience index revealed that 43% of the southern regions exhibit very low resilience, with an additional 12% displaying low resilience. In contrast, 28% of the regions demonstrate medium resilience, while only 13% and 4% show high and very high resilience, respectively. These results highlight substantial socio-economic challenges in nearly half of the southern regions, indicating a pressing need for targeted interventions to improve resilience. On the other hand, the physical-environmental resilience index presented a more balanced distribution of resilience levels. Only 7% of the regions showed very low resilience, while another 7% had low resilience. A significant portion of the regions fell into the medium to high resilience categories, with 23% displaying medium resilience, 20% high resilience, and 22% very high resilience. This distribution suggests that while physical-environmental factors contribute to resilience, there is still significant room for improvement, particularly in addressing the socio-economic vulnerabilities that exacerbate overall risk. When combining the socio-economic and physical-environmental indicators, the overall resilience map indicates that 50% of the regions possess very low resilience, with 13% showing low resilience, 12% medium resilience, 13% high resilience, and 12% very high resilience. These findings underscore the critical disparities in resilience across the southern regions and emphasize the need for a more integrated approach to resilience planning, particularly in addressing socio-economic factors. The research highlights that the most critical sub-criteria affecting resilience include the ratio of unstable building materials and population density, which had the highest importance coefficients. Conversely, distance from educational centers and sports fields had the lowest importance. The spatial analysis of resilience across socio-economic and physical-environmental indices provides a detailed understanding of the distribution of vulnerabilities and resilience levels, enabling more targeted and effective interventions.
Conclusion
The study concludes that there are significant disparities in the resilience of the southern regions of the Tehran metropolis, particularly between socio-economic and physical-environmental indicators. While the physical-environmental resilience shows a relatively balanced distribution, the socio-economic resilience reveals substantial challenges, with nearly half of the regions exhibiting very low to low resilience. These findings underscore the need for a holistic approach to resilience planning that integrates socio-economic and physical-environmental factors. The study also emphasizes the importance of spatial analysis in evaluating and enhancing resilience. Geographic Information Systems (GIS) and spatial data are invaluable tools in identifying high-risk regions, assessing infrastructure quality, and mapping socio-economic and physical-environmental variables. This comprehensive approach improves urban emergency management and provides data-driven insights for developing resilience policies and strategies that strengthen housing resilience to natural hazards. Ultimately, the research advocates for a more inclusive and dynamic approach to urban resilience that addresses urban systems' complexities and promotes sustainable development. By focusing on socio-economic and physical-environmental indicators, cities like Tehran can enhance their capacity to withstand and recover from seismic events, ensuring safer and more resilient urban environments for their inhabitants.
Funding
There is no funding support.
Authors’ Contribution
Authors contributed equally to the conceptualization and writing of the article. All of the authors approved thecontent of the manuscript and agreed on all aspects of the work declaration of competing interest none.
Conflict of Interest
Authors declared no conflict of interest.
Acknowledgments
We are grateful to all the scientific consultants of this paper.
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