ارزیابی تاب‌‌آوری منطقه‌ 20 کلان‌‌شهر تهران در برابر مخاطرات محیطی با استفاده از توابع فازی در سیستم اطلاعات جغرافیایی

منطقه‌ 20 در جنوب کلان‌شهر تهران با مخاطرات محیطی همچون سیلاب، زمین‌لرزه، بحران آب، آلودگی و طوفان مواجه است. افزایش تاب‌آوری دربرابر این مخاطرات مستلزم شناخت ظرفیت تاب‌آوری است؛ از این رو پژوهش حاضر با رویکرد توصیفی‌پیمایشی برای شناخت ظرفیت پایه‌ای تاب‌آوری این منطقه دربرابر مخاطرات محیطی انجام شد. نخست پرسش‌نامه‌ای با نظر کارشناسان برای استخراج مولفه‌های اثرگذار بر تاب‌آوری تهیه شد که برمبنای آن، 26 زیرمعیار در قالب چهار معیار اجتماعی‌اقتصادی، کاربری اراضی، دسترسی‌ها و زیرساخت‌های جاده‌ای به دست آمد. درجه‌ اهمیت هر زیرمعیار در تاب‌آوری با تحلیل شبکه و میزان عضویت آنها در تاب‌آوری با عملگرهای فازی مشخص شد؛ سپس زیرمعیارها با عملگرهای فازی and، or، sum، product و گاما روی هم گذاری و طبقه‌بندی محله‌ها در تاب‌آوری با خوشه‌بندی kmean انجام شد. نتایج نشان داد معیارهای اقتصادی‌اجتماعی و معیار زیرساخت‌ها با وزن 0.49 و 0.231 بیشترین اهمیت را در تاب‌آوری دارند. در معیار اقتصادی‌اجتماعی زیرمعیار استحکام منازل با وزن 0.332، در معیار پوشش اراضی زیرمعیار دسترسی به اماکن اجتماعی با وزن 0.321، در معیار دسترسی‌ها زیرمعیار مراکز بهداشتی‌درمانی با وزن 0.292 و در معیار زیرساخت‌های جاده‌ای زیرمعیار دسترسی به پل عابر پیاده با وزن 0.435، بیشترین وزن را در تاب‌آوری دارند. بهترین عملگر برای روی هم گذاری لایه‌ها، عملگر sum بود که بیشترین همبستگی را با معیارها دارد. درنهایت محله‌های منطقه‌ 20 به سه خوشه‌ تاب‌آوری زیاد، متوسط و ضعیف تقسیم شدند. از این بین، محله‌های جوانمرد، منصوریه، حمزه‌آباد، ابن‌بابویه، سرتخت، تقی‌آباد و عباس‌آباد به دلیل داشتن جمعیت مناسب، میزان مشارکت اقتصادی مطلوب، میزان مشارکت اجتماعی مطلوب، دوری از مسیل، دسترسی به زیرساخت‌های جاده‌ای و نزدیکی به مراکز خدمات‌رسانی، بیشترین تاب‌آوری را دربرابر مخاطرات محیطی دارند؛ اما محله‌های جنوبی و غربی در منطقه‌ 20، به دلیل دوری از مراکز خدمات‌رسانی و پل‌های عابر پیاده، نزدیکی به مسیل و کارخانه، کم‌بودن میزان مشارکت اقتصادی، و استحکام کم منازل، کمترین تاب‌آوری را دربرابر مخاطرات محیطی دارند.

Evaluation of the Resilience of District 20 of Tehran Metropolitan Region (TMR) against Environmental Hazards Using Fuzzy Functions in GIS Software

Extended abstractIntroduction:The idea of ​​resilience of different social, economic, physical, and managerial orientations has entered urban and regional studies on a large scale. This resilient system can absorb temporary or permanent crises and adapt to rapidly changing conditions without losing its function. Among these, resilience against natural disasters can be explained by how social, economic, institutional, political, and executive capacities of societies affect the increase of resilience and understanding of its dimensions in the society. Environmental crises, such as earthquakes, floods, fires, and climate pollution, have caused environmental vulnerability in cities and consequently created threats to their securities, especially in District 20 of Tehran City. By recognizing the dimensions of vulnerability in District 20 of this city against environmental crises, management strategies can be developed to reduce vulnerability and risks and enhance resilience. For this reason, the main purpose of this study was to evaluate resilience of the neighborhoods in District 20 of Tehran City against environmental crises. To achieve this goal, the Fuzzy MultiCriteria Decision Model (FMCDM) and Kmean method of classification were used. Methodology:To identify and assess the resilience of District 20 of Tehran against environmental crises, a database was created based on the crises and its spatial information was prepared in 4 criteria and 26 subcriteria. After creating the spatial database of the mentioned district and compiling the criteria and subcriteria, a layer of information was prepared in ArcGIS software and a distance map was drawn for each subcriterion through Euclidean distance mapping in order to measure and manage the resilience. Then, fuzzy operators were applied to draw each fuzzy map (subscale) with a value between 0 and 1. Analytic Network Process (ANP) method was utilized to weight and evaluate the research criteria and subcriteria. Next, the map of each criterion and subcriterion was drawn by combining the Euclidean distance and fuzzy operators multiplied by their fuzzy weights obtained from the ANP model in ArcGIS software. Thus, the final map was prepared for each criterion and subcriterion, which showed their values of resilience to the environmental crises. Then, fuzzy superimposing operators were applied to superimpose the fuzzy weighting maps and a superimposed map of 26 subcriteria (4 criteria) was obtained for each fuzzy operator. To identify the best fuzzy operator by superimposing the research subcriteria, analysis of spatial relationships between the independent variables and the dependent variable was done through the Ordinary Least Squares (OLS) regression. Finally, the classical Kmean clustering method was employed to classify the neighborhoods from the perspective of resilience to environmental crises. Discussion:The results showed that the weights and values of the socioeconomic criteria, road infrastructure, land use and accessibility in resilience measures were 0.49, 0.23, 0.16, and 0.11, respectively. In the socioeconomic, road infrastructure, land use, and accessibility criteria, the subcriteria of house strength, pedestrian bridge, access to social places, and access to medical centers with the weights of 0.33, 0.43, 0.32, and 0.29 had the highest values in resilience. Among the fuzzy superposition operators, the algebraic addition operator (SUM) had the highest correlation with the research criteria in identifying the resilience of the neighborhoods. The northeast and southeast neighborhoods, as well as the central neighborhoods of District 20 of Tehran, were the most resilient neighborhoods to environmental crises. In the final step of the current research, the classical Kmean method was used to cluster the existing neighborhoods in District 20 of Tehran City based on their resilience to environmental crises. The results revealed that the neighborhoods were divided into 3 clusters. In the first cluster showing a lot of patience, the neighborhoods of Javanmard Qassab, Mansouria and Mangal, Hamzehabad, Sartakht, Ibn Babavieh and Zahirabad, Taghiabad, and Abbasabad were located. In the second cluster indicating moderate tolerance, Dolatabad and Shahadat, Sadeghieh, Shahid Ghayuri, Deilman, Aqdasiyeh, Estakhr, and Alain neighborhoods were situated. Finally, the neighborhoods of Sizdeh Aban, Shahid Beheshti, Firoozabadi, Valiabad, and Hashemabad were located in the third cluster with poor productivity. Conclusion:Environmental crises, such as earthquake, flood, drought, air and water pollution, and fire, have the potential to become harmful in areas where there are no crisis management and risk mitigation. In the 21st century, the world has been hit by such environmental crises as Asian tsunamis, Hurricanes Katrina and Rita, successive earthquakes, flash floods, desert dust storms, and widespread fires. Although predictive tools are able to predict some disasters, future crises cannot be forecast based on empirical evidence. Therefore, increasing the ability of a system called resilience is very important for responding to such crises; yet, its resilience must first be measured. In the present study, the resilience of District 20 of Tehran City to environmental crises was evaluated based on socioeconomic, road infrastructure, land use, and accessibility criteria. The results of this modeling led to the extraction of 3 clusters for the resilience of the neighborhoods of District 20 of Tehran against environmental crises. The neighborhoods in the west region had the highest resilience compared to the urban areas. Keywords: resilience, home strength, Analytic Network Process (ANP), fuzzy operator, regression References Asadzadeh, A., Kötter, T., Zebardast, E. (2015). An augmented approach for measurement of disaster resilience using connective factor analysis and analytic network process (F’ANP) model. International Journal of Disaster Risk Reduction, 14, 504518. Bacud, S. T. (2018). 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Diagram of the steps of the work method in the present study Table 1 The weight of research criteria in resilience of District 20 of Tehran against environmental hazards Tab 3 Weight of criteria socioeconomic in the resilience of Tehran’s 20th districtFigure 3 Zoning of population and young population subcriteria in the resilience of District 20 of Tehran Figure 4 Zoning of Economic participation and employment rates subcriteria in the resilience of District 20 of Tehran Figure 5 Zoning of Home strength and literacy rates subcriteria in the resilience of District 20 of Tehran Tab 4 Weight of criteria and subcriteria of land cover in the resilience of Tehran’s 20th district Figure 6 Zoning of Access to parks and social sites subcriteria in the resilience of District 20 of Tehran Figure 7 Zoning of Distance from the flood and access to water sources subcriteria in the resilience of District 20 of Tehran Figure 8 Zoning of Distance from agricultural lands and urban green space subcriteria in the resilience of District 20 of Tehran Figure 9 Zoning of Distance from the green belt and outdoor rates subcriteria in the resilience of District 20 of Tehran Tab 5 Standard weight and subcriteria of accesses in Tehran 20 district resilience Figure 10 Zoning of Access to fuel station and security police subcriteria in the resilience of District 20 of Tehran Figure 11 Zoning of Access to educational and administrative centers subcriteria in the resilience of District 20 of Tehran Figure 12 Zoning of Access to Commercial and service centers subcriteria in the resilience of District 20 of Tehran Figure 13 Zoning of Access to Medical centers and distance from the factory subcriteria in the resilience of District 20 of Tehran Tab 6 Standard weight and subcriteria of road infrastructure in Tehran 20 district Figure 14 Zoning of Access to bus and freeway stations subcriteria in the resilience of District 20 of Tehran Figure 15 Zoning of Access to the pedestrian bridge and railway station subcriteria in the resilience of District 20 of Tehran Figure 16 Zoning of Criteria for access to urban services and socioeconomic criteria in the resilience of District 20 of Tehran Figure 17 Zoning of Land use criteria and access to road infrastructure criteria in the resilience of District 20 of Tehran Tab 7. Correlation coefficient between fuzzy overlay operators with research criteria Fig 18. Overlapping of research criteria with SUM operator and resilience modeling of Tehran Region 20