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افسری, رسول, نیک روش, فاطمه, حسین پور, هاله. (1402). ارزیابی مکانی کیفیت زندگی شهری: مورد مطالعه منطقه 2 تهران. , 11(3), 213-237. doi: 10.22059/jurbangeo.2024.366022.1864
رسول افسری; فاطمه نیک روش; هاله حسین پور. "ارزیابی مکانی کیفیت زندگی شهری: مورد مطالعه منطقه 2 تهران". , 11, 3, 1402, 213-237. doi: 10.22059/jurbangeo.2024.366022.1864
افسری, رسول, نیک روش, فاطمه, حسین پور, هاله. (1402). 'ارزیابی مکانی کیفیت زندگی شهری: مورد مطالعه منطقه 2 تهران', , 11(3), pp. 213-237. doi: 10.22059/jurbangeo.2024.366022.1864
افسری, رسول, نیک روش, فاطمه, حسین پور, هاله. ارزیابی مکانی کیفیت زندگی شهری: مورد مطالعه منطقه 2 تهران. , 1402; 11(3): 213-237. doi: 10.22059/jurbangeo.2024.366022.1864

ارزیابی مکانی کیفیت زندگی شهری: مورد مطالعه منطقه 2 تهران

پژوهش‌های جغرافیای برنامه‌ریزی شهری
دوره 11، شماره 3، آبان 1402، صفحه 213-237    اصل مقاله (3.08 M)
نوع مقاله: پژوهشی - کاربردی
شناسه دیجیتال (DOI): 10.22059/jurbangeo.2024.366022.1864
نویسندگان
رسول افسری* 1؛ فاطمه نیک روش2؛ هاله حسین پور3
1گروه شهرسازی، دانشکده پدافند غیرعامل، دانشگاه عالی دفاع ملی، تهران، ایران
2گروه جغرافیای انسانی، دانشکده جغرافیا، دانشگاه تهران، تهران، ایران
3گروه شهرسازی، واحد پردیس، دانشگاه آزاد اسلامی، پردیس، ایران.
چکیده
ارزیابی و کمی‌سازی کیفیت زندگی شهری یکی از پیش‌نیازهای مهم و کلیدی در برنامه‌ریزی و توسعه شهری است. هدف اصلی مطالعه حاضر ارائه یک استراتژی مبتنی بر سیستم تصمیم‌گیری چند معیاره مکانی برای ارزیابی کیفیت زندگی شهری در منطقه 2 تهران می‌باشد. برای این منظور، از 8 زیرمعیار محیطی و 6 زیرمعیار زیرساختی استفاده شد. وزن معیارها و زیرمعیارها موثر بر اساس نظر کارشناسان با استفاده از روش بهترین-بدترین محاسبه شد. سپس از روش میانگین وزنی مرتب‌شده برای تولید نقشه‌های کیفیت زندگی شهری در سناریوهای ذهنی مختلف استفاده شد. در نهایت، توزیع مکانی جمعیت در کلاس‌های مختلف کیفیت زندگی شهری ارزیابی شد. از بین معیارهای زیرساختی و محیطی به ترتیب معیارهای تراکم جمعیت و آلودگی هوا دارای بیشترین تأثیر در کیفیت زندگی شهری بودند. نقشه‌های کیفیت زندگی شهری در سناریوهای مختلف نشان داد که با افزایش درجه خوش‌بینی مساحت طبقات با کیفیت زندگی شهری بالا و خیلی بالا افزایش و با کاهش مقدار درجه خوش‌بینی مساحت طبقات با کیفیت زندگی شهری بالا و خیلی بالا کاهش می‌یابد. نتایج این مطالعه نشان داد که درصد بالایی از جمعیت در محیط شهری در شرایط کیفیت زندگی شهری پایین ساکن هستند که بیانگر ضرورت ارزیابی وضع موجود کیفیت زندگی شهری و برنامه‌ریزی برای بهبود وضع وجود می‌باشد
کلیدواژه‌ها
کیفیت زندگی شهری؛ سیستم اطلاعات جغرافیایی؛ میانگین وزنی مرتب‌شده؛ روش بهترین-بدترین؛ منطقه 2 تهران
عنوان مقاله [English]
Spatial evaluation of the quality of urban life The case study of the district 2 of Tehran
نویسندگان [English]
Rasoul Afsari1؛ Fatemeh Nickraveh2؛ Haleh Hosseinpour3
1Department of Urban Planning, Faculty of Non-Active Defense, Higher National Defense University, Tehran, Iran
2Department of Human Geography, Faculty of Geography, University of Tehran, Tehran, Iran
3Department of Urban Planning, Pardis Branch, Islamic Azad University, Pardis, Iran
چکیده [English]
ABSTRACT
Evaluation and quantification of the quality of urban life is one of the important and key prerequisites in urban planning and development. The purpose of this study is to provide a strategy based on a multi-criteria decision-making system to evaluate the quality of urban life. For this purpose, 8 environmental criteria and 6 infrastructure criteria were used. The weight of the effective criteria was calculated based on the opinion of experts using the BWM. Then, the OWA method was exerted to produce urban life quality maps in different mental scenarios. Finally, the spatial distribution of the population in different classes of quality of urban life was evaluated. Among the infrastructural and environmental criteria, population density and air pollution had the most significant impact on the quality of urban life. The quality of urban life maps in different scenarios showed that with the increase in the degree of optimism, the area of the classes with high and very high quality of urban life increases, and with the decrease of the degree of optimism, the area of the classes with high and very high quality of urban life decreases. The results of this study showed that a high percentage of the population in the urban environment lives in conditions of low quality of urban life, which indicates the necessity of evaluating the current state of the quality of urban life and planning to improve the existing state.
Extended Abstract
Introduction
The growth of cities since the beginning of the 20th century, the exponential increase of the urban population, the inappropriate and disorganized physical growth, and the quantitative approach to urban planning and neighborhoods have changed the culture of neighborhoods, inter-neighborhood migrations, and dissatisfaction with the quality of urban environments, which has been accompanied by the loss of identity and sense of belonging among residents. Therefore, to deal with such a trend, an approach called the quality of urban life has been proposed to create a desirable urban life. This approach is based on the belief that urban places, as part of human identity, also form an emotional bond between people and their surroundings. Therefore, paying attention to the quality of urban life can create a sense of belonging and identity in citizens towards the urban environment. Thus, this study aims to evaluate the quality of urban life in District 2 of Tehran by insisting on risk in decision-making. To achieve this goal, a risk-based expert system based on a geographic information system will be used. This system's ability is flexible in creating a wide range of scenarios (very optimistic to very pessimistic).
 
Methodology
The spatial data in this study includes satellite-based data, location-based field data, and spatial layers collected from related organizations. The research method in this study includes five steps. In the first stage, using past studies and experts' opinions, effective criteria for the quality of urban life were identified, and a spatial database of these data was created. In the second stage, due to the different sources of the collected data, the pre-processing operation was done on the data first. Then, according to the type of criterion, a map of the criteria was prepared using spatial analysis in GIS. Normalization of the criteria map, calculation of weight, and importance of criteria and sequential weights were done in the third stage. In the fourth step, using the ordered weighted averaging method, quality of urban life maps was prepared in different decision-making scenarios for environmental and infrastructure dimensions. Also, at this stage, the final quality of urban life maps was prepared by combining the two considered dimensions. Finally, in the fifth stage, an assessment of population distribution in urban quality of life classes was done.
 
Results and discussion
In this study, in the environmental dimension, air pollution, discomfort index, and vegetation cover criteria had the highest weight, and elevation, distance from stream network, and distance from fault had the lowest weight. Also, in terms of infrastructure, population density and distance from the road network have the most weight, and the criteria of distance from industrial areas and medical centers have the least weight. The visual evaluation of the quality of urban life maps in the environmental dimension shows that the eastern and central half of the studied area has a better quality of urban life than other regions. This is due to the adjustment of the urban microclimate in accordance with the increase of vegetation, reduction of air pollution, and improvement of the condition of discomfort index towards the eastern and central parts, directly affecting other environmental indicators. Regarding infrastructural criteria, the areas located north of the study area have the worst quality of urban life, and most areas with very low quality of urban life are located in these areas. However, the central parts of the studied region have a more favorable quality of urban life than other parts. The road network infrastructure, subway stations, medical centers, and parks are more concentrated in these areas than in others.
The combination of urban life quality maps in environmental and infrastructure dimensions showed that with the increase in the degree of optimism, the area of the areas located in the high and very high quality of urban life class increases, and the area of the areas located in the low and very low quality of urban life class decreases. So, the very low, low, medium, high, and very high quality of urban life in the very pessimistic scenario was 11.84, 20.07, 11.17, 3.73, and 1.58 km2, respectively. In a very optimistic scenario, these values would reach 3.46, 6.42, 13.79, 15.78, and 8.96 km2.
 
Conclusion
From an environmental point of view, air pollution and distance from the fault criteria, respectively, have the most and the least impact on modeling the quality of urban life. Also, in terms of infrastructure, the population density criterion has the most impact, and the distance from industrial areas criterion has the least impact in modeling the quality of urban life. The central and eastern regions of the studied region have better urban life quality conditions than other regions. With the increase in the degree of optimism, the area of the areas located in the class of high and very high quality of urban life increases, and the area of the areas located in the class of low and very low quality of urban life decreases. In the very pessimistic, pessimistic, intermediate, optimistic, and very optimistic scenarios, respectively, 5.31, 7.94, 10.24, 14.66, and 24.73 square kilometers of the studied area have suitable urban life quality conditions (high and very high class). In a very pessimistic state, 650,963 and 9,162 thousand people of the study area population are located in areas with unsuitable (low and very low class) and suitable (high and very high) quality of urban life, respectively. The results of this study can be useful for managers and planners to implement plans and programs to improve the quality of urban life.
 
Funding
There is no funding support.
 
Authors’ Contribution
All authors contributed equally to the preparation of this manuscript.
 
Conflict of Interest
Authors declared no conflict of interest.
 
Acknowledgments
We are grateful to all the scientific consultants of this paper.
کلیدواژه‌ها [English]
Quality of Urban Life, Geographic Information System, Ordered Weighted Averaging (OWA), Best-Worst Method (BWM), District 2 of Tehran
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