ارزیابی سطح هوشمندی محلات شهری ارومیه مورد مطالعه: مناطق پنج‏‏گانة شهر ارومیه

نوع مقاله : مقاله علمی پژوهشی

نویسندگان

1 دانشجوی کارشناسی ارشد جغرافیا، برنامه‌ریزی آمایش سرزمین، دانشگاه ارومیه، ایران

2 دانشیار گروه جغرافیا، برنامه‌ریزی روستایی، دانشگاه ارومیه، ایران

3 استاد گروه جغرافیا، آب‌وهواشناسی، دانشگاه ارومیه، ایران

چکیده

هدف از این تحقیق بررسی و تحلیل فضایی شاخص ‏های شهر هوشمند و عوامل مؤثر بر آن از طریق  شش شاخص حکمروایی، مردم، زندگی، پویایی، محیط، و اقتصاد هوشمند است. روش پژوهش این تحقیق تحلیلی- توصیفی و آزمون همبستگی است. برای تجزیه ‏و تحلیل داده‏ ها نیز از مدل‏ های کمی تصمیم ‏گیری ‏های چندمعیارة آنتروپی، ضریب پراکندگی، تحلیل خوشه ‏ای، و تحلیل رگرسیون استفاده‏ شده است. حجم نمونه با استفاده از فرمول کوکران 384 نفر انتخاب شد. روش نمونه ‏گیری طبقه ‏بندی تصادفی ساده و تخصیص متناسب است. بر اساس نتایج به ‏دست‏آمده، شاخص شهر هوشمند در محلة 8 شهریور با امتیاز تاپسیس 0.799 واقع در منطقة 3 در رتبة نخست هوشمندی در بین محله‏ های شهر است که بیشترین ضریب تأثیر در این محله مربوط به شاخص‏های زندگی هوشمند با امتیاز 0.29 است. رتبة آخر این رده بندی مربوط به محلة کوهنورد با امتیاز 0.16 واقع در منطقة 2 شهر ارومیه است. همچنین، میزان هوشمندی بین شاخص‏ های تلفیقی در رتبه ‏بندی مناطق پنج‏گانه، منطقة 3 با وزن 1 و منطقة 4 با وزن 0.001 به‏عنوان دو قطب متضاد برخوردار و محروم در سطح محله مطر‏ح ‏اند. بین حکمروایی و شاخص‏ های تلفیقی شهر هوشمند ارتباط همبستگی معناداری مشاهده نشد. شاخص ضریب پراکندگی نشان می ‏دهد در بین شاخص ‏های مختلف بیشترین میزان نابرابری در شاخص ‏های مردم هوشمند با مقدار 0.86 و کمترین میزان نابرابری در شاخص ‏های محیط هوشمند با مقدار 0.40 وجود دارد. نتایج حاصل از تحلیل رگرسیون توأم نشان می‏دهد از بین شاخص ‏های شش‏گانه، شاخص ‏های زندگی و اقتصاد هوشمند بیشترین سطح معناداری را در تبیین و پیش‏بینی شهر هوشمند دارند.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Zoning of urban smart living spaces Case study: Five Municipalities area of Urmia city

نویسندگان [English]

  • Akram Hoseini 1
  • Ali Akbar Taghiloo 2
  • Alireza Movaghari 3
1 Department of Geography, Faculty of Literature and Humanities, Urmia University, Urmia, Iran
2 Geography, Faculty of Literature, Urmia University, Iran
3 Department of Geography, Faculty of Literature and Humanities, Urmia University, Urmia, Iran
چکیده [English]

Introduction
In order to minimize the undesirable effects of unsteady growth of Urmia and to apply the smart-growth model for this city, recognizing the characteristics of different areas and their inequality in planning, is the basis of the work. Therefore, proper planning should be done to eliminate these inequalities and transform the optimal situation. Areas need to be categorized in terms of "development" in order to plan for whether or not they are developed. In measuring smart growth indices, there are different types of statistical methods and techniques. Using quantitative criteria and methods to classify the neighbourhoods and urban areas of Urmia in terms of smart growth indices not only recognizes the differences between areas, but also these criteria for determining the types. The services needed and the adjustment of inequality between areas of the city. The present study tries to study the spatial distribution of urban smart growth components in the five urban areas of Urmia and based on the obtained scores, the rate of urban smart growth indices in three levels of smart, semi-intelligent and less intelligent. Therefore, the following objectives were considered for the study: Identification of Smart Areas of Urmia, Prioritizing Urban Areas of Urmia for Future Planning in line with Urban Smart Growth Pattern and Identifying Homogeneous Neighborhoods of Urmia in terms of Urban Smart Growth Indicators.
Methodology
The approach of the research method in this study is of applied type and it is descriptive-analytical and correlational. Spatial statistics tests were used to model the spatial pattern of smart neighbourhood distribution. To identify the spatial pattern of intelligent living spaces and finally to identify the desired zones. First, library studies were used to identify smart city indices from different sources and databases. Accordingly, six main indices (intelligent dynamics, intelligent people, intelligent living, intelligent environments, intelligent governance, and smart economics) with 91 items were used. The field was determined. Regarding the research subject, random sampling was used in order to obtain the maximum accuracy coefficient in obtaining samples with a high degree of characteristics of the statistical population and the results of which can be generalized to the whole population. According to Cochran's formula, 384 people were selected as the sample population. Simple random stratified sampling and distribution of samples for 30 neighbourhoods were done based on proportional allocation. Questionnaires were collected based on field method through direct interviews with residents of five districts. In this study, Cronbach's alpha coefficient was calculated using SPSS software. The reliability of the research is significant since the reliability of the questionnaire was assigned to each of the answers 1 to 5 with a Cronbach's alpha of 0.785. In order to complete the questionnaire, a questionnaire was distributed in each of the five urban areas. According to the objectives of the study, Shannon entropy (as a multi-criteria decision-making method) was used to evaluate and rank Urmia metropolitan areas in terms of smart growth indices. Regression analysis (Pearson function and linear regression) were used in SPSS software.
Results and discussion
To achieve definitive ranking in terms of smart growth indices, all 91 variables were computed using Shannon entropy model and results were slightly different. In terms of integrated indices of Region 3, with an entropy value of 1 was ranked first. The region was also ranked first in smart living indicators. The last rank came in the 4th place with an entropy value of 0 which was in the last place in relation to the smart governance index. Overall, Region 3 was ranked as one of the most prosperous regions in terms of smart growth indices with economic and social structure, good accessibility, favourable environment, dynamic economy, proper urban infrastructure, proportional distribution of land uses and construction density. The mean of the integrated indices is 0.39 and the standard deviation is 0.39. Area one has the highest score above average and other areas are below average. Using the inequality coefficient, the coefficient of equilibrium in urban smart growth indices between urban areas for these indicators was calculated and a value of 1.01 was obtained, indicating heterogeneity and divergence between urban areas in terms of intelligence indicators. This inequality is affected by the inadequate distribution of facilities and services throughout the city. According to the calculated entropy and inequality coefficient, there are differences and inequality between the neighbourhoods of Urmia in terms of smart growth indices. In other words, this paper investigates and ranks the neighbourhoods of the five urban areas of Urmia for urban smart growth index using Shannon entropy model. The results of the ranking show that the neighbourhoods of Urmia city achieved different scores and scores in each of the indicators of a smart economy, smart people, smart governance, smart dynamics, and smart environment. This indicates significant inequality and differences in some indicators. The highest inequality between the indicators of smart governance and the lowest inequality between the indicators of intelligent life. All six indices (91 items) were combined and then tested for composite rank. Then the entropy of each index was calculated and classified using three clusters using cluster analysis. According to the consolidated results, smart growth index in neighbourhood 8 Shahrivar with entropy value 0.799 located in region 3 is in the first rank among smart neighbourhoods. The neighbourhoods of the school, Isarah, Imamate and Ayatollah Dastgheib are in second to fifth place, respectively. The last rank of this ranking is for the Kohnavard neighbourhood with an entropy value of 0.16 located in District 2 of Urmia.
Conclusion
Combined regression fitting shows that smart living variables have the greatest impact on predicting and developing the spatial structure of smart growth in urban neighbourhoods so that one unit change in the deviation of smart living indices will cause 0.680 units to change in integrated growth indices. The results emphasize the need for attention and prioritization of the Kohnavard neighbourhood in Zone 2 in future development and planning.

کلیدواژه‌ها [English]

  • Living Space"
  • Smart City Indicators"
  • Shannon Entropy"
  • "
  • Ranking"
  • Urmia City"
  1. ابوالحسن‏پور، امیر، 1387، تأثیرگذاری برای به‏کارگیری سیستم‏های حمل و انتقال هوشمند T.S در روان‏سازی ترافیک شهر اصفهان، مطالعات مدیریت مدیریت چاپ، ش 8، ص 26-32.
  2. بندرآباد، علیرضا، 1390، شهر زیست‏پذیر از مبانی تا معانی، تهران: آذرخش.
  3. پوراحمد، احمد؛ زیاری، کرامت‏الله؛ حاتم‏نژاد، حسین و پارسا پشاه‏آبادی، شهرام، 1397، تبیین مفهوم و ویژگی‏های شهر هوشمند، فصل‏نامة باغ نظر، س ۱۵، ش ۵۸.
  4. پورمحمدی، محمدرضا و قربانی، 1382، ابعاد و راهبردهای پارادایم متراکم‏سازی فضاهای شهری، فصل‏نامة مدرس علوم انسانی، ش 29، صص ۸۵-108.
  5. زیاری، کرامت‏الله، 1380، توسعة پایدار و مسئولیت برنامه‏ریزان شهری در قرن بیست‏ویکم، مجلة دانشکدة ادبیات و علوم انسانی دانشگاه تهران، ش 160، صص 371-385.
  6. سیف‏الدینی، فرانک و منصوریان، حسین، 1390، تحلیل الگوی تمرکز خدمات شهری و آثار زیست‏محیطی آن در شهر تهران، فصل‏نامة محیط‏شناسی، ش 60، صص 53-64.
  7. ضرابی، اصغر؛ صابری، حمید؛ محمدی، جمال و وارثی، حمیدرضا، 1390، تحلیل فضایی شاخص‏های رشد هوشمند شهری (مطالعة موردی: مناطق شهر اصفهان)، فصل‏نامة پژوهش‏های جغرافیای انسانی، ش 77، صص 1-17.
  8. فرید، یدالله، 1373، جغرافیا و شهرشناسی، تبریز: انتشارات دانشگاه تبریز.
  9. مبارکی، امید و عبدلی، اصغر، 1392، تحلیل سلسله‏مراتب مناطق شهر ارومیه بر پایة شاخص‏های توسعة پایدار شهری، نشریة تحقیقات کاربردی علوم جغرافیایی، 13 (30): 49-
  10. مختاری، رضا؛ حسین‏زاده، رباب و صفرعلی‏زاده، اسماعیل، 1392، تحلیل الگوهای رشد هوشمند شهری در مناطق چهارده‏گانة اصفهان بر اساس مدل‏های برنامه‏ریزی منطقه‏ای، مطالعات و پژوهش‏های شهری و منطقه‏ای، 5 (19): 65-
  11. مهاجری، مهسا و پری زنگنه، عبدالحسین،1391،رشد هوشمند شهری راهکارهای برای کاهش آلودگی هوا در کلان شهرها، اولین
  12. ثریا احمدی، سید محمد مهدی زاده، سیدوحید عقیلی، (1389)، تاثیر استفاده از تلفن همراه بر شکل گیری هویت شخصی مدرن در میان نوجوانان و جوانان شهر تهران،فصلنامه پژوهش های ارتباطی، ۱۶(۶۰)، ۱۲۵.
  13. کنفرانس مدیریت آلودگی هوا و صدا، تهران، https://civilica.com/doc/185144
  14. Abolhassanpour, Amir, 2008, Effective for Implementation of Intelligent Transportation Systems I.T.S in Traffic Lifestyle Isfahan Print Management, Issue 8, pp. 26-32.
  15. Bandar Abad, Alireza, 2010, City habitable from Basics to Meaning, Tehran: Azarakhsh Publications
  16. Pourahmad, Ahmad; Ziyari, Karamatollah; Hatamnejad, Hossein; Parsa Pashahabadi, Shahram, 2018, Explaining the Concept and Characteristics of Smart City, Quarterly Bagh Nazar, Fifteenth Year, No. 58.
  17. Pourmohammadi, Mohammad Reza and Ghorbani, Rasoul, 2003, Dimensions and Strategies of Urban Space Compression Paradigm, Quarterly Journal of Humanities, No. 29, pp. 85-108.
  18. Ziyari, Karamatollah, 2001, The Sustainable Development and Responsibility of Urban Planners in the 21st Century, Journal of the Faculty of Literature and Humanities, University of Tehran, No. 160, pp. 385-371.
  19. Seifaddini, Farank and Mansourian, Hossein, 2011, Analysis of Urban Services Concentration Pattern and its Environmental Effects in Tehran, Journal of Environmental Studies, No. 60, pp. 53-64.
  20. Zarabi, Asghar; Saberi, Hamid; Mohammadi, Jamal and Verarsati, Hamid Reza, 2011, Spatial Analysis of Urban Smart Growth Indices (Case Study: Isfahan City Areas), Journal of Human Geography Research, No. 77, pp. 17-1.
  21. Farid, Yadollah, 1994, Geography and Urban Studies, Tabriz: Tabriz University Press.
  22. Mobaraki, Omid and Abdoli, Asghar, 2013, Hierarchy Analysis of Urmia City Based on Sustainable Urban Development Indicators, Journal of Applied Geographical Sciences Research, 13 (30): 49-65.
  23. Soraya Ahmadi, Seyed Mohammad Mehdizadeh, Seyed Vahid Aghili, (2010). The effect of mobile phone use on the formation of modern personal identity among adolescents and young people in Tehran, Quarterly Journal of Communication Research, 16 (60), 125.
  24. Cohen, B., Almirall, E., & Chesbrough, H. (2016). The city as a lab: Open innovation meets the collaborative economy. California Management Review, 59(1), 5-13.
  25. Holler, J., Tsiatsis, V., & Mulligan, C. i in.(2014), From machine-to-machine to the Internet of Things: Introduction to a New Age of intelligence.
  26. Mohajeri, Mahsa and Peri Zanganeh, Abdolhossein, 2012, Smart Urban Growth Strategies to Reduce Air Pollution in Metropolises, The First Conference on Air and Noise Pollution Management, Tehran, https://civilica.com/doc/185144
  27. Mokhtari, Reza; Hosseinzadeh, Robab and Safaralizadeh, Ismail, 2013, Analysis of Urban Smart Growth Patterns in Fourteen Areas of Isfahan Based on Regional Planning Models, Urban and Regional Studies, 5 (19): 65-82.
  28. Borga, G.; Camporese, R.; Di Prinzio, L.; Niccolandelli, S. and Picchio, A. R., 2011, New Technologies And Eo Sensor Data Build Up Knowledge For A Smart Cityinternational Conference Data Flow From Space To Earth Application and Inter Operability, Venice, Italy, 21-23 March.
  29. Bricker, S. H.; Banks, V. J.; Galik, G.; Tapete, D. and Jones, R., 2017, Accounting for groundwater in future city visions. Land Use Policy, 69, 618-630.
  30. Caragliu, A.; Del Bo, C. and Nijkamp, P., 2009, Smart Cities in Europe. In Proceedings of the 3rd Central European Conference in Regional Science – CERS 2009 (pp. 49-59).
  31. Chourabi, H.; Nam, T.; Walker, S.; Gil-Garcia, J. R.; Mellouli, S.; Nahon, K.; ... and Scholl, H. J., 2012, January Understanding smart cities: An integrative framework. In System Science (HICSS), 2012 45th Hawaii International.
  32. Chrysochoou, M., 2012, A GIS and indexing scheme to screen brownfields for area-wide redevelopment planning. Landscape and Urban Planning, 105, 187-198.
  33. Conference on (pp. 2289-2297). IEEE.
  34. Cooke, P. and De Propris, L., 2011, A policy agenda for EU smart growth: the role of creative and cultural industries. Policy Studies, 32(4), 365-375.
  35. Correia, L. M. and Wünstel, K., 2012, Smart cities applications and requirements, NetWorks European Technology Platform, [on line]: smit.vub.ac.be.
  36. Cowan, Robert, 2005, The Dictionaryof Urbanism, Streetwise Press.
  37. Domingue, J.; Galis, A.; Gavras, A.; Zahariadis, T.; Lambert, D.; Cleary, F.; ... and Schaffers, H. (Eds.) (2011). The future internet: future internet assembly 2011: achievements and technological promises (Vol. 6656). Springer.
  38. Anastasia, S. (2012). The concept of smart cities; Towards community development? Networks and communication studies. 26.
  39. Feiock, R. C.; Tavares, A. F. and Lubell, M., 2008, Policy Instrument Choices for Growth Management and Land Use Regulation. The Policy Studies Journal, 36(3), 461-480.
  40. Giffinger, R. et al., 2007, Smart Cities Ranking of European Medium-sized Cities. Centre of Regional Science, Vienna UT.
  41. Hawkins, C. V., 2011, Smart Growth Policy Choice: A Resource Dependency and Local Governance Explanation. The Policy Studies Journal, 39(4), 682-697.
  42. Pourahmad, Ahmad; Ziyari, Karamatollah; Hatamnejad, Hossein; Parsa Pashahabadi, Shahram, 2018, Explaining the Concept and Characteristics of Smart City, Quarterly Bagh Nazar, Fifteenth Year, No. 58.
  43. Susanti, R.; Soetomo, S.; Buchori, I. and Brotosunaryo, P. M., 2016, Smart Growth, Smart City and Density: In Search of The Appropriate Indicator for Residential Density in Indonesia. Procedia - Social and Behavioral Sciences, 227, 194-201.
  44. Taewoo, N. and Theres, P., 2010, Conceptualizing smart city widh dimensions of technology, people, and institutions, Proceedings of the 12th Annual International Digital Government, Luis Luna-Reyes, Vijay Atluri.
  45. Yang, Fei, 2009, If ‘Smart’ is ‘Sustainable’? An Analysis of Smart Growth Policies and Its Successful Practices, A Thesis Submitted to the Graduate Faculty in Partial Fulfillment of the Requirements for the Degree of Master of Community and Regional Planning, Iowa State University Ames. IA, USA.