ارزیابی شهرستان‌های استان آذربایجان شرقی از لحاظ شاخص های زیربنایی با استفاده از تحلیل رابطه خاکستری

فصلنامه علمی برنامه ریزی منطقه ای

مقاله 3، دوره 10، شماره 38، مرداد 1399، صفحه 33-50   

نوع مقاله: مقاله پژوهشی

نویسندگان

فاطمه طاهرپور¹؛ موسی واعظی^{* 2}؛ هابیل خرمی³؛ مجید اکبری⁴

¹کارشناس ارشد جغرافیا و برنامه‌ریزی شهری، دانشگاه محقق اردبیلی، اردبیل، ایران

²دانشجوی دکتری جغرافیا و برنامه‌ریزی شهری، دانشگاه تبریز، تبریز، ایران

³دانش آموخته جغرافیا و برنامه‌ریزی، دانشگاه تبریز، تبریز، ایران

⁴دانشجوی دکتری جغرافیا و برنامه‌ریزی شهری، دانشگاه پیام نور تهران، تهران، ایران

تاریخ دریافت: 25 بهمن 1397،  تاریخ بازنگری: 27 شهریور 1398،  تاریخ پذیرش: 26 مهر 1398 

چکیده

         امروزه برخورداری متوازن و رعایت تعادل و برابری در دست­یابی به شاخص­های توسعه در کلیه ابعاد آن، به خصوص در سطح منطقه­ای در کشورهای در حال توسعه و به خصوص کشور ما یکی از چالش­های اصلی دست­یابی به توسعه پایدار با توجه به اصول تعریف شده برای آن است. در این راستا هدف از این پژوهش، ارزیابی و اولویت­بندی شهرستان­های استان آذربایجان­شرقی از لحاظ شاخص­های زیربنایی می­باشد. پژوهش حاضر از نظر نوع کاربردی و از نظر ماهیت توصیفی - تحلیلی می­باشد. بدین منظور20 شهرستان از لحاظ شاخص­های زیربنایی در قالب 46 شاخص قابل سنجش بررسی شدند. جهت تجزیه و تحلیل داده­ها از مدل آنتروپی شانون تعمیم­یافته، تحلیل رابطه خاکستری (GRA)، ضریب همبستگی پیرسون در قالب نرم­افزار SPSS استفاده شده است. یافته­های پژوهش حاکی از آن است که: 1- بر اساس تحلیل داده­ها در مدل رابطه خاکستری، شهرستان­های کلیبر، ورزقان، چاراویماق، خدآفرین و جلفا از نظر شاخص­های زیربنایی با میانگین ضریب اولویت (749/0)، در وضعیت بسیار محروم قرار گرفتند و اولویت اول برنامه­ریزی در جهت توسعه باید با این شهرستان­ها باشد. 2- بر اساس آزمون ضریب همبستگی پیرسون (512/0)، بین امکانات و زیرساخت­های زیربنایی و میزان جمعیت شهرستان­ها رابطه و همبستگی مثبتی وجود دارد. در سوی دیگر بین   شاخص­های زیر بنایی شهرستان­های استان و میزان نرخ رشد شهرنشینی آن­ها رابطه و همبستگی مثبتی وجود ندارد. پس در حالت کلی می­توان نتیجه­گیری کرد که در استان آذربایجان­شرقی امکانات و زیرساخت­های زیربنایی به سمت شهرستان­هایی سوق دارد که از جمعیّت بیشتری برخوردارند اما بین میزان برخورداری از شاخص­های زیربنایی و نرخ شهرنشینی شهرستان­ها محدوده رابطه معناداری وجود ندارد.

کلیدواژه‌ها

"توسعه یافتگی"؛ "توزیع فضایی"؛ "شاخص های زیربنایی"؛ "استان آذربایجان شرقی"

عنوان مقاله [English]

The Study of counties of East Azarbaijan Province in in terms of Infrastructure Indicators by Gray Relationship Analysis (GRA)

نویسندگان [English]

fatemeh taherpoor¹؛ Mousa Vaezi²؛ Habil Khorami³؛ Majid Akbari⁴

¹M.Sc. Geography and Urban Planning, Mohaghegh Ardabili University, Ardabil, Iran

²PhD student in Geography and Urban Planning, University of Tabriz, Tabriz, Iran

³Graduate in Geography and Planning, University of Tabriz, Tabriz, Iran

⁴PhD student in Geography and Urban Planning, Payame Noor University of Tehran, Tehran, Iran

چکیده [English]

     Today, having to achieve a balanced and respect the balance and equality in all aspects of development indices, the Especially at the regional level in developing countries, and especially our country achieve one of the main challenges According to the principles of sustainable development defined for it. The purpose of this study was to evaluate and Prioritize the East Azerbaijan province in terms of infrastructure indicators is. The present study is of applied type and descriptive-analytical in nature. For this purpose, 20 counties In terms of infrastructure indicators into 46 quantifiable indicators were studied. To analyze the data, the model Generalized Shannon entropy, gray relational analysis (GRA), in the form of Pearson correlation coefficient using SPSS Used. The results indicate that: (1) based on the analysis of data in the relational model gray, Counties nomads, Varzeghan, Charavimaq, Khoda Afarin and Julfa in terms of infrastructure With the mean coefficient of priority (0.749), in very poor condition. The first priority is planning to expand to the counties. 2. Based on the coefficient Pearson (0/512), correlation between the facilities and infrastructure, infrastructure and population in cities positive relationship there is.On the other hand between the index and the growth rates of urbanization Infrastructure Province of relationship and there is a positive correlation. So in general, it can be concluded that facilities in the province the underlying infrastructure has led to the counties that have more population, but between the Enjoyment of the underlying index and no significant relationship urbanization rate of counties.
Extended Abstract
Introduction:
    Today, balancing and maintaining equilibrium and equity in achieving development indicators in all its dimensions, especially at the regional level in developing countries and especially in our country, is one of the main challenges of achieving sustainable development in accordance with the principles defined for it is. In this regard, the necessity of this research arises from the fact that one of the most important goals of spatial planning is due to resource constraints; optimal and balanced distribution of facilities and services between different settlements. To do this, it is necessary to identify the settlements in terms of infrastructure indicators, so that underserved and undeveloped areas are identified so that planners can act to balance spatiality and reduce productivity gaps between regions. In this regard, the purpose of this study is to evaluate and prioritize East Azarbaijan cities in terms of infrastructure indices using gray relation analysis technique.
Methodology:
    This study was a descriptive-analytic one in terms of targeting as an applied study. The geographical territory of this study is 20 cities of East Azarbaijan province based on political-administrative divisions in 2011. The data gathering tool for the spatial distribution of the underlying indices is 4 criteria and 46 indices. Quantitative models such as generalized Shannon entropy model, gray relational analysis, Pearson correlation coefficient and Arc Gis, Excel and SPSS were used for data analysis.
Results and discussion:
    Step One: Creating a Gray Relationship (Decision Matrix): In this study, gray relationship analysis was used to determine the priority of cities based on the underlying indices and weights of each of these ratios. Therefore, in the first step of this study, for evaluation and prioritization of cities, the weight of 46 indicators used in this study was measured using Shannon entropy method. Step Two: Impact of Gray Relationship Coefficient: Using the gray relation coefficient, the proximity of each xij to xoj is measured. The larger the coefficient of the gray relation, the greater the proximity. Step 3: Gray Relationship Rank: The main goal in the gray relationship creation phase is to convert the original data into a comparable sequence. In order to better understand the situation and prioritize regional development, the cities of East Azarbaijan province were categorized according to 46 selected research indicators in terms of infrastructural indicators, in five levels of deprived, deprived, developing, developed and highly developed.Group 1: Highly deprived cities: Based on prioritization and ranking, among the 20 cities studied, 5 (25%) were included in this group. The cities of Kleiber, Varzaghan, Charavimag, Khodafarin and Jolfa are in critical condition in terms of indicators used.  Group 2: Excluded cities: Hashtrood, Osco, Harris and Ajabshir cities with average priority coefficient of 0.710 were included in this group.  Group3: Developing cities: Middle cities, Azarshahr, Ahar, Shabestar, Bonab, Sarab, Malkan and Bostanabad with average priority coefficient of 0.661. And the third priority is planning for development. Group 4: Extended cities: In this group two cities of Maragheh and Marand with average priority coefficient of 0.607. And so Maragheh and Marand are the fourth level of development priority. Group 5: Highly developed cities: Tabriz city as the center of the province is at a level of development. Therefore, Tabriz city has the fifth level of development priority. Due to the inequalities of development in East Azarbaijan province, according to the indicators, it can be mentioned that Tabriz as the province's center and the growth pole in the northwestern part of the country has the concentration of services, facilities and infrastructure and considering the population concentration which is high. 45% of the population of East Azarbaijan province is occupied and the advance of capitalist relations with the attraction of private and public capital and attracting investors' attention expects such level of development not only in infrastructure but in all aspects of development and so on. The reason for the high lineage difference To other cities of the province's development in the first row.
Conclusion:
     The results show that the spatial distribution of the underlying indices using gray relationship analysis model, the provinces are divided into five levels, with 0.25 deprived, 0.2 deprived, 0.4 deprived in 20 East Azarbaijan provinces, respectively. Currently under development, 0.1 are highly developed and 0.5 are highly developed. There are 5 highly deprived cities, 4 deprived cities, 8 developing cities, 2 developed cities and 1 highly developed city. In the meantime, the cities of Kalibar, Varzaqan, Charavimag, Khodafarin and Jolfa were in critical condition and the first priority of development planning should be with these cities. Another result of this study was that the cities that are in good condition in terms of infrastructure indicators (Tabriz, Maragheh, Marand, Bonab, Shabestar, Azarshahr, Malekan, Bostanabad) are located in the western half of the province. Thus, in general, it can be concluded that in East Azarbaijan province facilities and infrastructures are moving towards more populated cities, but there is no significant relationship between the level of infrastructure indicators and urbanization rates of cities. According to the results of the research and prioritization, it can be said that lack of accurate study and planning and unbalanced investments at the province level, makes the provincial cities different and heterogeneous in terms of regional development, which causes more facilities and facilities in several cities, Especially Tabriz city. This can be achieved through careful planning in order to provide balanced and coordinated development and development of the provincial cities, which require regional bottom-up and top-down regional studies. In order to achieve sustainable regional development and eliminate the spatial inequalities mentioned in the research findings throughout the East Azarbaijan province, it is essential that, first, any development program is based on a mutual understanding of the local needs and resources and existing conditions of the city. Secondly, any kind of development activity should result from a combination of bottom-up and top-down planning; thirdly, sustainability will be possible at the provincial level when it relies on the participation of the people.

کلیدواژه‌ها [English]

"development", "spatial distribution", "infrastructure indicators", "East Azerbaijan Province"

مراجع

1-      Azkia, M (2014): Sociology of Rural Development and Underdevelopment of Iran, Information Publication, Fifth Edition, Tehran.

2-      Asayesh, H  (2012): Principles and Methods of Regional Planning, Payam Noor Publications, Third Edition, Tehran.

3-      Asgharpour, M. J (2014): Multi-criteria Decision Making, Tehran, Tehran University Press.

4-      Papoliyzadi, M. H, and Rajabisnajardi, H (2013): Theories of the City and the Periphery, Khome Publications, Fourth Edition.

5-      Tagavi, M and Bahari, I (2012): Leveling and Measuring the Development Level of Mazandaran Provinces Using Factor Analysis and Cluster Analysis, Journal of Geography and Environmental Planning, No. 4, pp. 15-15.

6-      Zali, N and Pourmohammadi, M. R (2010): Analysis of Regional Inequalities and Development Futures (Case Study: East Azarbaijan Province), Summer 2010, Volume 15, Number 32, pp. 64-29.

7-      Zangi­Abadi, A., Bahari, I and Ghaderi, R (2013): Spatial Analysis and Classification of Health Indicators Using GIS (Case Study, East Azarbaijan Provinces), Quarterly Journal Geographical Research, Vol. 28, No. 1, Spring 1993, Serial No. 108, pp. 10-75.

8-      Zangi Abadi, A., Alizadeh, J and Ahmadian, M (2011): An Analysis on the Development Degree of East Azarbaijan Provinces Using AHP and TOPSIS Models, New Attitudes in Human Geography, Volume 4, Issue 1, Winter 2011, p. -131.

9-      Sarvar, R and Khaliji, M (2015): Measuring the Development Level of Kohgiluyeh and Boyerahmad Provinces, Journal of Urban Research and Planning, Vol. 6, No. 21, pp. 102-89.

10-  Shali, M and Razavian M. T (2010): Regional Inequalities in East Azarbaijan Province Using Taxonomy and Clustering, Journal of Geographical Sciences Applied Research, Volume 14, Number 17, Summer 2010, Pp. 40-25.

11-  Shokyi, H (2011): New Views on Urban Geography, Khome Publications, Tehran.

12-  Shahdadi, A & Sajasi­Qidari, H & Mirzadeh­Kouhshahi, M, & Bion, O and Hosseini­Kahnoj, S. R (2019): Measuring the Development Rate of Kerman Provincial Cities Using Integration Technique, Program Quarterly Regional Review, Year 9, No. 33, pp. 72-55.

13-  Safari, R & Bayat, M (2013): Determining the Development Levels of Rural Areas of East Azerbaijan Province Using Factor Analysis and Cluster Analysis, Journal of Applied Research in Geographical Sciences, No. 28, pp. 41-38.

14-  Saeedayi, S &  Olfati Aliabadi, H & Gholami, A and Karami, M (2017): Analysis of Spatial Inequality of Rural Development in Sahneh County, Kermanshah Province, Spatial Planning Quarterly, Seventh Year, No. 2: Pp. 21-38.

15-  Kalantari, K (2013): Regional Planning and Development, Khoshbin Publications, First Edition, Tehran.

16-  Mohammadi, J & Izadi M (2011): Ranking Isfahan's Areas of Cultural Indicators Based on Multi-Index Decision Making, Social Welfare Quarterly, Vol. 12, No. 11, Tehran, pp.198-175.

17-  Mohammadi, A and Molai, N (2010): Application of Gray Multi-criteria Decision Making in Evaluating Corporate Performance, Journal of Industrial Management, Volume 2, Issue 4, Spring and Summer, pp. 142-125.

18-  Mohammadi, A and Noori, S (2018): Measuring the Industrial Development of Ardebil Provinces by Spatial Justice Approach, Human Geography Research, Volume 50, Number 1, pp. 145-162.

19-  Iran Statistical Center, Statistical Yearbook of East Azarbaijan Province, 2011.

20-  Mosalanejad, A (2018): Government and Economic Development in Iran, Fourth Edition, Ney Publishers, Tehran.

21-  Mananraisi, M and Raeesi, I (2015): A Survey on the Development of Shiraz Districts, Journal of Urban Research and Planning, Vol. 6, No. 21, pp. 138-121.

22-  Mirktouli, J and Kanani, M.R (2011): Evaluation of Development Levels and Regional Inequality Using Multi-criteria Decision Making Model, Case Study: Rural Settlements of Mazandaran Province, Journal of Geography and Land Planning, Vol. Second, Winter 2011, pp. 89-36.

23-  Nazemfar, Hossei & Eshghiehcharborj, A and Alavi, S (2019): Measuring Sustainable Development of Iranian Provinces Based on Environmental Planning, Regional Planning Quarterly, Vol. 9, No. 33, Pp. 29-42.

24-  Chuang, Y. C., & Chuang, K. Y, (2008): Gender differences in relationships between social capital and individual smoking and drinking behavior in Taiwan, Social science & medicine, 67(8), 1321-1330.

25-  Erilli, N. A  )2015(: Socioeconomic Development Index RankingCalculations of Cities with Fuzzy Clustering Method: Case of Turkey, Theoretical and Applied Economics, 22(1): 215-226.

26-  Goletsis, Y., & Chletsos, M, (2011): Measurement of development and regional disparities in Greek periphery: A multivariate approach, Socio-Economic Planning Sciences, 45(4), 174-183.

27-  Hák, T. and Janousková, S. and Moldan, B, (2016): Sustainable Development Goals: A need for relevant indicators, Ecological Indicators, 60, 565–573.

28-  Hodder, R, (2000): Development Geography, Routledhe, London.

29-  Hou, J, (2010): Grey relational analysis method for multiple attribute decision making in intuitionistic fuzzy setting. Journal of Convergence Information Technology, 5(10), 194-199.

30-  Lelo, K., Monni, S., & Tomassi, F, (2019): Socio-spatial inequalities and urban transformation. The case of Rome districts, Socio-Economic Planning Sciences.

31-  Malm berg, A, (2000): Agglomeration and firm preformation, Economic of scale, Environmental and   planning, Vol. 22, No.

32-  Malmberg, A, (2000): Agglomeration and firm preformation, Economic of Scale, Environmental and Planning, Vol. 22, No. 2.

33-  Matsumoto, M, (2008): Redistribution and regional development under tax competition, Journal of Urban Economics 64, 480–487.

34-  Pallas, A., & Jennings, J., L, (2012): a Multiplex Theory of Urban Service Distribution: The Case of School Expenditures, Urban Affairs Review, VOL, 48. No, 1. PP, 20-37.

35-  Riddell, R. (2008): Sustainable urban planning: tipping the balance. John Wiley & Sons.

36-  Storper, M and Scott, A. (2006): The Wealth of Regions, Futures, 27, 5.

37-  White, R., Engelen, G., Uljee, I., Lavalle, C., & Ehrlich, D, (2010): Developing an Urban Land Use Simulator for European Cities, Landscape and urban Planning, Vol 30:

38-  Yan, Y., Wang, C., Quan, Y., Wu, G., & Zhao, J, (2018): Urban sustainable development efficiency towards the balance between nature and human well-being: Connotation, measurement, and assessment, Journal of Cleaner Production, 178, 67-75.

39-  Zhang, N.; Wu, D.; Olson, D.L, ( 2005): The method of rey related analysis to multiple attribute decision making problems with interval numbers, Mathematical nd Computer Modeling, 42 (9-10), pp: 991-998.