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  • سنجش میزان بهره‌مندی شهرستان‌های استان گلستان با تاکید بر توسعه یافتگی روستاها با استفاده از روش آنتروپی و تاپسیس

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کد مقاله : 13778 بازدید : 60 صفحه: 123 - 137

10.30495/jest.2018.13778

نوع مقاله: پژوهشی

سنجش میزان بهره‌مندی شهرستان‌های استان گلستان با تاکید بر توسعه یافتگی روستاها با استفاده از روش آنتروپی و تاپسیس

محورهای موضوعی : مدیریت محیط زیست

سحر سعیدی 1 (دانشجوی کارشناس ارشد محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان* (مسوول مکاتبات))
عبدالرسول سلمان ماهینی 2 (دانشیار گروه محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان)
سپیده سعیدی 3 (دانشجوی دکتری محیط زیست، دانشگاه علوم کشاورزی و منابع طبیعی گرگان)

تاریخ دریافت : 1394/10/23 تاریخ پذیرش : 1395/08/26 تاریخ انتشار : 1398/01/01

کلید واژه: آنتروپی, تاپسیس, تحلیل حساسیت, استان گلستان, ارزیابی سطح توسعه اقتصادی – اج,

چکیده مقاله :

چکیده زمینه و هدف: سطح زندگی انسان با رشد و پیشرفت علم و دانش بشری همواره در حال پیشرفت بوده است. با این حال، این رشد و توسعه در تمام مناطق و سکونتگاه‌های انسانی یکسان نبوده و در نتیجه آن جوامع مختلفی با سطح توسعه اجتماعی اقتصادی متفاوت ایجاد شده است. بنابراین استفاده از علم برنامه‌ریزی ناحیه‌ای درکاهش این نابرابری ضروری به نظر می‌رسد. هدف از انجام تحقیق حاضر، ارزیابی و سطح‌بندی توسعه اقتصادی اجتماعی شهرستان‌های استان گلستان با تاکید بر میزان توسعه‌یافتگی روستاهای این شهرستان است.روش بررسی: برای این منظور از روش آنتروپی و تاپسیس برای وزن‌دهی به معیارها و اولویت بندی شهرستان‌ها استفاده شد. تعداد 12 معیار در چهار دسته کلی شامل جمعیت، حمل و نقل، امکانات رفاهی و بهداشت و درمان جهت سنجش میزان بهره مندی شهرستان‌ها انتخاب شدند.یافته‌ها: بر اساس نتایج بدست آمده شهرستان گنبد با ضریب بهره مندی 92/0 رتبه اول و شهرستان بندر گز با ضریب بهره مندی 12/0 رتبه یازدهم را بدست آورد. پس از تعمیم ضرایب، شهرستان‌ها از نظر میزان بهره‌مندی در چهار طبقه زیاد، متوسط، کم و بسیار کم قرار گرفتند. در انتها برای اطمینان از اولویت هر یک از شهرستان‌ها، تحلیل حساسیت با هفت تکرارانجام شد.نتیجه‌گیری: نتایج این تحقیق می‌تواند به عنوان الگویی برای برنامه‌ریزی رشد و توسعه‌ی روستاهای شهرستان‌های استان مورد استفاد قرار گیرند.

چکیده انگلیسی:

  Background and Objective: The level of human life has always been in progress with the development of science and human knowledge, but this growth has not been uniform in all areas and consequently different communities with different socio - economic development levels have been created. Using regional planning seems to be a necessity to reduce these inequalities. The goal of the present research is to assess and rank the socio – economic rural development level of Golestan Province townships. Method: Entropy and TOPSIS methods were used to weight the criteria and prioritize the cities. Tweleve criteria in four main categories including population, transportation, welfare and healthcare were selected to measure the socio – economic rural development levels. Findings: The results showed that Gonbad Kavoos has the first rank with a coefficient of 0.92 and Bandar gaz has last rank with a coefficient of 0.12. After calculating the development rates, townships were divided into one of the high, medium, low and very low classes. Finally, sensitivity analysis with seven repetitions was implemented to ensure the consistency of the results. Discussion and Counclusion: The results of this research can be used as a model to design proper growth and development plans for Golestan Province townships.

منابع و مأخذ:



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_||_


  1. Salimifar, M. (2003). Economy and development. Movahed Publications, 215 pp. (In Persian)
    2.
  2. Khakpour, B. (2006). Assessing the development level of Shirvan’s villages in order to regional planning, Geography and regional developments, Number 7, 133-145. (In Persian)
    3.
  3. Taghvaei, M. and Bay, N. (2012). Assessing Impart Quantity of counties of Golestan province by Analytical Hierarchy Process. Geographical research, volume 27, Number 3, 1-20. (In Persian)
    4.
  4. Marsoosi, N. and Bahrami, R. (2011). Urban sustainable development. Tehran university of Payamenoor, 156 pp. (In Persian)
    5.
  5. Zali, N. (2000). Zonning the regional development in East Azarbayjan province. Master thesis, Shiraz university. (In Persian)
    6.
  6. Feyzizadeh, B., and Rezaei, M., Hejazi, M. (2012). Categorizing of economical level of Western Azarbayjan townships using spatial analysis and decision rules. Geographical space, Volume 12, Number 40, 1-25. (In Persian)
    7.
  7. Ghadiri, M., and Habibi, K. (2004). Measuring and analyzing the uraban development of Golestan province townships. Social sciences, Nunmber 23, 140-170. (In Persian)
    8.
  8. Hosseinzadeh, D. (2005). Regional planning. 4 th publication of Samt, 362 pp. (In Persian)
    9.
  9. Dong.C, Liu.J, and Song, Q. (2009), “Reserch on regional economical level of Ancang river basin based on grey cluster and GIS”, Chinese Academy of Surveying and Mapping, 16 Beitaiping Road, Beijing, China. 100039.
    10.
  10. Huby.M, Owen. A and Cinderby.S, (2007), “Reconciling socio- economic and environmental data in a GIS context: An example from rural England”, Applied Geography, Number 10, 1-10.
    11.
  11. Bell. N, Schuurman, N and Hayes. M, (2007), “Using GIS-based methods of multicriteria analysis to construct socio-economic deprivation indices”, International Journal of Health Geographics,Volume 17, Number 6, 6- 17.
    12.
  12. Ma.S, Feng. J and Cao.H, (2006), “Fuzzy Model of Regional Economic Competitiveness in GIS Spatial Analysis: Case Study of Gansu, Western China”. Applied Mathematical Modelling, Volume 5, Number 2, 99- 111.
    13.
  13. Ebrahimzadeh, I., Eskandari, S., Esmaeilnejad, M. (2010). Using factor analysis in determining spatial pattern of urban and regional development and non- development of Iran. Geography and development, Number 28, 7-17. (In Persian)
    14.
  14. Noormohammadi, Y. (2008). Statistical yearbook of 2007. Deputy Director of Planning in Golestan Province, Reyhani Publications, 312 pp. (In Persian)
    15.
  15. Butorab, S. (2006). Atlas of geotourism in Golestan province, National Geoscience Database of Iran. (In Persian)
    16.
  16. Roghanian, E., Rahimi, J., and Ansari, A. (2010). Comparison of first aggregation and last aggregation in fuzzy group TOPSIS. Applied Mathematical Modelling, Volume 34, Number 12, 3754-3766.
    17.
  17. Krohling, R. A., and Campanharo, V. C. (2011). Fuzzy TOPSIS for group decision making: A case study for accidents with oil spill in the sea. Expert Systems with Applications, Volume 38, Number 4, 4190-4197.
    18.
  18. Nahaei, V., Akbari, K., Shahmoradi, H., Rassoulamini, P. (2012). Selection of the best transmission path from Urumieh Power Plant to Balanj Post with the MADM Approach, 9th International Industrial Engineering Conference, 1st and 2nd of February 2012. (In Persian)
    19.
  19. Asgharpour, M.J. (2004). Multi- objective decision making. Tehran university Publication.
    20.
  20.  Sharifi, R., Mirabadi, A., Arfa, E. (2012). Investigation and selection of suitable signaling system by Entropy-Promethe method for Chabahar railway - Zahedan, Transportation Engineering, Second year, Number 4, 346-335. (In Persian)
    21.


 

 

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