تحلیل عوامل موثر بر الگوی رشد کالبدی شهرهای بزرگ ایران نمونه مطالعه: الگوی رشد کالبدی شهر رشت

نویسندگان

1 دانشیار دانشکده هنرو معماری، دانشگاه آزاد اسلامی واحد علوم و تحقیقات

2 استاد دانشکده شهرسازی، پردیس هنرهای زیبا، دانشگاه تهران

3 دانشجوی دکتری شهرسازی، دانشکده هنرو معماری، دانشگاه آزاد اسلامی واحد علوم و تحقیقات

چکیده

رشد شهری و عوامل محرک آن موضوعات مهمی در تحلیل مطالعات شهری کنونی به شمار می رود. هدف این مقاله، شناخت عوامل موثر بر رشد شهری، کمّی کردن وابستگی بین رشد و عوامل محرک آن و تحلیل الگوی رشد بر اساس تغییرات کاربری زمین تاریخی برای شهر رشت می باشد، با این فرض که رشد شهر رشت تحت تاثیر عوامل محرک خاص و الگوهای مشخص محلی است. در این راستا، با مروری بر مفاهیم نظری مرتبط با عوامل موثر بر رشد شهری، سنجه های کمّی برای رشد شهری تدوین شد، تا به عنوان چارچوب مناسب برای بررسی عوامل موثر بر رشد شهر رشت مورد استفاده قرار گیرد. سپس با رویکرد نمونه سازی لاجیستیک رگرسیون دو دسته از عوامل موثر بر رشد شهر رشت معرفی گردید: 1) عوامل با تاثیر مثبت بر رشد شهری: شیب (بر حسب درصد)، فاصله از نزدیک‌ترین محل تجاری، وجود زمین-های کشاورزی و بایر و مناطق دارای تراکم جمعیتی کم 2) عوامل با تاثیر منفی بر رشد شهری: فاصله از راه‌های اصلی و بین شهری، فاصله از مناطق مسکونی، فاصله از مراکز صنعتی، وجود مناطق دارای پوشش جنگلی و مناطق با قیمت زمین بالا.

کلیدواژه‌ها


عنوان مقاله [English]

The Analysis of Factors Influencing Physical Urban Growth Pattern for Large Cities of Iran

نویسندگان [English]

  • Hamid Majedi 1
  • Esfandiar Zebardast 2
  • Bahare Mojarrabi Kermani 3
1
2
3
چکیده [English]

The hastening increase in the population of the cities ,lack of urban infrastructures ,shifting the land use and the consequent vanish of ecologically valuable lands in the countries ,industrial pollutions ,illegal settlement in the suburbs and other human activities which have influenced the growth of cities in Iran too ,make it necessary to study and analyze the growth of Rasht(The capital of the Gilan Province in the vicinity of Caspian sea which is one of the large cities in Iran) Urban growth and its driving factors are important topics in recent urban research analysis. Several physical, economical and social factors influence the urban growth while they have nonlinear and complex relation. The goal of this study is to define and recognize the urban growth system, affecting factors on urban growth, quantize the relation between the urban growth and the driving factors and analyze the spatial growth patterns according to historical land use change for the city of Rasht, assuming that some special driving factors and local patterns which are consistent with geographic, economic, physical and social structure of the city, have influenced its growth. Since the factors of urban growth are unique for a given case and past studies were not concentrated on comparative analysis of urban growth, the present research focuses on determining the most important factors affecting city growth through modeling and compare the common and divers points of urban growth in Rasht with other studies. For this purpose, by reviewing the theoretical concepts associated with urban growth, quantative and measurable criteria are developed as proper frameworks to study the influencing factors on the city growth. This paper describes the urban growth model through “logistic regression” which based on the theories of urban growth, contributes to determination of growth mechanisms at different time phases and recognition of driving factors and introduces two series of influencing factors on Rasht urban growth: 1) factors with favorable effects including: slope(%), distance from nearest markets, farm lands and less populated areas. 2) factors with unfavorable effects including: distance from main roads, residential areas and industrial centers, lands covered with trees (forest) and areas with expensive lands. Finally it was found that the specifications of physical growth pattern of Rasht depended not only on the existing situation of the pattern, but on the factors influencing it as well. The most important driving factor of Rasht urban growth is its “Roads” which could be most observed in the south along the Rasht-Tehran road toward the industrial town. It shows that the mutual effect pattern of land use _ transportation will play an important role in the future planning of the city. Also unlike the forests, farm lands are progressively changing into town lands that should be prevented through feasible and practicable planning and investigating the political and managing factors. The results of this research could be suitable means to analyze and compare pattern and factors influencing on urban growth of Rasht with other large cities of Iran to be utilized by urban planners and managers .

کلیدواژه‌ها [English]

  • Growth' Driving Factors
  • Rasht
  • Spatial modeling
  • urban growth
ایران آمایش، مهندسین مشاور (1369)، طرح جامع (توسعه و عمران، حوزه نفوذ ) و تفصیلی رشت (مرحله اول)، اداره کل مسکن و شهرسازی استان گیلان، وزارت مسکن و شهرسازی.
طرح و کاوش، مهندسین مشاور با همکاری مهندسین مشاور پارسوماش(1384)، طرح جامع شهررشت، تهران، وزارت مسکن و شهرسازی.
Barredo, J. I., Kasanko, M., McCormick, N., & Lavalle, C. (2003), Modelling dynamic spatial processes: Simulation of urban future scenarios through cellular automata, Landscape and Urban Planning, 64(3), 145–160.
Batisani, N; Yarnal , B.(2009), Urban expansion in Centre County, Pennsylvania: Spatial dynamics and landscape transformations, Applied Geography,29(235-249).
Braimoh, A, K; Onishi, T.(2006), Spatial determinants of urban land use change in Lagos, Nigeria, AMS online journals, 8( 21).
Cheng, J., & Masser, I. (2003), Urban growth pattern modeling: a case study of Wuhan city, PR China, Landscape and Urban Planning, 62,. 199-217.
Cetin.M, Demirel.H (2010), Modelling and Simulation of Urban Dynamics, Fresenius Environmental Bulletin, Vol. 9, No. 10A.
Cheng,J.(2003), Modelling Spatial & Temporal Urban Growth, Doctoral Dissertation, Faculty of Geographical Sciences, Utrecht University.
Clarke K C, Hoppen S, Gaydos L, (1997), A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area, Environment and Planning B: Planning and Design, 24(2), 247 – 261.
Dubovyk, O.(2010), Spatio-temporal analysis of ISs development, A case study of Istanbul, Turkey, MSc thesis, Faculty of Geo-information science and earth observation, ITC.
Fang, S., Gertner, G. Z., Sun, Z., & Anderson, A. (2005), The impact of interactions in spatial simulation of the dynamics of urban sprawl, Landscape and urban planning.
Hagoort, M.J., Geertman, S.C.M. & Ottens, H.F.L. (2008), Spatial externalities, neighbourhood rules and CA land-use modeling, The annals of regional science,42,39–56.
Hu, Z., and Lo, C. P., (2007), Modeling urban growth in Atlanta using logistic regression, Computers, Environment and Urban Systems, 31-6. 6.
Huang, B; Zhang, L; and Wu, B.(2009), Spatiotemporal analysis of rural-urban land coversion, international journal of Geographic Information Science, 23(3),379-398.
Irwin, E. G., & Geoghegan, J. (2001), Theory, data, methods: Developing spatially explicit economic models of land use change, Agriculture, Ecosystems and Environment, 85(1–3), 7–24.
Landis, J. H; Zhang, M.(2000), Using GIS to Improve Urban Activity and Forecasting, Models: Three Examples, chapter five in: A, Fotheringham and Michael Wegener eds, Spatial Models and GIS: New Potential and New Models, 63-81. Taylor and Francis, London, UK.
Luo, J; Wei, Y, H,Y.(2009), Modeling spatial variations of urban growth patterns in Chinese cities: The case of Nanjing, Landscape and Urban Planning. 91(2), 51-64.
Poelmans, L., VanRompaey, A. ( 2009), “Complexity and performance of urban expansion models”. Computers, Environment and Urban Systems, 34 (1), 17-27.
Shamsuddin, s ; Yaakup, A. (2007), Predicting and simulating Future Land Use Pattern: A Case Study of Seremban District. Jurnal Alam Bina, 9(1).
Shen Ti-yan, Wang Wei-dong, H O U Min, G U O Zhao-cheng, X U E Ling, Yang Kai-zhong (2008), Study on Spatio-Temporal System Dynamic Models of Urban Growth, System Engineering Theories and Practices, 27(1),10-17.
Sietchiping, R.(2005), Prospective slum policies: Conceptualization and implementation of a proposed informal settlement growth model, Available at:http://www.worldbank.org/urban/symposium 2005/papers.
Sliuzas, R. V. (2004), Managing Informal Settlements, a study using geo-information in Dar es Salaam, Tanzania. ITC Publication Series, 112.
United nations(2011), World urbanization prospects: The 2011 revision.
Verburg P H; Ritsema Van Eck, J, R; de Nijs T C M; Dijst M J; Schot P,( 2004), Determinants of land-use change patterns in the Netherlands, Environment and Planning B: Planning and Design 31(1) 125 – 150.
verburg, P,H; Ritsema van Eck ,J,R; de Nijs T, C, M. ; Hans Visser, Kor de Jong(2004), A method to analyse neighbourhood characteristics of land use patterns, Computers, Environment and Urban Systems, 28(6), 667-690.
White, R. and Engelen, G. (2000), High-resolution integrated modeling of the spatial dynamics of urban and regional systems, Computers, Environment and urban systems,24(5),383-400.
Wu, F. and Yeh, A. G. (1997), Changing spatial distribution and determinants of land development in Chinese cities in the transition from a centrally planned economy to a Socialist Market Economy: A Case Study of Guangzhou, Urban Studies, 34(11),1851-1879.
Xie, C; Huang B; Claramunt C; Chandramouli ,C. (2009), Spatial logistic Regression and GIS to Model Rural-Urban Land Conversion, international journal of Geographic Information Science, 23(3).
Yin, Z,Y; Stewart, D,J; Bullard, S and MacLachlan , J, T(2005), Changes in urban built-up surface and population distribution patterns during 1986–1999: a case study of Cairo, Egypt” Computers, Environment and Urban Systems 29 (5), 595–616.