Year 2015, Volume , Issue 64, Pages 51 - 60 2015-06-09

Complex urban system, understanding urban growth concepts, and urban modeling techniques
Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri

Olgu Aydın [1]

341 2686

Urbanization is a process increasing progressively worldwide. However, with the urbanization process, concerns have been raising regarding environmental, ecological, and social structure. The speed and intensity of urbanization has effects on changing of land use pattern. Therefore, to be able to understand changing processes and predict change rate, density, and changing pathways in urban area, it is crucial to investigate effects causing changes in land-use pattern. Especially, these factors should be determined for the estimation and modelling of future trends of urban land use changes and its ecological impacts. Because of their complexity and interactions, these factors should be analyzed systematically. Urban system has rather complex structure. Rapid developments in modelling techniques thanks to Geographic Information System (GIS), Remote Sensing (RS) and particularly new mathematical methods provide to obtain and analyze of data in various spatio-temporal scales, understand a complex system or a phenomenon, and measure or show the complexity. Urban modelling techniques may allow to measure more realistic measurements of propagation area of a complex urban system/territorial size, the physical development stages and size of each stage. Besides, these techniques will open new horizons on spatial analyses and contribute to make projections determining in spatial development areas.

Keywords: Urbanization, urban growth system, complex urban systems, modeling techniques, urban models.

Kentleşme dünya genelinde çok hızlı gelişen bir süreçtir. Ancak, kentleşme ile birlikte çevresel, ekolojik ve sosyal yapıdaki kaygılar artmaktadır. Kentleşmenin hızı ve yoğunluğu, arazi kullanım paterninin değişmesinde etkilidir. Değişim sürecinin anlaşılması, kent bölgesindeki arazi değişiminin hızı, yoğunluğu ve izlediği yolun tahmin edilmesi için arazi kullanım değişimine neden olan faktörlerin araştırılması önemlidir. Özellikle kent arazi kullanım değişimini ve ekolojik etkilerinin gelecek trendlerini tahmin etme ve modellemede bu faktörlerin belirlenmesi gereklidir. Ancak bu faktörlerin karmaşık olması ve karşılıklı etkileşimi bunların sistematik olarak analiz edilmelerini gerektirmektedir. Kent sistemi oldukça karmaşık bir yapıya sahiptir. Coğrafi Bilgi Sistemleri (CBS), Uzaktan Algılama (UA) ve özellikle de yeni matematiksel yöntemler sayesinde modelleme tekniklerinde meydana gelen hızlı gelişmeler, çeşitli zamansal ve mekânsal ölçeklerde verilerin elde edilip analiz edilmesini, karmaşık sistemin anlaşılmasını, sözü edilen karmaşıklığın ölçülmesi ve gösterilmesini sağlamıştır. Karmaşık bir kent sisteminin yayılım alanı/alansal büyüklüğü, fiziksel gelişim evreleri ve her bir gelişim evresinin büyüklüğü ve büyüme miktarları kentsel modelleme teknikleri sayesinde en gerçek şekilde ölçülebilmektedir. Aynı zamanda, bu yöntemler mekân analizlerini farklı bir boyuta taşıyarak mekânsal büyüme alanlarının belirlenmesine, gelecek öngörülerin oluşturulmasına büyük katkılar sağlamaktadır.

Anahtar Kelimeler: Kentleşme, kentsel büyüme sistemi, karmaşık kent sistemi, modelleme teknikleri, kent modelleri.

  • Alig, R.J. and Healy, R.G. (1987) “Urban and Built-up Land Area Changes in the US: An Empirical Investigation of Determinants”, Land Economics 63(3), 215–226.
  • Allen, P.M. and Sanglier, M. (1981) “Urban Evolution, Self Organization and Decision Making”, Environment and Planning A 13(2), 167-183.
  • Batty, M. and Xie, Y. (1994) “From Cells to Cities”, Environment and Planning B: Planning and Design 21, 531-548.
  • Batty, M., Xie, Y.C. and Sun, Z.L. (1999) “Modeling Urban Dynamics through GIS-Based Cellular Automata”, Computer, Environment and Urban Systems 23, 205- 233.
  • Batty, M. (2007) Model Cities, Centre for Advanced Spatial Analysis Working Paper Series, Paper 113, Şubat 2007.
  • (http://www.casa.ucl.ac.uk/working_papers.htm, 16.07.2010).
  • Bishop, C.M. (1995) Neural Networks for Pattern Recognition, Clarendon Press, Oxford.
  • Benenson, I. and Torrens, P.M. (2004) Geosisimulation: Automata-Based Modeling of Urban Phenomena, John Wiley, London.
  • Berger, T. (2001) Agent-Based Spatial Models Applied to Agriculture: A Simulation Tool for Technology Diffision, Resource Use Changes and Policy Analysis”, Agriculture Economics 25, 245-260.
  • Brown, G. and Robinson, D.T. (2006) “Effects of Heterogeneity in Preferences on an Agent-Based Model of Urban Sprawl”, Ecology and Society 11(1), 46.
  • Cheng, J. and Masser, I. (2003) “Urban Growth Modeling: A Case Study of Wuhan City, PR China”, Landscape and Urban Planning 62, 199-217.
  • Clarke, K.C., Gaydos, L. and Hoppen, S. (1997) “A self- Modifying Cellular Automaton Model of Historical Urbanization in the San Francisco Bay area”, Environment and Planning B: Planning and Design 24, 247-261.
  • Clarke, K.C. and Gaydos, L.J. (1998) “Loose-Coupling a Cellular Automata Model and GIS: Long-Term Urban Growth Prediction for San Francisco and Washington/Baltimore”, International Journal of Geographical Information Science 12(7), 699-714.
  • Couclelis, H. (1997) “From Cellular Automata to Urban Models: New Principles for Model Development and Implementation”, Environment and Planning B: Planning and Design 24, 165-174.
  • Fischer, M.M. and Gopal, S. (1994) “Artificial Neural Networks: A New Approach to Modelling Interregional Telecommunication Flows”, Journal of Regional Science 34, 503-527.
  • Guan, Q., Wang, L. and Clarke, K.C. (2005) “An Artificial- Neural-Network-Based, Constrained CA Model for Simulating Urban Growth”, Cartography and Geographic Information Science 32(4), 369-380.
  • Happe, K. (2004) Agriculture Policies and Form Structures Aged Based Modelling and Application to EU-Policy Reform, Institute of Agricultural Development in Central and Eastern Europe (IAMO), 30.
  • He, C., Okada, N., Zhang, Q., Shi, P. and Li, J. (2008) “Modelling Dynamic Urban Expension Processes Incorporating a Potential Model with Cellular Automata”, Landscape and Urban Planning 86, 79-91.
  • Jacquin, A., Misakova, L. and Gay, M. (2008) “Ahybrid Object-Based Classification Approach for Mapping Urban Sprawl in Periurban Environment”, Landscape and Urban Planning 84(2), 152–165.
  • Krenker, A., Bešter, J. and Kos, A. (2011) “Introduction to the Artificial Neural Networks”, İçinde: Suzuki, K. (Ed). Artificial Neural Networks-Methodological Advances and Biomedical Applications. InTech, Croatia.
  • Lansing, J.S. and Kremer, J.N. (1993) “Emergent Properties of Balinese Water Temple Networks: Coadaptation on a Rugged Fitness Landscape”, American Antropologist 95(1), 97-114.
  • Lopez, E., Bocco, G., Mendoza, M. and Duhau, E. (2001) “Predicting Land Cover and Land Use Change in the Urban Fringe: A Case in Morelia City Mexico”, Landscape and Urban Planning 55(4), 271-285.
  • Maithani, S. (2009) “A Neural Network Based Urban Growth Model of an Indian City”, Journal of the Indian Society of Remote Sensing 37, 363-376.
  • Matthews, R.B., Gilbert, N.G., Roach, A., Polhill, J.G., Gotts, N.M. (2007) “Aged-Based Land-Use Models: A Review of Applications, Landscape Ecology 22, 1447-1459.
  • Openshaw, S. (1993) “Modelling Spatial Interaction Using a Neural Net”, İçinde, GIS, Spatial Modelling and Policy, Springer, Berlin, Germany, 147-164.
  • Pijanowski, B.C., Brown, D.G., Shellito, B.A. and Manik, G.A. (2002) “Using Neural Networks and GIS to Forecast Land Use Changes: A Land Transformation Model”, Computers, Environment and Urban Systems 26(6), 553–575.
  • Pijanowski, B.C., Pithadia, S., Shellito, B.A. and Alexandridis, K. (2005) “Calibrating a Neural Network- Based Urban Change Model for Two Metropolitan Areas of the Upper Midwest of the United States”, International Journal of Geographical Information Science 19, 197–215.
  • Pyle, D. (1999) Preparation for Data Mining, Morgan Kaufmann Publishers, San Francisco, CA.
  • Tobler, W.R. (1970) “Computer Movie Simulating Urban Growth in the Detroit Region”, Economic Geography 46, 234-240.
  • Ward, D.P., Murray, A.T. and Phinn, S.R. (2000) “A Stochastically Constrained Cellular Model of Urban Growth”, Computers, Environment and Urban Systems 24, 539-558.
  • White, R. and Engelen, G. (1993) “Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns”, Environment and Planning A 25, 1175-1199.
  • White, R. and Engelen, G. (1994) “Cellular Dynamics and GIS: Modelling Spatial Complexity”, Geographical Systems 1, 237-253.
  • White, R., Engelen, G. and Uijee, I. (1997) “The Use of Constrained Cellular Automata for High-Resolution Modelling of Urban Land-Use Dynamics”, Environment and Planning B: Planning and Design 24, 323-343.
  • Wolfram, S. (1984) “Cellular Automata as Models of Complexity”, Nature 311, 419-424.
  • Wolfram, S. (1988) Complex Systems Theory, Emerging Syntheses in Science: Proceedings of the Foundaing Workshops of the santa Fe Institute, Adisson-Wesley, Reading, MA.
  • Wu, F. and Webster, C.J. (1998) “Simulation of Land Development through the Integration of Cellular Automata and Multicriteria Evaluation”, Environment and Planning B: Planning and Design 25, 103-126.
  • Wu, F. and Yeh, A.G.O. (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.
  • Wu, F. (1998) “An Experiment on the Generic Polycentricity of Urban Growth in a Cellular Automatic City”, Environment and Planning B: Planning and Design 25, 103-126.
  • Wu, F. (2005) Introduction-Urban Simulation. İçinde: Atkinson, P.M., Foody, Giles, M., Darby, Steve, E., Wu, F. (Eds). GeoDynamics. CRC Press, Boca Raton, FL.
  • Yeh, A.G.O. and Li, X. (2001) “A Constrained CA Model for the Simulation and Planning of Suitainable Urban Forms Using GIS”, Environment and Planning B: Planning and Design 28, 733-753.
  • Yeh, A.G. and Li, X. (2003) “Simulation of Development Alternatives Using Neural Networks, Cellular Automata, and GIS for Urban Planning”, Photogrammetric Engineering and Remote Sensing 69, 1043–1052.
  • Zhang, L. and Yu, Z. (2006) “An Artificial Neural Network Model of the Landscape Pattern in Shanghai Metropolitan Region, China”, Frontiers of Biology in China 1(4), 463-469.
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Author: Olgu Aydın

Bibtex @ { tcd228387, journal = {Türk Coğrafya Dergisi}, issn = {1302-5856}, eissn = {1308-9773}, address = {Turkish Geographical Society}, year = {2015}, volume = {}, pages = {51 - 60}, doi = {10.17211/tcd.69978}, title = {Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri}, key = {cite}, author = {Aydın, Olgu} }
APA Aydın, O . (2015). Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri. Türk Coğrafya Dergisi, (64), 51-60. Retrieved from http://dergipark.org.tr/tcd/issue/21271/228387
MLA Aydın, O . "Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri". Türk Coğrafya Dergisi (2015): 51-60 <http://dergipark.org.tr/tcd/issue/21271/228387>
Chicago Aydın, O . "Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri". Türk Coğrafya Dergisi (2015): 51-60
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EndNote %0 Turkish Geographical Review Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri %A Olgu Aydın %T Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri %D 2015 %J Türk Coğrafya Dergisi %P 1302-5856-1308-9773 %V %N 64 %R %U
ISNAD Aydın, Olgu . "Karmaşık kent sistemi, kentsel büyüme kavramlarının anlaşılması ve kent modelleme teknikleri". Türk Coğrafya Dergisi / 64 (June 2015): 51-60.