Abstract
In planning practice, planners and policy makers frequently investigate urban forms, particularly urban growth boundaries (UGBs), using scenario analyses (SA) by regarding development policies as scenario conditions in urban simulations (i.e., Klosterman 1999; Landis 1994, 1995). Couclelis (2005), however, argued that routine land-use modeling has done little in the way of future-oriented research such as investigations of desirable or feared future conditions. This chapter uses planning alternatives, specifically UGBs, as scenarios to identify necessary spatial policies for planners. This is the inverse procedure of traditional urban growth SA. We propose the concept of “form scenario analysis” (FSA), which we employ to investigate relationships between planning alternatives and corresponding spatial policies. This chapter explains an FSA approach using constrained cellular automata (CA), a tool for matching planning alternatives with necessary spatial policies. We look in particular at form scenarios in order to present the institutional implications of different spatial land-use policy options. This novel exploration of FSA can identify necessary policies as well as policy variations required for different planning alternatives. This differs from traditional applications of constrained CA.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Beijing Municipal Planning Commission, Beijing Institute of City Planning, and Beijing Academy of Urban Planning. Beijing City Planning Atlas (1949–2005), 2006. [in Chinese]
Beijing Municipal Planning Commission. Ecologically Limited Land-use Planning in Beijing (2006–2020), Unpublished report, 2007. [in Chinese]
Beijing Planning Commission, (1988) Beijing Land Resource. Beijing: Beijing SciTech Press, [in Chinese]
Beijing Statistical Yearbook. (1987) Beijing Statistics Press, Beijing.
Beijing Statistical Yearbook. (2007) Beijing Statistics Press, Beijing.
Clark KC, and Gaydos L.J (1998), Loose-coupling a cellular automation model and GIS: Long-term urban growth prediction For San Francisco and Washington/Baltimore DOI:dx.doi.org. International Journal of Geographical Information Science, 12(7): 699–714.
Cohen, J. (1960) A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20: 37–46.
Congalton RG, and Mead R.A., (1983) A quantitative method to test for consistency and correctness in photo interpretation, Photogrammetric Engineering and Remote Sensing, 49(1): 69–74.
Couclelis, H. (2005) “Where has the future gone?” Rethinking the role of integrated land-use models in spatial planning, Environment and Planning A, Vol. 37, No. 8, 1353–1371.
Engelen, G., White, R., and Uljee, I., (1997) Integrating constrained cellular automata models, GIS and decision support tools for urban and regional planning and policy making. Timmermans, H. (ed): Decision Support Systems in Urban Planning, London: E&FN Spon. pp. 125–155.
Guan G, Wang, L., and Clark, K.C. (2005), An artificial-neural-network-based, constrained CA model for simulating urban growth. Cartography and Geographic Information Science, 32(4): 369–380.
Han, H., Lai, S., Dang, A., Tan, Z., and Wu, C., (2009) Effectiveness of urban construction boundaries in Beijing: An assessment DOI:dx.doi.org. Journal of Zhejiang University SCIENCE A, 10(9): 1285–1295.
Klosterman, R.E. (1999) The What if? Collaborative planning support system, Environment and Planning B: Planning and Design, Vol. 26, No. 3, 393–408.
Landis, J.D. (1994) The California Urban Future model: A new generation of metropolitan simulation models, Environment and Planning B: Planning and Design, Vol. 21, No. 4, 399–420.
Landis, J.D. (1995) Imaging land use futures: Applying the California Urban Future model, Journal of American Planning Association, Vol. 61, No. 4, 438–457.
Landis, J.D., and Zhang, M. (1998a) The second generation of the California Urban Future model, Part1: Model logic and theory, Environment and Planning B: Planning and Design, Vol. 25, No. 5, 657–666.
Landis, J.D., and Zhang, M. (1998b) The second generation of the California Urban Future model, Part2: Specification and calibration results of the land-use change submodel, Environment and Planning B: Planning and Design, Vol. 25, No. 6, 795–824.
Li, X., Yang, Q., and Liu, X. (2008) Discovering and evaluating urban signatures for simulating compact development using cellular automata, Landscape and Urban Planning Vol. 86, 177–186.
Li, X., and Yeh, A. G. O. (2000) Modeling sustainable urban development by the integration of constrained cellular automata and GIS DOI:dx.doi.org. International Journal @@of Geographical Information Science, 14(2): 131–152.
Li, X., and Yeh, A.G.O. (2002) Neural-network-based cellular automata for simulating multiple land use changes using GIS, International Journal of Geographical Information Science, Vol. 16, No. 4, 323–343.
Ligtenberg, A., Bregt, A.K. (2001) Multi-actor-based land use modelling: Spatial planning using agents, Landscape and Urban Planning, Vol. 56, No. 1–2, 21–33.
Liu, X., Wang, J., Liu, M., and Meng, B. (2005) Spatial heterogeneity of the driving forces of cropland change in China, Science in China Series D-Earth Sciences, Vol. 48, 2231–2240.
Long, Y., He, Y., Liu, X., and Du, L. (2006) Planning of the controlled-construction area in Beijing: Establishing urban expansion boundary (in Chinese), City Planning Review, Vol. 30, No.12, 20–26.
Long, Y., Shen, Z., Du, L., Mao, Q., and Gao, Z., (2008) BUDEM: An urban growth simulation model using CA for Beijing Metropolitan Area DOI:dx.doi.org. Proc. SPIE, Vol. 7143, 71431D.
Nelson, A. C., and Duncan, J. B., (1995) Growth Management Principles and Practices. Chicago, IL; Washington D.C.: Planners Press; American Planning Association.
Pendall, R., Martin, J., and Fulton, W., (2002), Holding the Line: Urban Containment in the United States. Washington, D C: The Brookings Institution Center on Urban and Metropolitan Policy.
Saarloos, D., Arentze, T., Borgers, A., and Timmermans, H. (2005) A multiagent model for alternative plan generation, Environment and Planning B: Planning and Design, Vol. 32, 505–522.
Spear, R.C., Grieb, T.M., and Shang, N. (1994) Parameter uncertainty and interaction in complex environment models, Water Resources Research, Vol. 30, No. 11, 3159–3169.
Tian, L., Lv, C., and Shen, T., (2008) Theoretical and empirical research on implementation evaluation of city master plan: A case of Guangzhou City Master Plan (2001–2010), Urban Planning Forum, (5): 90–96. [in Chinese]
Tobler, W. R. (1970) A computer movie simulating population growth in the Detroit region. Economic Geography, 42: 234–240.
Ward, D. P., Murray, A. T., and Phinn, S. R. (1999) An optimized cellular automata approach for sustainable urban development in rapidly urbanizing regions. GeoComputation99, 4th International Conference on GeoComputation, Virgina, USA.
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(6): 539–558.
White, R. W., and Engelen, G. (1993) Cellular automata and fractal urban form: A cellular modeling approach to the evolution of urban land use patterns DOI:dx.doi.org. Environment and Planning A, 25(8), 1175–1193.
White, R. W., and Engelen, G. (1997) Cellular automaton as the basis of integrated dynamic regional modeling Environment and Planning B: Planning and Design, 24(2), 235–246.
White, R., Straatman B., and Engelen, G. (2004), Planning scenario visualization and assessment - A cellular automata based integrated spatial decision support system. In: Goodchild, M.F., Janelle, D.G., Shrore, Z.G. (Eds.), Spatially Integrated Social Science, Oxford University Press. 420–442.
Wu, F. (1998), Simland: A prototype to simulate land conversion through the integrated GIS and CA with AHP-derived transition rules. International Journal of Geographical Information Science, 12(1): 63–82.
Wu, F. (2002) Calibration of stochastic cellular automata: The application to rural-urban land conversions, International journal of Geographical Information Science, Vol. 16, No. 8, 795–818.
Xie, Y. (1994) Analytical Models and Algorithms for Cellular Urban Dynamics. Unpublished Ph.D. dissertation, State University of New York at Buffalo, Buffalo, N.Y.
Xu, Y., Shi, S., and Fan, Y., (1992) Methodology of Shanghai City Master Plan in new position, Urban Planning Forum, 2009, (2). [in Chinese]
Acknowledgments
We would like to thank the National Natural Science Foundation of China (No. 51078213), the Grants-in-Aid for Scientific Research (No. 23404022B), Japan Society of the Promotion of Science for the financial support.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2012 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Long, Y., Shen, Z., Mao, Q., Du, L. (2012). A Challenge to Configure Form Scenarios for Urban Growth Simulations Reflecting the Institutional Implications of Land-Use Policy. In: Geospatial Techniques in Urban Planning. Advances in Geographic Information Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-13559-0_1
Download citation
DOI: https://doi.org/10.1007/978-3-642-13559-0_1
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-13558-3
Online ISBN: 978-3-642-13559-0
eBook Packages: Earth and Environmental ScienceEarth and Environmental Science (R0)