Cellular Automata Calibration Model to Capture Urban Growth

Uttam Kumar1,4,5, Chiranjit Mukhopadhyay4, T.V. Ramachandra1,2,3*

1Energy & Wetlends Research Group, Center for Ecological Sciences [CES], Indian Institute of Science,
2Center for Sustainable Technologies (astra), Indian Institute of Science,
3Centre for infrastructure, Sustainable Transportation and Urban Planning [CiSTUP]
4Department of Management Studies
5International Institute of Information Technology, Bangalore-560100, India
*Corresponding author: Energy & Wetlands Research Group, Centre for Ecological Sciences Indian Institute of Science,
Bangalore – 560 012, INDIA, E-mail: cestvr@ces.iisc.ernet.in, energy@ces.iisc.ernet.in.

References

AlKheder, S., Wang, J., and Shan, J., 2006. Change detection -cellular automata method for urban growth model modelling. ISPRS Commission VII Mid-term Symposium “Remote Sensing From Pixels to Processes”, Enschede, the Netherlands, 8-11 May, 2006.

AlKheder, S., Wang, J., and Shan, J., 2007.Cellular automata urban growth model calibration with genetic algorithms.Urban Remote Sensing Joint Event, 11-13 April, 2007, Paris, France, 1-5.

Barredo, J. I., Demicheli, L., Lavalle, C., Kasanko, M., McCormick, N., 2004.Modelling future urban scenarios in developing countries: an application case study in Lagos, Nigeria.Environment and Planning B: Planning and Design, 32, 65-84.

Batty, M., and Xie, Y., 1994.From cells to cities.Environment and Planning, B21, 531-548.

Batty, M, Xie, Y, Sun, Z, 1999. Modelling urban dynamics through GIS-based cellular automata.Computers, Environment and Urban Systems, 23, 205-233.

Batty, M., 2005. Cities and Complexity: Understanding Cities with Cellular Automata, Agent-based Models, and Fractals. The MIT Press, Cambridge, MA.

Bayarsaikhan, U., Boldgiv, B., Kim, K-R., Park, K-A., and Lee, D., 2009. Change detection and classification of land cover at Hustai National Park in Mongolia. International Journal of Applied Earth Observation and Geoinformation, 11, 273-280.

Census of India, 2011. Ministry of Home Affairs, Government of India.
Chen, F, Hu, Y., Peng, X., Wang, Lu., 2010, Simulation of land use/cover change based on the CLUE-S model. In 18th International Conference on Geoinformatics, 1(5), 18-20.

Cheng, J., Masser, I., 2004. Understanding spatial and temporal process of urban growth: cellular automata modelling. Environment and Planning B: Planning and Design, 31, 167-194.

Clarke, K. C., and Gaydos, L. J., 1998.Loose-coupling a cellular automaton model and GIS: long-term urban growth prediction for San Francisco and Washington/Baltimore. International Journal of Geographical Information Sciences, 12, 699-714.

Clarke, K. C., Hoppen, S., and Gaydos, L., 1997.Aselfmodifying cellular automaton model of historical urbanization in the San Francisco Bay area.Environment and planning, 24, 247-261.

Conese, C., and Maselli, F., 1992. Use of error matrices to improve area estimates with maximum likelihood classification procedures. Remote Sensing of Environment, 40, 113-124.

Couclelis, H., 1985. Cellular worlds: a framework for modeling micro–macro dynamics. Environ. Planning,A 17, 585–596.

Dietzel, C., Clarke, K., 2006. The effect of disaggregating land use categories in cellular automata during model calibration and forecasting. Computers, Environment and Urban Systems, 30 (1), 78–101.

Duda, R. O., Hart, P. E., and Stork, D, G., 2000. Pattern classification, 2nded. New York: A Wiley-Interscience Publication.

Ediriwickrema, L., Khorram, S., 1997. Hierarchical maximum-likelihood classification for improved accuracies. IEEE Transactions on Geoscience and Remote Sensing, 35(4), 810-816.

Geertman, S., Hagoort, M., Ottens, H., 2007.Spatial–temporal specific neighbourhood rules for cellular automata land-use modelling. Int. J. Geogr. Inform. Sci. 21 (5), 547–568.

Hagerstrand, T., 1967. Innovation Diffusion as a Spatial Process, Chicago, IL: University of Chicago Press.

Itami, R.M., 1994. Simulating spatial dynamics: cellular automata theory.Landscape and Urban Planning, 30, 24–47.

Johnson, R. A., and Wichern, D. W., Applied Multivariate Statistical Analysis, Pearson Education, Second Indian Reprint, New Delhi, India, 2005, ISBN 81-7808-686-7, pp. 591-592 and 610-611.

Lau, K.H., Kam, B.H., 2005. A cellular automata model for urban land-use simulation.Environment and Planning B: Planning and Design, 32, 247–263.

Li, X., Yang, Q. S., Liu, X. P., 2007.Genetic algorithms for determining the parameters of the effect of disaggregating land use categories in cellular automata in urban simulation. Science in China, Series D: Earth 50(12), 1857–1866.

Li, X., Yang, Q., Liu, X., 2008. Discovering and evaluating urban signatures for simulating compact development using cellular automata. Landsc.Urban Plann. 86,177–186.

Li, X., Yeh, A., 2001.Calibration of cellular automata by using neural networks for the simulation of complex urban system.Environment and Planning A, 33, 1445–1462.

Li, X., Yeh, A.G., 2002. Neural-network based cellular automata for simulating multiple land use changes using GIS. International Journal of Geographical Information Sciences, 16, 323–343.

Li, X., and Yeh, A. G. O., 2003. Error propagation and model uncertainties of cellular automata in urban simulation with GIS. In:7th International Conference on GeoComputation, 8- 10, September 2003, University of Southampton, Southampton, UK (GeoComputation CD-ROM).

Liu, S., Li, X., Shi, X., Wu, S., Liu, T., 2008. Simulating complex urban development using kernel-based non-linear cellular automata.Ecological Modelling, 211, 169–181.

Lillesand, T. M., and Kiefer, R. W., Remote Sensing and Image Interpretation, Fourth Edition, John Wiley and Sons: New York, 2002, ISBN 9971-51-427-3.

Pinto, N.N., Antunes, A.P., 2007.Cellular automata and urban studies: a literature survey. Archit. City Environ. 1 (3), 367–398.

Ramachandra, T.V., and Kumar, U., 2008. Wetlands of Greater Bangalore, India: Automatic Delineation through Pattern Classifiers. Electronic Green Journal, 1(26), 1-22.

Richards, J. A., and Jia, X., Remote Sensing Digital Image Analysis, Springer-Verlag: Berlin, 2006.

Sante, I. Garcia, A. M. Miranda, D., and Crecente R., 2010, Cellular automata models for the simulation of real-world urban processes: A review and analysis. Landscape and Urban planning, 96, 108-122.

Silva, E.A, Clarke K.C., 2002.Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal.Computers, Environment and Urban Systems, 26, 525-552.

Stevens, D., Dragicevic, S., Rothley, K., 2007.iCity: a GIS-CA modelling tool for urban planning and decision making. Environmental Modelling & Software, 22, 761–773.
Strahler, A. H., 1980. The use of prior probabilities in maximum likelihood classification of remotely sensed data. Remote Sensing of Environment, 10, 135-163.

Tobler, W., ed., 1979. Cellular geography, in Philosophy.In: Geography, Eds S Gale, G Olsson (D Reidel, Dordrecht), 379-386.

Veldkamp, A.; Fresco, L., 1996, Clue-cr: An integrated multi-scale model to simulate land use change scenarios in costa rica. Ecological Modelling, 91, 231-248.

von Neumann, J., ed. Burks, A. W., 1966. Theory of Self-Reproducing Automata, Illinois: University of Illinois Press.
Verburg, P.H., 2010, The Clue Modelling Framework:CourSe Material, Amsterdam University Institute for Environmental Studies, pp. 53.

Verburg, P.H., de Koning, G., Kok, K., Veldkamp, A., Bouma, J., 1999, A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological Modelling, 116, 45–61.

Verburg, P.H. and Overmars, K.P., 2007, Dynamic Simulation of Land-Use Change Trajectories with the Clue-S Model. In: Modelling Land-Use Change, Progress and Applications V, (Eds. Koomen, Eric; Stillwell, John; Bakema, Aldrik; Scholten, H. J.), Springer, Netherlands, 90, 321-337.

Verburg, P.H., Soepboer, W., Limpiada, R., Espaldon, M.V.O., Sharifa, M., Veldkamp,  A., 2002, Land use change  modelling at the regional scale: the CLUE-S model. Environmental Management, 30, 391-405.

Verburg, P.H., Veldkamp, A., 2004, Projecting land use transitions at forest fringes in the Philippines at two spatial scales. Landscape Ecology, 19(1), 77-98.
Waddell, P., 2005. Introduction to urban simulation: design and development of operational models. Handbook in Transport, 5(2004), 203-236.

Wagner, D.F., 1997. Cellular automata and geographic information systems.Environ.Plann. B: Plann. Design 24, 219–234.

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. Geogr. Syst. 1, 237–253.

Wölfel, M., and Ekenel, H. K., 2005. Feature Weighted Mahalanobis Distance: Improved Robustness for Gaussian Classifiers, In Proceedings of the 13th European Signal Processing Conference: EUSIPCO, Antalya, Turkey, September, 2005.

Wolfram, S., 1984. Cellular automata: a model of complexity. Nature, 31, 419–424.

Wolfram, S., 1994. Cellular automata. In: Cellular Automata and Complexity: Collected Papers, Reading, MA: Addison Wesley.

Wolfram, S., 2002.A New Kind of Science.Wolfram Media, Canada.

World Urbanization Prospects, 2005.Revision, Population Division, Department of Economic and Social Affaris, UN.

Wu, F., 2002. Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Systems, 16 (8), 795–818.

Wu, F., and Webster, C. J., 1998, Simulation of land development through the integration of cellular automata and multi-criteria evaluation.Environment and Planning B, vol. 25, pp. 103-126.

Wu, Ning, and Silva, E. A., 2010. Artificial intelligence solutions for Urban Land Dynamics: A Review. Journal of Planning Literature, 24, 246-265.

Xu, L., Li, Z., Song, H., and Yin, H., 2013, Land-Use Planning for Urban Sprawl Based on the  CLUE-S Model: A Case Study of Guangzhou, China. Entropy, 15, 3490-3506.Yang, Q., Li, X., Shi, X., 2008. Cellular automata for simulating land use changes based on support vector machines. Computers & Geosciences, 34, 592–602.

Yang, X, and Lo, C. P., 2003. Modelling urban growth and landscape changes in the Atlanta metropolitan area.International Journal of Geographical Information Science, 17, 463-488.

Yeh, A., Li, X., 2001. A constrained CA model for the simulation and planning of sustainable urban forms by using GIS.Environment and Planning B: Planning and Design, 28, 733-753.

Zheng, M., Cai, Q., and Wang, Z., 2005. Effect of prior probabilities on maximum likelihood classifier. In: Geoscience and Remote Sensing Symposium, IGARS’05, 25-29 July, 2005, Seoul, Korea. 2005 IEEE International, 6, 3753-3756.


 

Citation : U. Kumar, C. Mukhopadhyay, T. V. Ramachandra, 2014. Cellular Automata Calibration Model to Capture Urban Growth. Boletín Geológico y Minero, 125 (3): 285-299 [Best Paper Award, Boletín Geológico y Minero].
* Corresponding Author :
  Dr. T.V. Ramachandra
Energy & Wetlands Research Group, Centre for Ecological Sciences, Indian Institute of Science, Bangalore – 560 012, INDIA.
  Tel : 91-80-23600985 / 22932506 / 22933099,
Fax : 91-80-23601428 / 23600085 / 23600683 [CES-TVR]
E-mail : cestvr@ces.iisc.ernet.in, energy@ces.iisc.ernet.in,
Web : http://wgbis.ces.iisc.ernet.in/energy
 
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