905
Views
76
CrossRef citations to date
0
Altmetric
Original Articles

A systematic sensitivity analysis of constrained cellular automata model for urban growth simulation based on different transition rules

, &
Pages 1317-1335 | Received 11 Aug 2013, Accepted 09 Jan 2014, Published online: 18 Mar 2014

References

  • Batty, M. and Xie, Y., 1994. From cells to cities. Environment and Planning B: Planning and Design, 21 (7), 31–48.
  • Breiman, L., 1996. Bagging predictors. Machine Learning, 24 (2), 123–140.
  • Chen, J., et al., 2002. Assessment of urban development plan of Beijing by using CA-based urban growth model. Photogrammetric Engineering & Remote Sensing, 68 (10), 1063–1071.
  • Chen, Y., et al., 2011. Estimating the relationship between urban forms and energy consumption: a case study in the Pearl River Delta, 2005–2008. Landscape and Urban Planning, 102 (1), 33–42.
  • Clarke, K., 1997. A self-modifying cellular automaton model of historical. Environment and Planning B: Planning and Design, 24, 247–261.
  • Clinton, N. and Gong, P., 2013. MODIS detected surface urban heat islands and sinks: global locations and controls. Remote Sensing of Environment, 134, 294–304.
  • Couclelis, H., 1985. Cellular worlds: a framework for modeling micro-macro dynamics. Environment and Planning A, 17 (5), 585–596.
  • Freund, Y. and Schapire, R.E., 1996. Experiments with a new boosting algorithm. In: S. Lorenza, ed. Machine Learning: Proceedings of the Thirteenth International Conference (ICML ‘96), 3–6 July 1996 Bari. San Francisco, CA: Morgan Kaufmann Publisher, 148–156.
  • Garcia, A.M., et al., 2011. An analysis of the effect of the stochastic component of urban cellular automata models. Computers, Environment and Urban Systems, 35 (4), 289–296.
  • Garcia, A.M., et al., 2012. A comparative analysis of cellular automata models for simulation of small urban areas in Galicia, NW Spain. Computers, Environment and Urban Systems, 36 (4), 291–301.
  • Gong, P., 1993. Change detection using principal component analysis and fuzzy set theory. Canadian Journal of Remote Sensing, 19 (1), 22–29.
  • Gong, P., 2012. Remote sensing of environmental change over China: a review. Chinese Science Bulletin, 57 (22), 2793–2801.
  • Gong, P., et al., 2012. Urbanisation and health in China. Lancet, 379 (9818), 843–852.
  • He, C., et al., 2006. Modeling urban expansion scenarios by coupling cellular automata model and system dynamic model in Beijing, China. Applied Geography, 26 (3), 323–345.
  • Hu, Z. and Lo, C.P., 2007. Modeling urban growth in Atlanta using logistic regression. Computers, Environment and Urban Systems, 31 (6), 667–688.
  • Jantz, C.A., et al., 2010. Designing and implementing a regional urban modeling system using the SLEUTH cellular urban model. Computers, Environment and Urban Systems, 34 (1), 1–16.
  • Kocabas, V. and Dragicevic, S., 2006. Assessing cellular automata model behaviour using a sensitivity analysis approach. Computers, Environment and Urban Systems, 30 (6), 921–953.
  • Li, X., et al., 2011. Concepts, methodologies, and tools of an integrated geographical simulation and optimization system. International Journal of Geographical Information Science, 25 (4), 633–655.
  • Li, X., et al., 2013. Calibrating cellular automata based on landscape metrics by using genetic algorithms. International Journal of Geographical Information Science, 27 (3), 594–613.
  • Li, X. and Liu, X., 2006. An extended cellular automaton using case – based reasoning for simulating urban development in a large complex region. International Journal of Geographical Information Science, 20 (10), 1109–1136.
  • Li, X. and Yeh, A.G.-O., 2000. Modelling sustainable urban development by the integration of constrained cellular automata and GIS. 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, 16 (4), 323–343.
  • Li, X. and Yeh, A.G.-O., 2004. Data mining of cellular automata’s transition rules. International Journal of Geographical Information Science, 18 (8), 723–744.
  • Liu, J., Zhan, J., and Deng, X., 2005. Spatio-temporal patterns and driving forces of urban land expansion in China during the economic reform era. AMBIO: A Journal of the Human Environment, 34 (6), 450–455.
  • Liu, X., et al., 2008. A bottom-up approach to discover transition rules of cellular automata using ant intelligence. International Journal of Geographical Information Science, 22 (11–12), 1247–1269.
  • Liu, X., et al., 2011. Zoning farmland protection under spatial constraints by integrating remote sensing, GIS and artificial immune systems. International Journal of Geographical Information Science, 25 (11), 1829–1848.
  • Liu, Y. and Phinn, S.R., 2003. Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers, Environment and Urban Systems, 27 (6), 637–658.
  • McGarigal, K., et al., 2012. FRAGSTATS v4: spatial pattern analysis program for categorical and continuous maps [online]. Computer software program produced by the authors at the University of Massachusetts, Amherst. Available from: http://www.umass.edu/landeco/research/fragstats/fragstats.html [Accessed 28 January 2014].
  • Menard, A. and Marceau, D.J., 2005. Exploration of spatial scale sensitivity in geographic cellular automata. Environment and Planning B: Planning and Design, 32 (5), 693–714.
  • Pan, Y., et al., 2010. The impact of variation in scale on the behavior of a cellular automata used for land use change modeling. Computers, Environment and Urban Systems, 34 (5), 400–408.
  • Polikar, R., 2006. Ensemble based systems in decision making. Circuits and Systems Magazine, IEEE, 6 (3), 21–45.
  • Samat, N., 2006. Characterizing the scale sensitivity of the cellular automata simulated urban growth: a case study of the Seberang Perai Region, Penang State, Malaysia. Computers, Environment and Urban Systems, 30 (6), 905–920.
  • Sante, I., et al., 2010. Cellular automata models for the simulation of real-world urban processes: a review and analysis. Landscape and Urban Planning, 96 (2), 108–122.
  • Schneider, A., Friedl, M.A., and Potere, D., 2010. Mapping global urban areas using MODIS 500-m data: new methods and datasets based on ‘urban ecoregions’. Remote Sensing of Environment, 114 (8), 1733–1746.
  • Sun, X.F., Yue, T.X., and Fan, Z.M., 2012. Simulation of the spatial pattern of land use change in China: the case of planned development scenario. Acta Ecologica Sinica, 20, 6440–6451.
  • United Nations, 2012. World Urbanization Prospects: The 2011 revision. New York: United Nations.
  • Wang, L., et al., 2012. China’s urban expansion from 1990 to 2010 determined with satellite remote sensing. Chinese Science Bulletin, 57 (22), 2802–2812.
  • 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 (8), 1175–1199.
  • White, R., Engelen, G., and Uljee, 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, 323–344.
  • Wu, B., Huang, B., and Fung, T., 2009. Projection of land use change patterns using kernel logistic regression. Photogrammetric Engineering & Remote Sensing, 75 (8), 971–979.
  • Wu, F., 2002. Calibration of stochastic cellular automata: the application to rural-urban land conversions. International Journal of Geographical Information Science, 16 (8), 795–818.
  • Wu, F. and Webster, C.J., 1998. Simulation of natural land use zoning under free-market and incremental development control regimes. Computers, Environment and Urban Systems, 22 (3), 241–256.
  • Wu, H., et al., 2012. Quantifying and analyzing neighborhood configuration characteristics to cellular automata for land use simulation considering data source error. Earth Science Informatics, 5 (2), 77–86.
  • Yeh, A.G.-O. and Li, X., 2006. Errors and uncertainties in urban cellular automata. Computers, Environment and Urban Systems, 30 (1), 10–28.
  • Zhang, G.J., Cai, M., and Hu, A., 2013. Energy consumption and the unexplained winter warming over northern Asia and North America. Nature Climate Change, 3 (5), 466–470.
  • Zhang, Q., He, K., and Huo, H., 2012. Policy: cleaning China’s air. Nature, 484 (7393), 161–162.
  • Zhang, Y.H., et al., 2011. The CA model based on data assimilation. Journal of Remote Sensing, 15 (3), 475–491.
  • Zhou, Z.H., Wu, J., and Tang, W., 2002. Ensembling neural networks: many could be better than all. Artificial Intelligence, 137 (1), 239–263.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.