References
- Batty, M. and Xie, Y., 1994. From cells to cities. Environment and Planning B: Planning and Design, 21, 531–548.
- Benenson, I., 1998. Multi-agent simulations of residential dynamics in the city. Computers, Environment and Urban Systems, 22 (1), 25–42.
- Berjak, S.G. and Hearne, J.W., 2002. An improved cellular automaton model for simulating fire in a spatially heterogeneous Savanna system. Ecological Modelling, 148, 133–151.
- Berling-wolff, S. and Wu, J., 2004. Modeling urban landscape dynamics: a review. Ecology Research, 19, 119–129.
- Bone, C., Dragicevic, S., and Roberts, A., 2006. A fuzzy-constrained cellular automata model of forest insect infestations. Ecological Modelling, 192, 107–125.
- Cheng, J. and Masser, I., 2004. Understanding spatial and temporal processes of urban growth: cellular automata modelling. Environment and Planning B, 31, 167–194.
- 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, 699–714.
- Clarke, K.C., Hoppen, S., and Gaydos, L.J., 1997. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area. Environment and Planning B, 24, 247–261.
- He, C., et al., 2011. Simulation of the spatial stress due to urban expansion on the wetlands in Beijing, China using a GIS-based assessment model. Landscape and Urban Planning, 101 (3), 269–277.
- Heimlich, R.E. and Anderson, W.D., 2001. Development at the urban fringe and beyond: impacts on agricultural and rural land. Washington, D.C: US Department of Agriculture, Economic Research Service, AER–803.
- Herold, M., Goldstein, N.C., and Clarke, K.C., 2003. The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote Sensing of Environment, 86 (3), 286–302.
- Leao, S., Bishop, I., and Evans, D., 2004. Simulating urban growth in a developing nation’s region using a CA-based model. Journal of Urban Planning and Development, 130 (3), 145–158.
- Li, X. and Liu, X.P., 2006. An extended cellular automaton using case-based reasoning for simulating urban. International Journal of Geographical Information Science, 20, 1109–1136.
- 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, 323–343.
- Liu, X.P., et al., 2008a. A bottom-up approach to discover transition rules of cellular automata using ant intelligence. International Journal of Geographical Information Science, 22, 1247–1269.
- Liu, X.P., et al, 2008b. Simulating complex urban development using kernel-based non-linear cellular automata. Ecological Modeling, 211, 169–181.
- Liu, X.P., et al., 2010a. Simulating land use dynamics under planning policies by integrating artificial immune systems with cellular automata. International Journal of Geographical Information Science, 24 (5), 783–802.
- Liu, X.P., et al., 2010b. A new landscape index for quantifying urban expansion using multi-temporal remotely sensed data. Landscape Ecology, 25, 671–682.
- Liu, X.P., et al., 2012. A multi-type ant colony optimization (MACO) method for optimal land use allocation in large areas. International Journal of Geographical Information Science, 26 (7), 1325–1343.
- Liu, Y. and Stuart, R.P., 2003. Modelling urban development with cellular automata incorporating fuzzy-set approaches. Computers, Environment and Urban Systems, 27, 637–658.
- Matsinos, Y.G. and Troumbis, A.Y., 2002. Modeling competition, dispersal and effects of disturbance in the dynamics of a grassland community using a cellular automaton model. Ecological Modelling, 149, 71–83.
- Pijanowskia, B.C., et al., 2002. Using neural networks and GIS to forecast land use changes: a land transformation model. Computers, Environment and Urban Systems, 26 (6), 553–575.
- Sirakoulis, G.C., Karafyllidis, I., and Thanailakis, A., 2000. A cellular automaton model for the effects of population movement andvaccination on epidemic propagation. Ecological Modelling, 133, 209–223.
- Tobler, W., 1970. A computer movie simulating urban growth in the Detroit region, Economic Geography, 46, 234–240.
- Torrens, P.M. and O’Sullivan, D., 2001. Cellular automata and urban simulation: where do we go from here? Environment and Planning B, 28, 163–168.
- United Nations, 2004. World urbanization prospects: the 2003 revision. New York, NY: United Nations Economic and Social Affairs, 335 pp.
- Verburg, P.H., et al., 1999. A spatial explicit allocation procedure for modelling the pattern of land use change based upon actual land use. Ecological Modelling, 116, 45–61.
- Wang, Y. and Zhang, X., 2001. A dynamic modelling approach to simulating socioeconomic effects on landscape changes. Ecological Modelling, 140, 141–162.
- 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.
- Wilson, E.H., et al., 2003. Development of a geospatial model to quantify, describe and map urban growth. Remote Sensing of Environment, 86, 275–285.
- Wu, F., 2002. Calibration of stochastic cellular automata: the application to rural–urban land conversions. International Journal of Geographical Information Science, 16, 795–818.
- Wu, F. and Webster, C.J., 1998. Simulation of land development through the integration of cellular automata and multicriteria evaluation. Environment and Planning B, 25, 103–126.