Abstract
To support urban planning for sustainable development, the SLEUTL model was selected to predict urban growth under different scenarios in this paper. Taken the Dongguan central city of the Pearl River Delta as an example, three scenarios for different planning goals were created, which were the Historical Trend (HT) scenario, the Forest Protection (FP) scenario and the Growth Restriction (GR) scenario. The results showed that the urban area would expand continuously from 2003 to 2030 under the HT scenario. More land resources would be saved in GR scenario than FP scenario. Furthermore, the urban growth under HT and FP scenarios would come to a steady state at 2020, while this deadline of the GR scenario would be postpone to 2025. The results of scenario prediction demonstrated that the GR scenario was more effective to meet the goal of land protection for the study area.
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References
Long, H., Tang, G., Li, X., Gerhard: Socio-economic driving forces of land-use change in Kunshan, the Yangtze River Delta economic area of China. Journal of Environmental Management 83, 351–364 (2007)
Zhang, K.H., Song, S.: Rural–urban migration and urbanization in China: Evidence from time-series and cross-section analyses. China Economic Review 14, 386–400 (2003)
Chen, J.: Rapid urbanization in China: A real challenge to soil protection and food security. Catena 69, 1–15 (2007)
Shen, L., Cheng, S., Gunson, A.J., Wan, H.: Urbanization, sustainability and the utilization of energy and mineral resources in China. Cities 22, 287–302 (2005)
Editorial, Scenario-based studies of future land use in Europe. Agriculture, Ecosystems and Environment 114, 1–6 (2006)
Menard, A., Marceau, D.J.: Simulating the impact of forest management scenarios in an agricultural landscape of southern Quebec, Canada, using a geographic cellular automata. Landscape and Urban Planning 79, 253–265 (2007)
Petrov, L.O., Lavalle, C., Kasanko, M.: Urban land use scenarios for a tourist region in Europe: Applying the MOLAND model to Algarve, Portugal. Landscape and Urban Planning 92, 10–23 (2009)
Rafiee, R., Mahiny, A.S., Khorasani, N., Darvishsefat, A.A., Danekar, A.: Simulating urban growth in Mashad City, Iran through the SLEUTH model (UGM). Cities 26, 19–26 (2009)
Rounsevell, M.D.A., Ewert, F., Reginster, I., Leemans, R., Carter, T.R.: Future scenarios of European agricultural land use II. Projecting changes in cropland and grassland. Agriculture, Ecosystems and Environment 107, 117–135 (2005)
Verburg, P.H., Schulp, C.J.E., Witte, N., Veldkamp, A.: Downscaling of land use change scenarios to assess the dynamics of European landscapes. Agriculture, Ecosystems and Environment 114, 39–56 (2006)
Luo, G., Yin, C., Chen, X., Xu, W., Lu, L.: Combining system dynamic model and CLUE-S model to improve land use scenario analyses at regional scale: A case study of Sangong watershed in Xinjiang, China. Ecological Complexity 7, 198–207 (2010)
Solecki, W.D., Oliveri, C.: Downscaling climate change scenarios in an urban land use change model. Journal of Environmental Management 72, 105–115 (2004)
Clarke, K.C.: Loose coupling a cellular automaton model and GIS long term urban growth prediction for San Francisco and Washington/Baltimore. International Journal of Geographical Information Science 12, 699–714 (1998)
Clarke, K.C., Hoppen, S.: 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 (1997)
Silva, E.A., Clarke, K.C.: Calibration of the SLEUTH urban growth model for Lisbon and Porto. Computers, Environment and Urban Systems 26, 525–552 (2002)
US Geological Survey. Project gigalopolis: Urban and land cover modeling (2007), http://www.ncgia.ucsb.edu/projects/gig/
Herold, M., Goldstein, N.C., Clarke, K.C.: The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote Sensing of Environment 86, 286–302 (2003)
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Feng, H., Liu, H. (2012). Scenario Prediction of Urban Growth Based on the SLEUTH Model. In: Wu, Y. (eds) Advanced Technology in Teaching - Proceedings of the 2009 3rd International Conference on Teaching and Computational Science (WTCS 2009). Advances in Intelligent and Soft Computing, vol 117. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25437-6_126
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DOI: https://doi.org/10.1007/978-3-642-25437-6_126
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