Special Column:Celebration of the 70th Anniversary of IGSNRR, CAS

Applying SLEUTH for Simulating Urban Expansion of Hangzhou

  • 1. College of Resources and Environment, Southwest University, Chongqing 400716, China;
    2. Institute of Land Science and Property Management, Zhejiang University, Hangzhou 310029, China;
    3. School of Urban Design, Wuhan University, Wuhan 430072, China

Received date: 2008-01-21

  Revised date: 2008-05-23

  Online published: 2008-09-28


Rapid urbanization often results in intensive land use change especially in the urban area of China. Simulation of urban expansion thus captures increasing research interests. Taking the metropolitan area of Hangzhou as a case study, this paper utilized the urban growth model of SLEUTH to forecast the urban growth of Hangzhou in four alternative scenarios based on four Landsat TM/ETM+ images(e.g. 1991, 1996, 2000 and 2005). Through generating buffers from the CBD and urban fringe area, the research explored the past change process and projected the future urban pattern. The results indicated that Compare and Lee-sallee were 0.95 and 0.59 respectively in the calibration process of SLEUTH, and the amount and morphology of simulatcd urban were more consistent with actual situation in 2005 than in the past. Due to the complex behavior of urban systems, SLEUTH was unable to simulate wave-like process of urban growth and potential development. Based on different assumptions, four scenarios were simulated by SLEUTH model, which included Maintain Status Quo, Expanded Roads, Moderate Farmland Protection and Compact City. The urbanization process could be divided into three phases including radial urban growth from 1991 to 1996, spatially contiguous expansion from 1996 to 2000, and multi-nuclear development from 2000 to 2005.Urban area would increase linearly and urban morphology would continue to be multi-nuclear from projected scenarios. The hotspot area featured by intensive urban growth would shift from urban center to new developed area outside. The growth intensity declined in power function and it would be less in the future than in the past. It would decrease gradually in the area with the radius of 12 km from CBD or 500 m from urban fringe. Urban area would increase by 189 km2 and farmland would reduce by 9 km2 per year from the result of MSQ. Urban area would be restricted by MFP from urban encroachment, and pushed to new developed area by ER from over crowded area and concentrated in the edge of the existing urban area by CC. Urban plan and land use planning can help to save farmland and adjust urban morphology.

Cite this article

LIU Yong, WU Ci-fang, YUE Wen-ze, HUANG Jing-nan . Applying SLEUTH for Simulating Urban Expansion of Hangzhou[J]. JOURNAL OF NATURAL RESOURCES, 2008 , 23(5) : 797 -807 . DOI: 10.11849/zrzyxb.2008.05.007


[1] Turner B L, Meyer W B. Global land use and land cover change: An overview. Meyer W B, Turner B L. Changes in Land Use and Land Cover: A Global Perspective. New York: Cambridge University Press, 1994.1-11. [2] Lambin E F, Turner B L, Geist H J, et al. The causes of land-use and land-cover change: Moving beyond the myths[J]. Global Environmental Change,2001,11(4):261-269. [3] United Nations. World Urbanization Prospects: The 2003 Revision[M]. New York: United Nations Press, 2004. [4] Batty M. Urban evolution on the desktop: Simulation with the use of extended cellular automata[J]. Environment and Planning A,1998,30(11):1943-1967. [5] Wu F. Calibration of stochastic cellular automata: The application to rural-urban land conversions[J]. International Journal of Geographical Information Science,2002,16(8):795-818. [6] 黎夏,叶嘉安,刘小平,等.地理模拟系统:元胞自动机与多智能体[M].北京:科学出版社,2007. [7] Torrens P M, O'Sullivan D. Cellular automata and urban simulation: Where do we go from here?[J]. Environment and Planning B: Planning and Design,2001,28(2):163-168. [8] Fragkias M, Seto K C. Modeling urban growth in data-sparse environments: A new approach[J]. Environment and Planning B: Planning and Design,2007,34(5):858-883. [9] Clarke K C, Hoppen S, Gaydos J. A self-modifying cellular automaton model of historical urbanization in the San Francisco Bay area[J]. Environment and Planning B: Planning and Design,1997,24(2):247-261. [10] Silva E A, Clarke K C. Calibration of the SLEUTH urban growth model for Lisbon and Porto, Portugal[J]. Computers, Environment and Urban Systems,2002,26(6):525-552. [11] Clarke K C, Gaydos L J. Loose-coupling a cellular automaton model and GIS: Long-term urban growth prediction for San Francisco and Washington/Baltimore[J]. International Journal of Geographical Information Science,1998,12(7):699-714. [12] Jantz C A, Geog D, Goetz S J, et al. Using the SLEUTH urban growth model to simulate the impacts of future policy scenario on urban land use in the Baltimore-Washington metropolitan area[J]. Environment and Planning B: Planning and Design,2004,31(2):251-271. [13] 丁菡.中国沿海经济发达地区土地利用变化及其驱动机制与预测模型研究——以浙江省沿海地区为例(博士学位论文).杭州:浙江大学,2006. [14] 武晓波,赵健,魏成阶,等.细胞自动机模型用于城市发展模拟的方法初探——以海口市为例[J].城市规划, 2002,26(8):69~73. [15] 张岩,李京,陈云浩.利用SLEUTH模型进行北京城市扩展模拟研究[J].遥感信息,2007,(2): 50~54. [16] 冯健.杭州城市形态和土地利用结构的时空演化[J].地理学报,2003,58(3):343~353. [17] 周国平.对杭州城市空间扩展的设想[J].浙江建筑,2006,23(11):1~10. [18] 李王鸣,李疏贝.杭州都市区新城发展特点与发展策略研究[J].浙江大学学报:理学版,2005,32(1): 108~114,120. [19] Xu C, Liu M, Zhang C, et al. The spatiotemporal dynamics of rapid urban growth in the Nanjing metropolitan region of China[J]. Landscape Ecology,2007,22(6):925-937. [20] 朱会义,李秀彬.关于区域土地利用变化指数模型方法的讨论[J].地理学报,2003,58(5):643~649. [21] 姚士谋.中国大都市的空间扩展[M].合肥:中国科技大学出版社,1997.465~483. [22] 冯健.转型期中国城市内部空间重构[M].北京:科学出版社,2004. [23] 杭州市规划局,杭州市城市规划编制中心.迈向钱塘江时代[M].上海:同济大学出版社,2002. [24] Xian G, Crane M. Assessments of urban growth in the Tampa Bay watershed using remote sensing data[J]. Remote Sensing of Environment,2005,97(2):203-215.