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Simulating Urban Growth Using the SLEUTH Model in a Coastal Peri-Urban District in China

Author

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  • Lizhong Hua

    (College of Computer and Information Engineering, Xiamen University of Technology, Xiamen 361024, China)

  • Lina Tang

    (Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Shenghui Cui

    (Key Lab of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Kai Yin

    (The Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100101, China)

Abstract

China’s southeast coastal areas have witnessed rapid growth in the last two decades, owing mostly to their economic and social attractions. In this paper, we chose Jimei, a coastal peri-urban district of Xiamen city on the southeast coast of China, as a study area to explore the district’s growth dynamics, to predict future sprawl during the next decade and to provide a basis for urban planning. The SLEUTH urban growth model was calibrated against historical data derived from a series of Landsat TM 5 satellite images taken between 1992 and 2007. A Lee-Sallee value of 0.48 was calculated for the district, which is a satisfactory result compared with related studies. Five coefficients of urban growth, diffusion, spread, breed, slope resistance and road gravity had values of 25, 68, 86, 24 and 23, respectively, in 2007. The growth coefficients ( i.e ., urban character) can capture urban growth characteristics in Jimei district. The urban DNA revealed that, over the study period, urban growth in the district was dominated both by urbanization through establishment of new urban centers, and by expansion outward from existing urban centers. In contrast to interior cities, in which expansions are dramatically shaped by actual road patterns, urban expansion in the district was likely constrained by the nearby coastline. Future urban growth patterns were predicted to 2020 assuming three different development scenarios. The first scenario simulated a continuation of historical urban growth without changing current conditions. The second scenario projected managed growth in which urban growth is limited by a layer with areas excluded from urbanization, which is the future development plan for Jimei district and Xiamen city. The third scenario depicted a growth with maximum protection in which growth was allowed to continue, similar to the second scenario, but with lower diffusion and spread coefficients applied to the growth pattern. The third scenario demonstrated that valuable land could be saved, which is the most desirable outcome for Jimei urban development. The study showed that SLEUTH can be an extremely useful tool for coastal city managers to explore the likely outcomes of their city development plans.

Suggested Citation

  • Lizhong Hua & Lina Tang & Shenghui Cui & Kai Yin, 2014. "Simulating Urban Growth Using the SLEUTH Model in a Coastal Peri-Urban District in China," Sustainability, MDPI, vol. 6(6), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:6:y:2014:i:6:p:3899-3914:d:37196
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    Cited by:

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    3. Sajida Perveen & Md. Kamruzzaman & Tan Yigitcanlar, 2017. "Developing Policy Scenarios for Sustainable Urban Growth Management: A Delphi Approach," Sustainability, MDPI, vol. 9(10), pages 1-27, October.
    4. Hsing-Fu Kuo & Ko-Wan Tsou, 2017. "Modeling and Simulation of the Future Impacts of Urban Land Use Change on the Natural Environment by SLEUTH and Cluster Analysis," Sustainability, MDPI, vol. 10(1), pages 1-21, December.
    5. Erqi Xu & Yimeng Chen, 2019. "Modeling Intersecting Processes of Wetland Shrinkage and Urban Expansion by a Time-Varying Methodology," Sustainability, MDPI, vol. 11(18), pages 1-24, September.
    6. Yishao Shi & Jie Wu & Shouzheng Shi, 2017. "Study of the Simulated Expansion Boundary of Construction Land in Shanghai Based on a SLEUTH Model," Sustainability, MDPI, vol. 9(6), pages 1-15, May.
    7. Hashem Dadashpoor & Mahboobeh Nateghi, 2017. "Simulating spatial pattern of urban growth using GIS-based SLEUTH model: a case study of eastern corridor of Tehran metropolitan region, Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 19(2), pages 527-547, April.
    8. Xiaobin Yang & Zhilong Chen & Hao Cai & Linjian Ma, 2014. "A Framework for Assessment of the Influence of China’s Urban Underground Space Developments on the Urban Microclimate," Sustainability, MDPI, vol. 6(12), pages 1-31, November.
    9. Maryam Kiani Sadr & Roghayeh Parchianloo & Sedighe Abdollahi & Hamta Golkarian, 2023. "Application of weighted aggregated sum product assessment and geographical information system for urban development zoning," Asia-Pacific Journal of Regional Science, Springer, vol. 7(3), pages 845-863, September.
    10. Hashem Dadashpoor & Fardis Salarian, 2020. "Urban sprawl on natural lands: analyzing and predicting the trend of land use changes and sprawl in Mazandaran city region, Iran," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 22(2), pages 593-614, February.
    11. Lizhong Hua & Xinxin Zhang & Qin Nie & Fengqin Sun & Lina Tang, 2020. "The Impacts of the Expansion of Urban Impervious Surfaces on Urban Heat Islands in a Coastal City in China," Sustainability, MDPI, vol. 12(2), pages 1-21, January.
    12. Youjung Kim & Galen Newman & Burak Güneralp, 2020. "A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models," Land, MDPI, vol. 9(8), pages 1-22, July.
    13. Yilun Liu & Yueming Hu & Shaoqiu Long & Luo Liu & Xiaoping Liu, 2017. "Analysis of the Effectiveness of Urban Land-Use-Change Models Based on the Measurement of Spatio-Temporal, Dynamic Urban Growth: A Cellular Automata Case Study," Sustainability, MDPI, vol. 9(5), pages 1-15, May.

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