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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

Author

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  • Yilun Liu

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou 510642, China)

  • Yueming Hu

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China)

  • Shaoqiu Long

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Key Laboratory of the Ministry of Land and Resources for Construction Land Transformation, Guangzhou 510642, China)

  • Luo Liu

    (College of Natural Resources and Environment, South China Agricultural University, Guangzhou 510642, China
    Guangdong Province Key Laboratory for Land Use and Consolidation, Guangzhou 510642, China)

  • Xiaoping Liu

    (School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

Abstract

Developing countries have been undergoing dramatic urban growth over the past three decades. It is essential to understand and simulate the urban growth process for smart urban planning and sustainable development purposes. Cellular automata (CA) modeling is an efficient approach to simulating urban land use/cover change; however, the traditional CA method has limitations in simulating the various urban growth patterns and processes. This study aims to analyze the influences of different urban growth characteristics on the effectiveness of CA modeling by conducting a case study over the area in the Pearl River Delta of Southern China. We used the growth rate, landscape expansion index, and spatial dependency to quantify the urban growth characteristics. The effectiveness of CA modeling was measured through a comparison of the simulation results with the reference data. The simulation results and validation analyses reveal that the traditional CA is not applicable for the following three situations: (1) the urban growth pattern characterized by less growth area or a higher ratio of outlying expansion; (2) the urban region that includes several subregions with disparate growth characteristics; and (3) the existence of temporal differences in growth characteristics over a long period.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:9:y:2017:i:5:p:796-:d:98172
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    References listed on IDEAS

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    Cited by:

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    6. Ayanlade, Ayansina & Howard, Michael T., 2017. "Understanding changes in a Tropical Delta: A multi-method narrative of landuse/landcover change in the Niger Delta," Ecological Modelling, Elsevier, vol. 364(C), pages 53-65.
    7. Sadooghi, Seyed Ehsan & Taleai, Mohammad & Abolhasani, Somaie, 2022. "Simulation of urban growth scenarios using integration of multi-criteria analysis and game theory," Land Use Policy, Elsevier, vol. 120(C).
    8. Jun Ren & Wei Zhou & Xuelu Liu & Liang Zhou & Jing Guo & Yonghao Wang & Yanjun Guan & Jingtian Mao & Yuhan Huang & Rongrong Ma, 2019. "Urban Expansion and Growth Boundaries in an Oasis City in an Arid Region: A Case Study of Jiayuguan City, China," Sustainability, MDPI, vol. 12(1), pages 1-21, December.
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