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Improving an Urban Cellular Automata Model Based on Auto-Calibrated and Trend-Adjusted Neighborhood

Author

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  • Xinhao Pan

    (Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Zichen Wang

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Miao Huang

    (Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

  • Zhifeng Liu

    (Center for Human-Environment System Sustainability (CHESS), State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE), Beijing Normal University, Beijing 100875, China
    Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China)

Abstract

Accurately simulating urban expansion is of great significance for promoting sustainable urban development. The calculation of neighborhood effects is an important factor that affects the accuracy of urban expansion models. The purpose of this study is to improve the calculation of neighborhood effects in an urban expansion model, i.e., the land-use scenario dynamics-urban (LUSD-urban) model, by integrating the trend-adjusted neighborhood algorithm and the automatic rule detection procedure. Taking eight sample cities in China as examples, we evaluated the accuracies of the original model and the improved model. We found that the improved model can increase the accuracy of simulated urban expansion in terms of both the degree of spatial matching and the similarity of urban form. The increase of accuracy can be attributed to such integration comprehensively considers the effects of historical urban expansion trends and the influences of neighborhoods at different scales. Therefore, the improved model in this study can be widely used to simulate the process of urban expansion in different regions.

Suggested Citation

  • Xinhao Pan & Zichen Wang & Miao Huang & Zhifeng Liu, 2021. "Improving an Urban Cellular Automata Model Based on Auto-Calibrated and Trend-Adjusted Neighborhood," Land, MDPI, vol. 10(7), pages 1-17, June.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:7:p:688-:d:585527
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    References listed on IDEAS

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    1. R White & G Engelen, 1993. "Cellular Automata and Fractal Urban Form: A Cellular Modelling Approach to the Evolution of Urban Land-Use Patterns," Environment and Planning A, , vol. 25(8), pages 1175-1199, August.
    2. Karen C Seto & Michail Fragkias & Burak Güneralp & Michael K Reilly, 2011. "A Meta-Analysis of Global Urban Land Expansion," PLOS ONE, Public Library of Science, vol. 6(8), pages 1-9, August.
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    Cited by:

    1. Quang Chi Truong & Thao Hong Nguyen & Kenichi Tatsumi & Vu Thanh Pham & Van Pham Dang Tri, 2022. "A Land-Use Change Model to Support Land-Use Planning in the Mekong Delta (MEKOLUC)," Land, MDPI, vol. 11(2), pages 1-16, February.
    2. Pedro Bueno Rocha Campos & Cláudia Maria de Almeida & Alfredo Pereira de Queiroz, 2022. "Spatial Dynamic Models for Assessing the Impact of Public Policies: The Case of Unified Educational Centers in the Periphery of São Paulo City," Land, MDPI, vol. 11(6), pages 1-25, June.

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