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  1. However, current research on CA modeling of urban growth predominantly focuses on uncovering objective patterns of urban growth, often falling short in adequately representing the impact of urban planning and policy on urban growth (Zhang and Wang 2021; Yang et al., 2024). Many studies tend to focus exclusively on the influence of macro-level policies on the quantitative structure of land use ...

  2. Feb 20, 2023 · The urban spatial growth intensity can effectively improve the spatial distribution of urban growth and can increase the accuracy of the urban CA model. As for the neighbourhood effects, we observed that more urban cells in the neighbourhood, does not necessarily mean a greater the probability of the central cell evolving.

  3. Apr 7, 2021 · Abstract. In recent decades, cellular automata (CA) have become popular for evaluating and forecasting urban transformation over time and space, especially in rapidly developing countries. These models enhance the understanding of urban dynamics and the complex interplay between land-use changes and urban sustainability.

    • Anthony G. O. Yeh, Xia Li, Chang Xia
    • 2021
  4. Mar 1, 2023 · Cellular automata (CA) has become one of the most prevalent approaches for spatially explicit urban growth modeling. Previous studies have investigated how the key components of CA models are defined, structured, and coupled to represent the top-down and bottom-up processes of urban growth.

  5. Dec 23, 2019 · Sakieh Y, Amiri BJ, Danekar A, Feghhi J, Dezhkam S (2015) Simulating urban expansion and scenario prediction using a cellular automata urban growth model, SLEUTH, through a case study of Karaj City, Iran. Journal of Housing and the Built Environment 30(4): 591–611.

    • Yan Liu, Michael Batty, Siqin Wang, Jonathan Corcoran
    • 2021
  6. Sep 10, 2024 · Regarding cellular automata-based urban growth simulation, many publications have applied different modeling approaches to simulate and project future scenarios for various kinds of areas ...

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  8. May 30, 2010 · In recent decades, a number of modeling techniques have been developed to better understand and predict urban growth. Early studies of urban processes used transportation and land-use planning models based on gravity theory or optimizing mathematics, but soon evolved into more dynamic spatial models (Berling-Wolff and Wu, 2004a), such as cellular automata (CA).

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