2019
DOI: 10.3390/su11154012
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A Cellular Automata Model Constrained by Spatiotemporal Heterogeneity of the Urban Development Strategy for Simulating Land-use Change: A Case Study in Nanjing City, China

Abstract: While cellular automata (CA) has become increasingly popular in land-use and land-cover change (LUCC) simulations, insufficient research has considered the spatiotemporal heterogeneity of urban development strategies and applied it to constrain CA models. Consequently, we proposed to add a zoning transition rule and planning influence that consists of a development grade coefficient and traffic facility coefficient in the CA model to reflect the top-down and heterogeneous characteristics of spatial layout and … Show more

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Cited by 15 publications
(16 citation statements)
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“…Because of its powerful computing power and spatial modeling capabilities, it can simulate a variety of dynamic systems with very complex temporal and spatial features, such as biological reproduction and evolution. Compared with the traditional mathematical model, the cellular automaton can simulate various complex natural phenomena more clearly and accurately [25]. Its main advantage is the ability to simulate unpredictable results in complex systems.…”
Section: Cellular Automaton Modelmentioning
confidence: 99%
“…Because of its powerful computing power and spatial modeling capabilities, it can simulate a variety of dynamic systems with very complex temporal and spatial features, such as biological reproduction and evolution. Compared with the traditional mathematical model, the cellular automaton can simulate various complex natural phenomena more clearly and accurately [25]. Its main advantage is the ability to simulate unpredictable results in complex systems.…”
Section: Cellular Automaton Modelmentioning
confidence: 99%
“…After more than thirty years of continuous growth, China has entered into a relatively stable period of urbanization [3,4]. Now, smaller cities and towns -those with fewer than 5 million people-are gaining more attention and attracting new opportunities as regional planning policies are redistributing resources away from larger cities [5]. Today's planning policy in China aims for a balanced network of cities, where the small cities and towns in the coastal region become key components of regional urban networks, releasing the pressure, congestion, and pollution of larger cities such as Shanghai, Beijing, and Guangzhou.…”
Section: Introductionmentioning
confidence: 99%
“…The emergence of new modelling schemes, higher resolution data, and better computing capabilities enabled the progress of urban growth modelling. Recognizing that urban growth is a dynamic process with high uncertainty, [21] adopted the outcomes of planning policy to the model, [5] incorporated growth-constrain rules into the urban growth models, and [22] created multiple scenarios to simulate zone-specific land-use plans. To perform the spatiotemporal uncertainty analysis in this paper, we use a cellular automata (CA) model known as SLEUTH CA [20], and a Machine Learning (ML) framework that was introduced recently in [23].…”
Section: Introductionmentioning
confidence: 99%
“…Another partitioned particle swarm optimization–cellular automata (PSO‐CA) model has been proposed at both regional, meso and city scales by taking terrain feature and administrative boundaries into consideration (Feng et al., 2018). Besides, a set of zoning transition rules has been introduced to the proposed CA model by Yang, Shi, Sun, and Zhu (2019) as a reflection of the heterogeneous characteristics of the local urban development strategy. Xia, Zhang, Wang, and Zhang (2019) integrated partitioned logistic CA with an improved gravitational field model for the simulation of historical urban evolution.…”
Section: Introductionmentioning
confidence: 99%