标题: A new type of dual-scale neighborhood based on vectorization for cellular automata models
作者: Zhang, B (Zhang, Bin); Wang, HJ (Wang, Haijun)
来源出版物: GISCIENCE & REMOTE SENSING DOI: 10.1080/15481603.2021.1883946 提前访
摘要: Although the neighborhood of the cellular automata (CA) model has been studied in detail, there is a contradiction in the selection of the neighborhood size that has not been revealed and addressed. The contradiction is that small neighborhoods can constrain the shape complexity of the simulated landscape, but they cannot sufficiently characterize the local interactions, while large neighborhoods do the opposite. In this paper, we propose a new type of dual-scale neighborhood (DSN) based on vectorization to avoid this contradiction. Taking Beijing, Wuhan, and the Pearl River Delta in China as study areas, two kinds of CA models, namely, the CA model using the original neighborhood (ORN-CA) and the CA model using the proposed DSN (DSN-CA), were constructed based on the serial/scalar algorithm and the vectorized algorithm, respectively. The comparison of the simulation results and the time taken shows that the DSN enables the user to choose the appropriate neighborhood configuration to obtain high-accuracy simulation results and a landscape that is similar to the ground truth. The vectorization can also greatly improve the computational efficiency of the neighborhood effects. Overall, the findings show that integrating the DSN with vectorization can significantly improve the simulation performance and efficiency of CA models.
文献类型: Article; Early Access
作者关键词: Cellular automata; neighborhood; dual-scale; urban growth; simulation
地址: [Zhang, Bin; Wang, Haijun] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.
[Wang, Haijun] Wuhan Univ, Key Lab Geog Informat Syst MOE, Wuhan, Peoples R China.
通讯作者地址: Wang, HJ (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Peoples R China.
Wang, HJ (通讯作者)，Wuhan Univ, Key Lab Geog Informat Syst MOE, Wuhan, Peoples R China.
版权所有 © 武汉大学资源与环境科学学院