太阳成8722(中国)有限公司-GREEN NO.1

标题: Using a maximum entropy model to optimize the stochastic component of urban cellular automata models

作者: Wang, HJ (Wang, Haijun); Zhang, B (Zhang, Bin); Xia, C (Xia, Chang); He, SW (He, Sanwei); Zhang, WT (Zhang, Wenting)

来源出版物: INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE  DOI: 10.1080/13658816.2019.1687898  提前访问日期: NOV 2019  

摘要: The stochastic perturbation of urban cellular automata (CA) model is difficult to fine-tune and does not take the constraint of known factors into account when using a stochastic variable, and the simulation results can be quite different when using the Monte Carlo method, reducing the accuracy of the simulated results. Therefore, in this paper, we optimize the stochastic component of an urban CA model by the use of a maximum entropy model to differentially control the intensity of the stochastic perturbation in the spatial domain. We use the kappa coefficient, figure of merit, and landscape metrics to evaluate the accuracy of the simulated results. Through the experimental results obtained for Wuhan, China, the effectiveness of the optimization is proved. The results show that, after the optimization, the kappa coefficient and figure of merit of the simulated results are significantly improved when using the stochastic variable, slightly improved when using Monte Carlo methods. The landscape metrics for the simulated results and actual data are much closer when using the stochastic variable, and slightly closer when using the Monte Carlo method, but the difference between the simulated results is narrowed, reflecting the fact that the results are more reliable.

入藏号: WOS:000495532200001

语言: English

文献类型: Article; Early Access

作者关键词: Urban cellular automata; maximum entropy; stochastic component; geographic simulation

地址: [Wang, Haijun; Zhang, Bin] Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China.

[Wang, Haijun] Wuhan Univ, Key Lab Geog Informat Syst MOE, Wuhan, Hubei, Peoples R China.

[Xia, Chang] Univ Hong Kong, Dept Urban Planning & Design, Hong Kong, Peoples R China.

[He, Sanwei] Zhongnan Univ Econ & Law, Sch Publ Adm, Wuhan, Hubei, Peoples R China.

[Zhang, Wenting] Huazhong Agr Univ, Coll Resources & Environm, Wuhan, Hubei, Peoples R China.

通讯作者地址: Zhang, B (通讯作者)，Wuhan Univ, Sch Resource & Environm Sci, Wuhan, Hubei, Peoples R China.

电子邮件地址: landgiszb@whu.edu.cn

影响因子：3.545