标题: Incorporation of intra-city human mobility into urban growth simulation: A case study in Beijing
作者: Wang, SY (Wang, Siying); Fei, T (Fei, Teng); Li, WF (Li, Weifeng); Zhang, AQ (Zhang, Anqi); Guo, HG (Guo, Huagui); Du, YY (Du, Yunyan)
来源出版物: JOURNAL OF GEOGRAPHICAL SCIENCES 卷: 32 期: 5 页: 892-912 DOI: 10.1007/s11442-022-1977-6 出版年: MAY 2022
摘要: The effective modeling of urban growth is crucial for urban planning and analyzing the causes of land-use dynamics. As urbanization has slowed down in most megacities, improved urban growth modeling with minor changes has become a crucial open issue for these cities. Most existing models are based on stationary factors and spatial proximity, which are unlikely to depict spatial connectivity between regions. This research attempts to leverage the power of real-world human mobility and consider intra-city spatial interaction as an imperative driver in the context of urban growth simulation. Specifically, the gravity model, which considers both the scale and distance effects of geographical locations within cities, is employed to characterize the connection between land areas using individual trajectory data from a macro perspective. It then becomes possible to integrate human mobility factors into a neural-network-based cellular automata (ANN-CA) for urban growth modeling in Beijing from 2013 to 2016. The results indicate that the proposed model outperforms traditional models in terms of the overall accuracy with a 0.60% improvement in Cohen's Kappa coefficient and a 0.41% improvement in the figure of merit. In addition, the improvements are even more significant in districts with strong relationships with the central area of Beijing. For example, we find that the Kappa coefficients in three districts (Chaoyang, Daxing, and Shunyi) are considerably higher by more than 2.00%, suggesting the possible existence of a positive link between intense human interaction and urban growth. This paper provides valuable insights into how fine-grained human mobility data can be integrated into urban growth simulation, helping us to better understand the human-land relationship.
作者关键词: cellular automata; urban growth simulation; human mobility; massive trajectories
地址: [Wang, Siying; Fei, Teng] Wuhan Univ, Sch Resource & Environm Sci, Wuhan 430079, Peoples R China.
[Wang, Siying; Li, Weifeng; Zhang, Anqi] Univ Hong Kong, Dept Urban Planning & Design, Hong Kong, Peoples R China.
[Li, Weifeng] Guangdong Hong Kong Macau Joint Lab Smart Cities, Hong Kong, Peoples R China.
[Du, Yunyan] Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
[Guo, Huagui] Fuzhou Univ, Sch Architecture & Urban Rural Planning, Fuzhou 350108, Peoples R China.
通讯作者地址: Du, YY (通讯作者)，Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Beijing 100101, Peoples R China.
电子邮件地址: email@example.com; firstname.lastname@example.org
版权所有 © 官方金沙娱场151_首页(welcome)