A new flow-based centrality method for identifying statistically significant centers
文献类型：期刊论文
| 作者 | Wang, Xi4; Pei, Tao3,4; Song, Ci4; Chen, Jie; Shu, Hua2; Chen, Xiao4; Wu, Mingbo4 |
| 刊名 | SUSTAINABLE CITIES AND SOCIETY
 |
| 出版日期 | 2023-12-01 |
| 卷号 | 99页码:104984 |
| 关键词 | Urban centrality Urban agglomeration Spatial structure Geographical flows Spatial interaction |
| DOI | 10.1016/j.scs.2023.104984 |
| 产权排序 | 1 |
| 文献子类 | Article |
| 英文摘要 | Quantifying the centrality of places and identifying centers constitute the basis for assessing the urban spatial structure, which is essential for sustainable spatial planning. Both the existence and intensity of linkages contribute to the centrality of places. However, few centrality measures consider both aspects simultaneously. Additionally, the identification of centers often relies on specified minimum thresholds, which is subjective and arbitrary. To overcome these limitations, we propose a new flow-based centrality measure (MX-degree) inspired by the scientist's H-index, which effectively integrates flow volume and flow diversity automatically. Furthermore, we design a novel permutation strategy to test the significance of the MX-degree to identify the statistically significant centers. To demonstrate the validity of our method, we conduct a case study quantifying city centrality in China's two urban agglomerations: Beijing-Tianjin-Hebei (BTH) and Yangtze River Delta (YRD), based on population flow data. Specifically, the MX-degree outperforms other common centrality measures in reflecting cities' socioeconomic development levels. Significance tests show that the BTH region is dominated by the only statistically significant central city - Beijing, while the YRD region is more polycentric but with an uneven spatial distribution of central cities. Several implications for regional planning by the comparison of spatial structures are provided. |
| WOS关键词 | URBAN AGGLOMERATION ; LOS-ANGELES ; CHINA ; POLYCENTRICITY ; CONNECTIVITY ; PERSPECTIVE ; SUBCENTERS ; SYSTEM ; POWER |
| WOS研究方向 | Construction & Building Technology ; Science & Technology - Other Topics ; Energy & Fuels |
| WOS记录号 | WOS:001091088000001 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/199445]  |
| 专题 | 资源与环境信息系统国家重点实验室_外文论文 |
| 作者单位 | 1.Hubei Univ, Sch Comp Sci & Informat Engn, Wuhan 430062, Peoples R China 2.Jiangsu Ctr Collaborat Innovat Geog Informat Resou, Nanjing 210023, Peoples R China 3.Univ Chinese Acad Sci, Beijing 100049, Peoples R China 4.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, State Key Lab Resources & Environm Informat Syst, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Wang, Xi,Pei, Tao,Song, Ci,et al. A new flow-based centrality method for identifying statistically significant centers[J]. SUSTAINABLE CITIES AND SOCIETY,2023,99:104984. |
| APA | Wang, Xi.,Pei, Tao.,Song, Ci.,Chen, Jie.,Shu, Hua.,...&Wu, Mingbo.(2023).A new flow-based centrality method for identifying statistically significant centers.SUSTAINABLE CITIES AND SOCIETY,99,104984. |
| MLA | Wang, Xi,et al."A new flow-based centrality method for identifying statistically significant centers".SUSTAINABLE CITIES AND SOCIETY 99(2023):104984. |
入库方式： OAI收割
来源：地理科学与资源研究所
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