Urban Network Spatial Connection and Structure in China Based on Railway Passenger Flow Big Data
文献类型：期刊论文
| 作者 | Li, Minmin1,2; Guo, Wenhua3,4; Guo, Renzhong1,2; He, Biao1,2; Li, Zhichao5; Li, Xiaoming1,2; Liu, Wenchao3,4; Fan, Yong1,2 |
| 刊名 | LAND
 |
| 出版日期 | 2022-02-01 |
| 卷号 | 11期号:2页码:18 |
| 关键词 | big data of railway passenger flow weighted average travel time railway network density economic connection model spatial interaction |
| DOI | 10.3390/land11020225 |
| 通讯作者 | He, Biao(hebiao@szu.edu.cn) |
| 英文摘要 | China's transportation industry has made great achievements in the past 40 years of reform and opening up. At the same time, it has gradually accumulated a series of problems. These problems have led to closer and more complex social and economic connection within and between regions of different scales. The existing research only carries out the characteristic analysis of urban network spatial connection and pattern from a single perspective such as "flow space" theory, spatial interaction model and accessibility method, and fails to accurately describe the complex socio-economic relations between regions. Based on the big data of railway passenger flow, this study selected weighted average travel time, railway network density, and the economic connection model to express the urban network spatial connection and structure of China in 2016 from the perspectives of time, space, and interaction. In 2016, the accessibility, connectivity, and total urban external economic connection of the railway network showed a trend of declining from the east to the west. The top 50 cities ranked by interurban economic connection were all located in the central and eastern regions and showed "diamond shape" distribution characteristics. The four diamond-shaped pairs were Beijing-Tianjin-Hebei, Yangtze River Delta, Pearl River Delta, and Chengyu urban agglomerations. This shape was basically in line with the T-shaped space that has existed for a long time in China's regional development. The accessibility, connectivity, and total external economic connection of national-level urban agglomerations were greater than those of regional-level urban agglomerations, and far greater than those of local-level urban agglomerations. The results showed that there was a mismatch between the layout of the railway network and the population. It will still be necessary to focus on strengthening the construction of transportation infrastructure in urban agglomerations and densely populated areas in the future. This study enriches the "flow space" theory, more fully describes urban network spatial connection and structure in China by considering the three perspectives of time, space, and interaction, and can provides reasonable suggestions for the development of national comprehensive three-dimensional transportation network planning, regional spatial structure optimization, and sustainable development. |
| WOS关键词 | ACCESSIBILITY ; TRANSPORT ; MODEL |
| 资助项目 | Humanity and Social Science Youth Foundation of the Ministry of Education of China[19YJCZH081] ; Open Fund of the Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources[KF-2020-05-013] ; Open Fund of the Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources[KF-2020-05-035] |
| WOS研究方向 | Environmental Sciences & Ecology |
| 语种 | 英语 |
| WOS记录号 | WOS:000763724600001 |
| 出版者 | MDPI |
| 资助机构 | Humanity and Social Science Youth Foundation of the Ministry of Education of China ; Open Fund of the Key Laboratory of Urban Land Resources Monitoring and Simulation, Ministry of Natural Resources |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/171612]  |
| 专题 | 中国科学院地理科学与资源研究所 |
| 通讯作者 | He, Biao |
| 作者单位 | 1.Minist Nat Resources, Key Lab Urban Land Resources Monitoring & Simulat, Shenzhen 518060, Peoples R China 2.Shenzhen Univ, Sch Architecture & Urban Planning, Res Inst Smart Cities, Shenzhen 518060, Peoples R China 3.Minist Nat Resources Peoples Republ China, Informat Ctr, Beijing 100036, Peoples R China 4.Minist Nat Resources, Technol Innovat Ctr Terr & Spatial Big Data, Beijing 100036, Peoples R China 5.Chinese Acad Sci, Inst Geog Sci & Nat Resources Res, Key Lab Land Surface Pattern & Simulat, Beijing 100101, Peoples R China |
| 推荐引用方式 GB/T 7714 | Li, Minmin,Guo, Wenhua,Guo, Renzhong,et al. Urban Network Spatial Connection and Structure in China Based on Railway Passenger Flow Big Data[J]. LAND,2022,11(2):18. |
| APA | Li, Minmin.,Guo, Wenhua.,Guo, Renzhong.,He, Biao.,Li, Zhichao.,...&Fan, Yong.(2022).Urban Network Spatial Connection and Structure in China Based on Railway Passenger Flow Big Data.LAND,11(2),18. |
| MLA | Li, Minmin,et al."Urban Network Spatial Connection and Structure in China Based on Railway Passenger Flow Big Data".LAND 11.2(2022):18. |
入库方式： OAI收割
来源：地理科学与资源研究所
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