| 中国地级及以上城市网络结构韧性测度 |
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| 引用本文： | 魏石梅,潘竟虎.中国地级及以上城市网络结构韧性测度[J].地理学报,2021,76(6):1394-1407. |
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| 作者姓名： | 魏石梅 潘竟虎 |
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| 作者单位： | 西北师范大学地理与环境科学学院,兰州730070 |
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| 基金项目： | 国家自然科学基金项目(42071216);国家自然科学基金项目(41661025) |
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| 摘 要： | 随着城市间关系趋向于网络化发展以及外部急性冲击和慢性压力的增加,城市网络结构韧性作为衡量区域韧性的重要手段,致力于评估城市网络系统在面对突发故障或扰动时,能够抵御、吸收和恢复原有网络特征和重要功能的能力。以中国346个地级及以上城市为研究对象,采用2017年百度指数、腾讯人口迁徙大数据等,在构建信息、交通、经济和综合城市联系网络的基础上,从城市节点和网络层面对其层级性和匹配性进行测度,并对中断场景下网络的传输性和多样性进行分析,进而针对各网络从不同视角提出网络结构优化策略和建议。结果表明：① 2017年中国346个地级及以上城市的信息、交通、经济和综合联系网络整体上呈现以“胡焕庸线”为界的“东密西疏”的分布格局,但空间结构各有特点。② 信息、交通和经济三大网络的层级性排名依次为经济>信息>交通网络。大城市及省会城市因其信息技术的快速创新与传播、产业经济的高度发展与集聚及交通基础设施的快速配备与完善在网络中具有更高的层级。③ 信息、交通、经济三大网络均具有异配性特征。信息网络中高权重节点与低权重节点间的跨区域交流机会更多,因而具有最高的异配韧性。④ 信息网络的传输与多样韧性稍高于经济网络,远高于交通网络。同一城市节点的故障或中断在影响网络传输性的同时,也会累及网络的多样性。
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| 关 键 词： | 城市网络 网络结构韧性 空间分析 空间大数据 中国 |
| 收稿时间： | 2020-05-03 |
| 修稿时间： | 2021-04-14 |
Network structure resilience of cities at the prefecture level and above in China |
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| WEI Shimei,PAN Jinghu.Network structure resilience of cities at the prefecture level and above in China[J].Acta Geographica Sinica,2021,76(6):1394-1407. |
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| Authors: | WEI Shimei PAN Jinghu |
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| Institution: | College of Geography and Environmental Science, Northwest Normal University, Lanzhou 730070, China |
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| Abstract: | With the rapid development of information technology, the interweaving physical infrastructure and virtual urban networks show more abundant connotations. As one of the most effective indicators to measure regional resilience, urban network structure resilience focuses on the capacity of the urban network system to restore, maintain, or improve the original network characteristics and important functions when faced with external acute shock and chronic pressure. Therefore, evaluating the resilience of the urban network structure is of great significance for recognizing and understanding regional resilience. Taking 346 cities of China at the prefecture level and above as the research objects, this study constructed information, transportation, economic, and comprehensive connection networks based on the Baidu index, Tencent location services, and social statistics data. The resilience of the urban network was then measured and evaluated in four aspects: hierarchy, heterogeneity, transmissibility, and diversity. The last two properties are in interrupting simulation scenarios. Accordingly, the optimization strategies and suggestions for the network structure were put forward. Based on the results, the following conclusions can be drawn: (1) Although China's information, transportation, economic, and comprehensive networks among the 346 prefecture-level cities and above in 2017 presented a spatial pattern of "dense in the east and sparse in the west" with "Hu Huanyong Line" as the boundary, their spatial structures exhibit their own characteristics. (2) The hierarchy of information, transportation, and economic networks from strong to weak is in the following order: economic network > information network > transportation network. Large cities and provincial capital cities have a higher hierarchy in a network because of the rapid innovation and dissemination of information technology, the high development and agglomeration of industrial economy, and the rapid allocation and improvement of traffic infrastructures. (3) The three major networks of information, transportation, and economy are all heterogeneous. In the information network, there are more opportunities for cross-regional communication between high-weighted and low-weighted nodes, thereby exhibiting the highest heterogeneous resilience. (4) The transmissibility and diversity resilience of information network was slightly higher than those of the economic network and much higher than those of the transportation network. Failures or perturbations of a city have almost the same impact on network transmissibility and diversity. Cities that have a great impact on the resilience of China's urban network structure typically exhibit high centrality and control power. These cities not only have a higher level of economic development and a relatively sound transportation hub, but also exhibit superiority with regard to their geographical conditions and distribution of natural resources. |
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| Keywords: | urban network network structure resilience spatial analysis spatial big data China |
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