IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i23p16130-d991944.html
   My bibliography  Save this article

Exploration of Urban Network Spatial Structure Based on Traffic Flow, Migration Flow and Information Flow: A Case Study of Shanxi Province, China

Author

Listed:
  • Sujuan Li

    (College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China
    Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

  • Xiaohui Zhang

    (College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China
    Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

  • Xueling Wu

    (School of Geographical Sciences, Shanxi Normal University, Taiyuan 030031, China)

  • Erbin Xu

    (College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China
    Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China)

Abstract

Urban coordinated development is an important aspect of regional development. The high-quality development of the Yellow River Basin cannot be separated from the coordinated and sustainable development of its inner cities. However, the network connection and spatial structure of cities in the Yellow River Basin have not received sufficient attention. Therefore, this study considered 11 prefecture-level cities in Shanxi Province, an underdeveloped region in the Yellow River Basin, as case areas and selected data on traffic, migration, and information flow that can better represent the urban spatial network structure and depict the spatial connection between cities. Based on the flow intensity calculation, flow direction judgment, spatial structure index, and social network analysis, the spatial structural characteristics of Shanxi Province were comprehensively analyzed from the perspective of flow space. The results showed the following: (1) Cities in Shanxi Province present a development trend of “one core and multiple centers.” The strong connection concerns mostly Taiyuan and radiates outward and presents a Chinese character “大”—shaped spatial connection pattern. (2) Taiyuan is the first connecting city of most cities in Shanxi Province, and the element flows particularly towards the central city and geographical proximity. (3) The urban spatial pattern of Shanxi Province presents an obvious unipolar development trend, where the network structure is an “absence-type pyramid.” The imbalance of the urban network connection strength is prominent in Shanxi Province, which is strong and numerous in the south but opposite in the north. (4) The overall network element flow density is low, the network connection is weak, Taiyuan agglomeration and radiation are the strongest, and Changzhi centrality ranks second, but the gap between Changzhi and Taiyuan is wide, and the polarization phenomenon is serious. Future research should focus on the rapidly developing provincial capital city of Taiyuan, coordinating the steady development of the central Shanxi city cluster, and driving the common development of neighboring cities.

Suggested Citation

  • Sujuan Li & Xiaohui Zhang & Xueling Wu & Erbin Xu, 2022. "Exploration of Urban Network Spatial Structure Based on Traffic Flow, Migration Flow and Information Flow: A Case Study of Shanxi Province, China," Sustainability, MDPI, vol. 14(23), pages 1-18, December.
  • Handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16130-:d:991944
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/23/16130/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/14/23/16130/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wenqian Ke & Wei Chen & Zhaoyuan Yu, 2017. "Uncovering Spatial Structures of Regional City Networks from Expressway Traffic Flow Data: A Case Study from Jiangsu Province, China," Sustainability, MDPI, vol. 9(9), pages 1-16, August.
    2. Duo Chai & Dong Zhang & Yonghao Sun & Shan Yang, 2020. "Research on the City Network Structure in the Yellow River Basin in China Based on Two-Way Time Distance Gravity Model and Social Network Analysis Method," Complexity, Hindawi, vol. 2020, pages 1-19, December.
    3. Feng Lan & Huili Da & Haizhen Wen & Ying Wang, 2019. "Spatial Structure Evolution of Urban Agglomerations and Its Driving Factors in Mainland China: From the Monocentric to the Polycentric Dimension," Sustainability, MDPI, vol. 11(3), pages 1-20, January.
    4. Edward J. Malecki, 2002. "The Economic Geography of the Internet’s Infrastructure," Economic Geography, Taylor & Francis Journals, vol. 78(4), pages 399-424, October.
    5. Yongjian Cao & Zhongwu Zhang & Jie Fu & Huimin Li, 2022. "Coordinated Development of Urban Agglomeration in Central Shanxi," Sustainability, MDPI, vol. 14(16), pages 1-17, August.
    6. Matsumoto, Hidenobu, 2004. "International urban systems and air passenger and cargo flows: some calculations," Journal of Air Transport Management, Elsevier, vol. 10(4), pages 239-247.
    7. Qiaowen Lin & Mengyu Xiang & Lu Zhang & Jinjiang Yao & Chao Wei & Sheng Ye & Hongmei Shao, 2021. "Research on Urban Spatial Connection and Network Structure of Urban Agglomeration in Yangtze River Delta—Based on the Perspective of Information Flow," IJERPH, MDPI, vol. 18(19), pages 1-20, September.
    8. Chengzhuo Wu & Li Zhuo & Zhuo Chen & Haiyan Tao, 2021. "Spatial Spillover Effect and Influencing Factors of Information Flow in Urban Agglomerations—Case Study of China Based on Baidu Search Index," Sustainability, MDPI, vol. 13(14), pages 1-17, July.
    9. Xiaokun Su & Chenrouyu Zheng & Yefei Yang & Yafei Yang & Wen Zhao & Yue Yu, 2022. "Spatial Structure and Development Patterns of Urban Traffic Flow Network in Less Developed Areas: A Sustainable Development Perspective," Sustainability, MDPI, vol. 14(13), pages 1-18, July.
    10. Huifang Liu & Xiaoyi Shi & Pengwei Yuan & Xiaoqing Dong, 2022. "Study on the Evolution of Multiple Network Resilience of Urban Agglomerations in the Yellow River Basin," Sustainability, MDPI, vol. 14(18), pages 1-24, September.
    11. Yong-Zhi Chang & Suo-Cheng Dong, 2016. "Evaluation of Sustainable Development of Resources-Based Cities in Shanxi Province Based on Unascertained Measure," Sustainability, MDPI, vol. 8(6), pages 1-18, June.
    12. Fang Wang & Mengyao Guo & Xi Guo & Fangqu Niu & Miao Zhang, 2021. "Research on the Hierarchical Spatial Structure of the Urban Agglomeration of the Yellow River Ji-Shaped Bend," Complexity, Hindawi, vol. 2021, pages 1-13, August.
    13. Xuewei Wang & Shuangli Ding & Weidong Cao & Dalong Fan & Bin Tang, 2020. "Research on Network Patterns and Influencing Factors of Population Flow and Migration in the Yangtze River Delta Urban Agglomeration, China," Sustainability, MDPI, vol. 12(17), pages 1-19, August.
    14. Xue, Dan & Yue, Li & Ahmad, Fayyaz & Draz, Muhammad Umar & Chandio, Abbas Ali & Ahmad, Munir & Amin, Waqas, 2022. "Empirical investigation of urban land use efficiency and influencing factors of the Yellow River basin Chinese cities," Land Use Policy, Elsevier, vol. 117(C).
    15. Juzi Xia & Gengxin Sun, 2022. "A Model of Urban Economic Resilience Development with Multisource Data Fusion," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-7, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Liang Ding & Zhiqian Xu & Juan Wang & Jun Zhou & Junshen Zhang & Xingyue Li, 2023. "Validation of the Basic Supporting Role of Traffic Networks in Regional Factor Flow: A Case Study of Zhejiang Province," Sustainability, MDPI, vol. 15(4), pages 1-18, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Bao Meng & Jifei Zhang & Xiaohui Zhang, 2023. "Detecting the Spatial Network Structure of the Guanzhong Plain Urban Agglomeration, China: A Multi-Dimensional Element Flow Perspective," Land, MDPI, vol. 12(3), pages 1-18, February.
    2. Fei Ma & Yujie Zhu & Kum Fai Yuen & Qipeng Sun & Haonan He & Xiaobo Xu & Zhen Shang & Yan Xu, 2022. "Exploring the Spatiotemporal Evolution and Sustainable Driving Factors of Information Flow Network: A Public Search Attention Perspective," IJERPH, MDPI, vol. 19(1), pages 1-25, January.
    3. You He & Alex de Sherbinin & Guoqing Shi & Haibin Xia, 2022. "The Economic Spatial Structure Evolution of Urban Agglomeration under the Impact of High-Speed Rail Construction: Is There a Difference between Developed and Developing Regions?," Land, MDPI, vol. 11(9), pages 1-17, September.
    4. Shengdong Nie & Hengkai Li, 2023. "Analysis of Construction Networks and Structural Characteristics of Pearl River Delta and Surrounding Cities Based on Multiple Connections," Sustainability, MDPI, vol. 15(14), pages 1-26, July.
    5. Zhangfeng Yao & Kunhui Ye & Liang Xiao & Xiaowei Wang, 2021. "Radiation Effect of Urban Agglomeration’s Transportation Network: Evidence from Chengdu–Chongqing Urban Agglomeration, China," Land, MDPI, vol. 10(5), pages 1-21, May.
    6. Liang Ding & Zhiqian Xu & Juan Wang & Jun Zhou & Junshen Zhang & Xingyue Li, 2023. "Validation of the Basic Supporting Role of Traffic Networks in Regional Factor Flow: A Case Study of Zhejiang Province," Sustainability, MDPI, vol. 15(4), pages 1-18, February.
    7. Ben Derudder, 2006. "On Conceptual Confusion in Empirical Analyses of a Transnational Urban Network," Urban Studies, Urban Studies Journal Limited, vol. 43(11), pages 2027-2046, October.
    8. Wang, Jiaoe & Du, Delin & Huang, Jie, 2020. "Inter-city connections in China: High-speed train vs. inter-city coach," Journal of Transport Geography, Elsevier, vol. 82(C).
    9. Yan Yu & Qianwen Han & Wenwu Tang & Yanbin Yuan & Yan Tong, 2018. "Exploration of the Industrial Spatial Linkages in Urban Agglomerations: A Case of Urban Agglomeration in the Middle Reaches of the Yangtze River, China," Sustainability, MDPI, vol. 10(5), pages 1-18, May.
    10. Rui Ding & Jun Fu & Yiling Zhang & Ting Zhang & Jian Yin & Yiming Du & Tao Zhou & Linyu Du, 2022. "Research on the Evolution of the Economic Spatial Pattern of Urban Agglomeration and Its Influencing Factors, Evidence from the Chengdu-Chongqing Urban Agglomeration of China," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    11. Alexander, D.W. & Merkert, R., 2021. "Applications of gravity models to evaluate and forecast US international air freight markets post-GFC," Transport Policy, Elsevier, vol. 104(C), pages 52-62.
    12. Li, Cunfang & Li, Danping & Zhang, Xiaoxu, 2019. "Why can China's coal resource-exhausted enterprises cross the district to transfer?," Resources Policy, Elsevier, vol. 60(C), pages 94-105.
    13. Jinzhao Song & Qing Feng & Xiaoping Wang & Hanliang Fu & Wei Jiang & Baiyu Chen, 2018. "Spatial Association and Effect Evaluation of CO 2 Emission in the Chengdu-Chongqing Urban Agglomeration: Quantitative Evidence from Social Network Analysis," Sustainability, MDPI, vol. 11(1), pages 1-19, December.
    14. Cariolle, Joël, 2021. "International connectivity and the digital divide in Sub-Saharan Africa," Information Economics and Policy, Elsevier, vol. 55(C).
    15. Renato A. Orozco Pereira & Ben Derudder, 2010. "Determinants of Dynamics in the World City Network, 2000-2004," Urban Studies, Urban Studies Journal Limited, vol. 47(9), pages 1949-1967, August.
    16. Xingxing Jin & Guojian Hu & Hailong Ding & Shilin Ye & Yuqi Lu & Jinhuang Lin, 2020. "Evolution of spatial structure patterns of city networks in the Yangtze River Economic Belt from the perspective of corporate pledge linkage," Growth and Change, Wiley Blackwell, vol. 51(2), pages 833-851, June.
    17. Yongwang Cao & Xiong He & Chunshan Zhou, 2023. "Characteristics and Influencing Factors of Population Migration under Different Population Agglomeration Patterns—A Case Study of Urban Agglomeration in China," Sustainability, MDPI, vol. 15(8), pages 1-25, April.
    18. Gong, Qiang & Wang, Kun & Fan, Xingli & Fu, Xiaowen & Xiao, Yi-bin, 2018. "International trade drivers and freight network analysis - The case of the Chinese air cargo sector," Journal of Transport Geography, Elsevier, vol. 71(C), pages 253-262.
    19. Ke Huang & Martin Dallimer & Lindsay C. Stringer & Anlu Zhang & Ting Zhang, 2021. "Does Economic Agglomeration Lead to Efficient Rural to Urban Land Conversion? An Examination of China’s Metropolitan Area Development Strategy," Sustainability, MDPI, vol. 13(4), pages 1-19, February.
    20. Van Asch, Thomas & Dewulf, Wouter & Kupfer, Franziska & Cárdenas, Ivan & Van de Voorde, Eddy, 2020. "Cross-border e-commerce logistics – Strategic success factors for airports," Research in Transportation Economics, Elsevier, vol. 79(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:14:y:2022:i:23:p:16130-:d:991944. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.