IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v17y2025i6p2376-d1608052.html
   My bibliography  Save this article

Exploring Connectivity Dynamics in Historical Districts of Mountain City: A Case Study of Construction and Road Networks in Guiyang, Southwest China

Author

Listed:
  • Zhixin Lin

    (College of Forestry, Guizhou University, Guiyang 550025, China)

  • Zongsheng Huang

    (College of Architecture and Urban Planning, Guizhou University, Guiyang 550025, China)

  • Huiwen Xiang

    (Division of Landscape Architecture, Department of Architecture, The University of Hong Kong, Hong Kong SAR, China)

  • Shaowei Lu

    (PowerChina Guiyang Engineering Co., Ltd., Guiyang 550081, China)

  • Yuanduo Chen

    (College of Forestry, Guizhou University, Guiyang 550025, China)

  • Jiachuan Yang

    (College of Forestry, Guizhou University, Guiyang 550025, China
    College of Architecture and Urban Planning, Guizhou University, Guiyang 550025, China)

Abstract

As urbanization accelerates globally, preserving and developing historical cultural districts is increasingly critical, especially in areas with unique historical and cultural value. To understand the development of urban construction and the diachronic and spatial patterns of development, this paper focuses on Guiyang, a key transportation hub in Southwest China connected to Southeast Asia. It examines the historical districts from four representative periods: the early Ming Dynasty (1413–1420), the early Qing Dynasty (1616–1626), the Republican era (1912–1949), and the 1980s (1980–1990). Employing complex network analysis, the study investigates the changes in the connectivity characteristics of construction land and road networks. Key findings reveal: (1) Stability: The construction land networks stability decreased steadily from the early Ming period to the 1980s, whereas the road network density exhibited a wave-like decline. (2) Centrality: The construction land networks centrality decreased linearly, and the road network density exhibited a wave-like decrease. (3) Vulnerability: Both networks showed increased vulnerability, with fluctuations in the road network during the early Qing period, but generally reduced vulnerability. The analysis also indicates that changes in the connectivity of Guiyang’s historical district construction land and road networks are influenced by shifts in social structures, improvements in productivity, and the physical geography of the area. In mountainous cities with limited terrain, urban forms have transitioned from single-center aggregation to multi-center aggregation, and areas where administrative expansion is not feasible have adopted compact spatial development strategies. The application of complex network analysis has proven effective in urban spatial studies, revealing that changes in construction land and road networks reflect multifaceted internal transformations in society, politics, economy, military, and culture, significantly impacting the formation of a diverse yet unified national identity. Based on these findings, this paper offers recommendations for the planning and development of mountainous cities globally.

Suggested Citation

  • Zhixin Lin & Zongsheng Huang & Huiwen Xiang & Shaowei Lu & Yuanduo Chen & Jiachuan Yang, 2025. "Exploring Connectivity Dynamics in Historical Districts of Mountain City: A Case Study of Construction and Road Networks in Guiyang, Southwest China," Sustainability, MDPI, vol. 17(6), pages 1-20, March.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:6:p:2376-:d:1608052
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/17/6/2376/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/17/6/2376/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. M. E. J. Newman & D. J. Watts, 1999. "Scaling and Percolation in the Small-World Network Model," Working Papers 99-05-034, Santa Fe Institute.
    2. Manfred Perlik & Andrea Membretti, 2018. "Migration by Necessity and by Force to Mountain Areas: An Opportunity for Social Innovation," Post-Print hal-01992189, HAL.
    3. Wenhai Zhang & Jiang Xin, 2023. "Green Spaces and the Spontaneous Renewal of Historic Neighborhoods: A Case Study of Beijing’s Dashilar Community," Sustainability, MDPI, vol. 15(24), pages 1-27, December.
    4. Zihan Chen & Su Liu & Wei Liao & Junxue Zhang, 2023. "Construction of Security Pattern for Historical Districts in Cultural Landscape Based on MCR Model: A Case Study of Chaozong Street, Changsha City," Sustainability, MDPI, vol. 15(13), pages 1-17, July.
    5. Qiyan Wu & Jianquan Cheng, 2019. "A temporally cyclic growth model of urban spatial morphology in China: Evidence from Kunming Metropolis," Urban Studies, Urban Studies Journal Limited, vol. 56(8), pages 1533-1553, June.
    6. Jun Zhang & Xiong He & Xiao-Die Yuan, 2020. "Research on the relationship between Urban economic development level and urban spatial structure—A case study of two Chinese cities," PLOS ONE, Public Library of Science, vol. 15(7), pages 1-14, July.
    7. Danjie Shen & Shujing Dong, 2022. "Transition of Urban Morphology in the Mountainous Areas Since Early-Modern Times from the Perspective of Urban Historic Landscape—A GIS Tools and Historical Map Translation Approach," Sustainability, MDPI, vol. 14(19), pages 1-21, October.
    Full references (including those not matched with items on IDEAS)

    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. Vinayak, & Raghuvanshi, Adarsh & kshitij, Avinash, 2023. "Signatures of capacity development through research collaborations in artificial intelligence and machine learning," Journal of Informetrics, Elsevier, vol. 17(1).
    2. Lahtinen, Jani & Kertész, János & Kaski, Kimmo, 2005. "Sandpiles on Watts–Strogatz type small-worlds," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 349(3), pages 535-547.
    3. Bahram Zikirya & Yueqing Xing & Chunshan Zhou, 2024. "The Matching Relationship Between the Distribution Characteristics of High-Grade Tourist Attractions and Spatial Vitality in Xinjiang," Sustainability, MDPI, vol. 16(21), pages 1-17, October.
    4. Liu, Run-Ran & Chu, Changchang & Meng, Fanyuan, 2023. "Higher-order interdependent percolation on hypergraphs," Chaos, Solitons & Fractals, Elsevier, vol. 177(C).
    5. Xu, Jiwei & Li, Jincheng & Han, Zhen & Zhu, Peican, 2024. "Coupled epidemic dynamics with awareness heterogeneity in multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    6. Lee Fleming & Charles King & Adam I. Juda, 2007. "Small Worlds and Regional Innovation," Organization Science, INFORMS, vol. 18(6), pages 938-954, December.
    7. Dorso, Claudio O. & Medus, Andrés & Balenzuela, Pablo, 2017. "Vaccination and public trust: A model for the dissemination of vaccination behaviour with external intervention," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 433-443.
    8. Xenikos, D.G. & Constantoudis, V., 2023. "Weibull dynamics and power-law diffusion of epidemics in small world 2D networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 617(C).
    9. Floortje Alkemade & Carolina Castaldi, 2005. "Strategies for the Diffusion of Innovations on Social Networks," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 3-23, February.
    10. Veronica Polin & Laura Cavalli & Matteo Spinazzola, 2023. "Bottom-Up Initiatives for Sustainable Mountain Development in Italy: An Interregional Explorative Survey," Sustainability, MDPI, vol. 16(1), pages 1-30, December.
    11. Shen, Xiaoda & Wang, Zhigang & Deng, Ye & Wu, Jun, 2024. "Spatial network disintegration with heterogeneous cost," Chaos, Solitons & Fractals, Elsevier, vol. 187(C).
    12. Shlomo Angel & Patrick Lamson-Hall & Alejandro Blei & Sharad Shingade & Suman Kumar, 2021. "Densify and Expand: A Global Analysis of Recent Urban Growth," Sustainability, MDPI, vol. 13(7), pages 1-28, March.
    13. Huo, Liang’an & Song, Naixiang, 2016. "Dynamical interplay between the dissemination of scientific knowledge and rumor spreading in emergency," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 461(C), pages 73-84.
    14. Mark Newman, 1999. "Small Worlds: The Structure of Social Networks," Working Papers 99-12-080, Santa Fe Institute.
    15. Shen, Ai-Zhong & Guo, Jin-Li & Wu, Guo-Lin & Jia, Shu-Wei, 2018. "The agglomeration phenomenon influence on the scaling law of the scientific collaboration system," Chaos, Solitons & Fractals, Elsevier, vol. 114(C), pages 461-467.
    16. Walter Quattrociocchi & Guido Caldarelli & Antonio Scala, 2014. "Self-Healing Networks: Redundancy and Structure," PLOS ONE, Public Library of Science, vol. 9(2), pages 1-7, February.
    17. I. Vieira & R. Cheng & P. Harper & V. Senna, 2010. "Small world network models of the dynamics of HIV infection," Annals of Operations Research, Springer, vol. 178(1), pages 173-200, July.
    18. Paolo Zeppini & Koen Frenken, 2015. "Networks, Percolation, and Demand," Department of Economics Working Papers 38/15, University of Bath, Department of Economics.
    19. Gancio, Juan & Rubido, Nicolás, 2022. "Critical parameters of the synchronisation's stability for coupled maps in regular graphs," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    20. Liu, Hao & Chen, Xin & Huo, Long & Zhang, Yadong & Niu, Chunming, 2022. "Impact of inter-network assortativity on robustness against cascading failures in cyber–physical power systems," Reliability Engineering and System Safety, Elsevier, vol. 217(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:17:y:2025:i:6:p:2376-:d:1608052. 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.