IDEAS home Printed from https://ideas.repec.org/a/gam/jlands/v12y2023i6p1260-d1174861.html
   My bibliography  Save this article

Which Spatial Elements Influence Waterfront Space Vitality the Most?—A Comparative Tracking Study of the Maozhou River Renewal Project in Shenzhen, China

Author

Listed:
  • Yating Fan

    (School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Da Kuang

    (School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Wei Tu

    (School of Architecture and Urban Planning, Shenzhen University, Shenzhen 518060, China)

  • Yu Ye

    (College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China
    Key Laboratory of Ecology and Energy-Saving Study of Dense Habitat (Tongji University), Ministry of Education, Shanghai 200092, China)

Abstract

Urban waterfront renewal, especially public space improvement, is important for regaining waterfront space vitality. However, existing studies constrained by sparse and hard-to-access data are hard to explore how changes in spatial elements during waterfront renewal would affect space vitality. Waterfront space vitality comprises social vitality represented by public behaviors and economic vitality represented by urban functional facilities. Taking the Maozhou River renewal project in China as an example, we collect spatial elements and vitality on corresponding periods in 2018 and 2020 (before and after the renewal construction) and use multiple linear regression models to assess the relationships. We find that the functional diversity (e.g., commercial and cultural facilities) and design quality (e.g., path density and the shoreline’s proximity to the water) are the two most influential spatial elements affecting space vitality during waterfront renewal. Overall, the use of two-time datasets has generated strong evidence for measuring waterfront revitalization.

Suggested Citation

  • Yating Fan & Da Kuang & Wei Tu & Yu Ye, 2023. "Which Spatial Elements Influence Waterfront Space Vitality the Most?—A Comparative Tracking Study of the Maozhou River Renewal Project in Shenzhen, China," Land, MDPI, vol. 12(6), pages 1-18, June.
    • Handle: RePEc:gam:jlands:v:12:y:2023:i:6:p:1260-:d:1174861
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2073-445X/12/6/1260/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2073-445X/12/6/1260/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Reid Ewing & Robert Cervero, 2010. "Travel and the Built Environment," Journal of the American Planning Association, Taylor & Francis Journals, vol. 76(3), pages 265-294.
    2. Mi Diao & Yi Zhu & Joseph Ferreira Jr & Carlo Ratti, 2016. "Inferring individual daily activities from mobile phone traces: A Boston example," Environment and Planning B, , vol. 43(5), pages 920-940, September.
    3. Weibull, Jorgen W., 1976. "An axiomatic approach to the measurement of accessibility," Regional Science and Urban Economics, Elsevier, vol. 6(4), pages 357-379, December.
    4. Ali Keyvanfar & Arezou Shafaghat & Sapura Mohamad & Mu’azu Mohammed Abdullahi & Hamidah Ahmad & Nurul Hidayah Mohd Derus & Majid Khorami, 2018. "A Sustainable Historic Waterfront Revitalization Decision Support Tool for Attracting Tourists," Sustainability, MDPI, vol. 10(2), pages 1-23, January.
    5. Dominique Peeters & Isabelle Thomas, 2000. "Distance predicting functions and applied location-allocation models," Journal of Geographical Systems, Springer, vol. 2(2), pages 167-184, July.
    6. Chris Jacobs-Crisioni & Piet Rietveld & Eric Koomen & Emmanouil Tranos, 2014. "Evaluating the Impact of Land-Use Density and Mix on Spatiotemporal Urban Activity Patterns: An Exploratory Study Using Mobile Phone Data," Environment and Planning A, , vol. 46(11), pages 2769-2785, November.
    7. Merje Feldman, 2000. "Urban Waterfront Regeneration and Local Governance in Tallinn," Europe-Asia Studies, Taylor & Francis Journals, vol. 52(5), pages 829-850.
    8. Tu, Wei & Cao, Rui & Yue, Yang & Zhou, Baoding & Li, Qiuping & Li, Qingquan, 2018. "Spatial variations in urban public ridership derived from GPS trajectories and smart card data," Journal of Transport Geography, Elsevier, vol. 69(C), pages 45-57.
    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. Li, Zhitao & Tang, Jinjun & Zhao, Chuyun & Gao, Fan, 2023. "Improved centrality measure based on the adapted PageRank algorithm for urban transportation multiplex networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    2. Yunzi Yang & Yuanyuan Ma & Hongzan Jiao, 2021. "Exploring the Correlation between Block Vitality and Block Environment Based on Multisource Big Data: Taking Wuhan City as an Example," Land, MDPI, vol. 10(9), pages 1-23, September.
    3. Yuting Chen & Bingyao Jia & Jing Wu & Xuejun Liu & Tianyue Luo, 2022. "Temporal and Spatial Attractiveness Characteristics of Wuhan Urban Riverside from the Perspective of Traveling," Land, MDPI, vol. 11(9), pages 1-21, August.
    4. Ding, Chuan & Cao, Xinyu & Yu, Bin & Ju, Yang, 2021. "Non-linear associations between zonal built environment attributes and transit commuting mode choice accounting for spatial heterogeneity," Transportation Research Part A: Policy and Practice, Elsevier, vol. 148(C), pages 22-35.
    5. Deng, Yiling & Zhao, Pengjun, 2022. "The impact of new metro on travel behavior: Panel analysis using mobile phone data," Transportation Research Part A: Policy and Practice, Elsevier, vol. 162(C), pages 46-57.
    6. Aston, Laura & Currie, Graham & Kamruzzaman, Md. & Delbosc, Alexa & Fournier, Nicholas & Teller, David, 2020. "Addressing transit mode location bias in built environment-transit mode use research," Journal of Transport Geography, Elsevier, vol. 87(C).
    7. Zhang, Mengzhu & Zhao, Pengjun, 2021. "Literature review on urban transport equity in transitional China: From empirical studies to universal knowledge," Journal of Transport Geography, Elsevier, vol. 96(C).
    8. Mehzabin Tuli, Farzana & Mitra, Suman & Crews, Mariah B., 2021. "Factors influencing the usage of shared E-scooters in Chicago," Transportation Research Part A: Policy and Practice, Elsevier, vol. 154(C), pages 164-185.
    9. John Stanley & Janet Stanley, 2023. "Improving Appraisal Methodology for Land Use Transport Measures to Reduce Risk of Social Exclusion," Sustainability, MDPI, vol. 15(15), pages 1-18, August.
    10. Marie Geraldine Herrmann-Lunecke & Cristhian Figueroa-Martínez & Francisca Parra Huerta & Rodrigo Mora, 2022. "The Disabling City: Older Persons Walking in Central Neighbourhoods of Santiago de Chile," Sustainability, MDPI, vol. 14(17), pages 1-19, September.
    11. Li, Jingjing & Kim, Changjoo & Sang, Sunhee, 2018. "Exploring impacts of land use characteristics in residential neighborhood and activity space on non-work travel behaviors," Journal of Transport Geography, Elsevier, vol. 70(C), pages 141-147.
    12. Ding, Chuan & Wang, Donggen & Liu, Chao & Zhang, Yi & Yang, Jiawen, 2017. "Exploring the influence of built environment on travel mode choice considering the mediating effects of car ownership and travel distance," Transportation Research Part A: Policy and Practice, Elsevier, vol. 100(C), pages 65-80.
    13. Van Acker, Veronique & Ho, Loan & Stevens, Larissa & Mulley, Corinne, 2020. "Quantifying the effects of childhood and previous residential experiences on the use of public transport," Journal of Transport Geography, Elsevier, vol. 86(C).
    14. Ding, Yu & Lu, Huapu, 2016. "Activity participation as a mediating variable to analyze the effect of land use on travel behavior: A structural equation modeling approach," Journal of Transport Geography, Elsevier, vol. 52(C), pages 23-28.
    15. Singleton, Patrick A. & Park, Keunhyun & Lee, Doo Hong, 2021. "Varying influences of the built environment on daily and hourly pedestrian crossing volumes at signalized intersections estimated from traffic signal controller event data," Journal of Transport Geography, Elsevier, vol. 93(C).
    16. Toşa, Cristian & Sato, Hitomi & Morikawa, Takayuki & Miwa, Tomio, 2018. "Commuting behavior in emerging urban areas: Findings of a revealed-preferences and stated-intentions survey in Cluj-Napoca, Romania," Journal of Transport Geography, Elsevier, vol. 68(C), pages 78-93.
    17. Liu, Yan & Wang, Siqin & Xie, Bin, 2019. "Evaluating the effects of public transport fare policy change together with built and non-built environment features on ridership: The case in South East Queensland, Australia," Transport Policy, Elsevier, vol. 76(C), pages 78-89.
    18. Yaxi Gong & Xiang Ji & Yuan Zhang & Shanshan Cheng, 2023. "Spatial Vitality Evaluation and Coupling Regulation Mechanism of a Complex Ecosystem in Lixiahe Plain Based on Multi-Source Data," Sustainability, MDPI, vol. 15(3), pages 1-32, January.
    19. Regine Gerike & Caroline Koszowski & Bettina Schröter & Ralph Buehler & Paul Schepers & Johannes Weber & Rico Wittwer & Peter Jones, 2021. "Built Environment Determinants of Pedestrian Activities and Their Consideration in Urban Street Design," Sustainability, MDPI, vol. 13(16), pages 1-21, August.
    20. Chetan Doddamani & M. Manoj, 2023. "Analysis of the influences of built environment measures on household car and motorcycle ownership decisions in Hubli-Dharwad cities," Transportation, Springer, vol. 50(1), pages 205-243, February.

    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:jlands:v:12:y:2023:i:6:p:1260-:d:1174861. 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.