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The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region

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  • Runde Fu

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    The Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Xinhuan Zhang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

  • Degang Yang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    The Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Tianyi Cai

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China
    The Graduate School, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Yufang Zhang

    (State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi 830011, China)

Abstract

Creating a vital and lively urban environment is an inherent requirement of urban sustainable development, and understanding urban vibrancy is helpful for urban development policy making. The urban vibrancy theory needs more empirical supplementation and more evidence for the effect of the built environment on urban vibrancy. We use multisource urban spatial information data, including real-time population distribution (RPD) data and small catering business (SCB) data; quantitatively measure urban vibrancy; and build a comparative framework to explore the effect of the built environment on the urban vibrancy of a northwestern emerging city in China. The results demonstrate that the two urban vibrancy metrics present a spatial distribution pattern that is high in the south and low in the north areas of the city with significant spatial aggregation. Land-use intensity and diversity have strong positive effects on urban vibrancy but present a different pattern of effects on the two vibrancy measures. The influences on urban vibrancy of distance to the district center and distance to the nearest commercial complex are spatially complementary in the study area, and the effect of accessibility factors is weak. Our findings suggest that a somewhat cautious approach is required in the application of these classical planning theories to Urumqi.

Suggested Citation

  • Runde Fu & Xinhuan Zhang & Degang Yang & Tianyi Cai & Yufang Zhang, 2021. "The Relationship between Urban Vibrancy and Built Environment: An Empirical Study from an Emerging City in an Arid Region," IJERPH, MDPI, vol. 18(2), pages 1-20, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:2:p:525-:d:477898
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    References listed on IDEAS

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    1. Katherine Kenyon Henderson & Yan Song, 2008. "Can nearby open spaces substitute for the size of a property owner's private yard?," International Journal of Housing Markets and Analysis, Emerald Group Publishing Limited, vol. 1(2), pages 147-165, June.
    2. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    3. Yu Liu & Xi Liu & Song Gao & Li Gong & Chaogui Kang & Ye Zhi & Guanghua Chi & Li Shi, 2015. "Social Sensing: A New Approach to Understanding Our Socioeconomic Environments," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(3), pages 512-530, May.
    4. Shiwei Lu & Chaoyang Shi & Xiping Yang, 2019. "Impacts of Built Environment on Urban Vitality: Regression Analyses of Beijing and Chengdu, China," IJERPH, MDPI, vol. 16(23), pages 1-16, November.
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    3. Yuan Lai & Jiatong Li & Jiachen Zhang & Lan Yan & Yifeng Liu, 2022. "Do Vibrant Places Promote Active Living? Analyzing Local Vibrancy, Running Activity, and Real Estate Prices in Beijing," IJERPH, MDPI, vol. 19(24), pages 1-19, December.
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    6. Hongyu Gong & Xiaozihan Wang & Zihao Wang & Ziyi Liu & Qiushan Li & Yunhan Zhang, 2022. "How Did the Built Environment Affect Urban Vibrancy? A Big Data Approach to Post-Disaster Revitalization Assessment," IJERPH, MDPI, vol. 19(19), pages 1-25, September.
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    9. Bahram Zikirya & Xiong He & Ming Li & Chunshan Zhou, 2021. "Urban Food Takeaway Vitality: A New Technique to Assess Urban Vitality," IJERPH, MDPI, vol. 18(7), pages 1-18, March.
    10. Kai Zhao & Jinhan Guo & Ziying Ma & Wanshu Wu, 2023. "Exploring the Spatiotemporal Heterogeneity and Stationarity in the Relationship between Street Vitality and Built Environment," SAGE Open, , vol. 13(1), pages 21582440231, February.
    11. Jilong Li & Shiping Lin & Niuniu Kong & Yilin Ke & Jie Zeng & Jiacheng Chen, 2024. "Nonlinear and Synergistic Effects of Built Environment Indicators on Street Vitality: A Case Study of Humid and Hot Urban Cities," Sustainability, MDPI, vol. 16(5), pages 1-29, February.
    12. Yibo Gao & Hongwei Wang & Suyan Yi & Deping Wang & Chen Ma & Bo Tan & Yiming Wei, 2021. "Spatial and Temporal Characteristics of Hand-Foot-and-Mouth Disease and Their Influencing Factors in Urumqi, China," IJERPH, MDPI, vol. 18(9), pages 1-17, May.

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