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Exploring the Correlation between Block Vitality and Block Environment Based on Multisource Big Data: Taking Wuhan City as an Example

Author

Listed:
  • Yunzi Yang

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Yuanyuan Ma

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China)

  • Hongzan Jiao

    (Department of Urban Planning, School of Urban Design, Wuhan University, Wuhan 430072, China
    Engineering Research Center of Human Settlements and Environment of Hubei Province, Wuhan 430072, China)

Abstract

Block is the basic unit for studying the urban activities of residents, and block vitality is the concrete expression of urban dynamics at the block level. The quality of the block’s residential environment is a crucial medium to satisfy the residents’ pursuit of high-quality life; good block quality is essential for fostering the block vitality and further enhancing the overall vitality of the city. This study used the distribution density of cellular signaling data to quantify block vitality and constructed a block environment index system covering four dimensions—block accessibility, block function, block development degree, and human perception of block environment—innovatively introducing the elements of block environment from the human perspective. Considering the variability of block vitality between workdays and weekends, and between downtown and suburban blocks, this study used a geographically weighted regression model to show the mechanism of the spatial and temporal influence of indicators on block vitality, as well as to suggest how to enhance block vitality at different times of the day based on the influence mechanism. This study was conducted in Wuhan, China. The findings suggest that block vitality exhibited significant spatial and temporal heterogeneity. A high-vitality block can be created by enhancing the block’s accessibility, increasing the degree of block construction, and enriching the functional density and mix of functions in the block. A pleasantly green environment with a moderate degree of openness exerted a significant impact on promoting human activity and enhancing block vitality. The creation of high-vitality blocks should also consider the differences in the impact of various elements on block vitality between weekend and workday. For example, amid the surge in travel demand for education venues on weekends, enhancing the accessibility of blocks can significantly increase the vitality of blocks on weekends. We can truly realize the people-oriented approach to build a livable and high-vitality city by adapting to local conditions and time.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jlands:v:10:y:2021:i:9:p:984-:d:638080
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    References listed on IDEAS

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    Cited by:

    1. He Liu & Xueming Li, 2022. "Understanding the Driving Factors for Urban Human Settlement Vitality at Street Level: A Case Study of Dalian, China," Land, MDPI, vol. 11(5), pages 1-20, April.
    2. Yan Long & Siyu Hu & Zhengyuan Lu & Lianghao Cheng & Cairui Zhen & Jingmei Shao & Yuqiao Zheng & Xuehui Zhou & Jin Li & Yudi Lin & Shu Zhang & Yue Wang & Tianyue Luo & Haijuan Zhao & Xuejun Liu, 2024. "A Study on the Influence Mechanisms of Neighborhood Vitality and the Characteristics of Spatial and Temporal Differentiation in the Urban Fringe Areas of Wuhan City," Land, MDPI, vol. 13(11), pages 1-36, October.
    3. Xin Li & Yongsheng Qian & Junwei Zeng & Xuting Wei & Xiaoping Guang, 2021. "The Influence of Strip-City Street Network Structure on Spatial Vitality: Case Studies in Lanzhou, China," Land, MDPI, vol. 10(11), pages 1-17, October.
    4. Yi Peng & Xu Cui & Bingjie Yu & Runze Liu & Hong Li, 2025. "How 2D and 3D Built Environment Impact Urban Vitality: Evidence from Overhead-Level to Eye-Level Urban Form Metrics," Land, MDPI, vol. 14(5), pages 1-23, May.
    5. Yiming Liu & Xiangxiang Pan & Qing Liu & Guicai Li, 2023. "Establishing a Reliable Assessment of the Green View Index Based on Image Classification Techniques, Estimation, and a Hypothesis Testing Route," Land, MDPI, vol. 12(5), pages 1-14, May.
    6. Jing Huang & Xiao Hu & Jieqiong Wang & Andong Lu, 2023. "How Diversity and Accessibility Affect Street Vitality in Historic Districts?," Land, MDPI, vol. 12(1), pages 1-23, January.
    7. Jing Zhao & Wanyue Suo, 2024. "Research on the Construction and Application of a SVM-Based Quantification Model for Streetscape Visual Complexity," Land, MDPI, vol. 13(11), pages 1-27, November.

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