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Spatial Distribution Characteristics of Leisure Urban Spaces and the Correlation with Population Activity Intensity: A Case Study of Nanjing, China

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  • Xinyang Li

    (Department of Architecture, Faculty of Design and Architecture, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia)

  • Marek Kozlowski

    (Department of Architecture, Faculty of Design and Architecture, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia)

  • Sumarni Binti Ismail

    (Department of Architecture, Faculty of Design and Architecture, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia)

  • Sarah Abdulkareem Salih

    (Department of Architecture, Faculty of Design and Architecture, Universiti Putra Malaysia (UPM), Serdang 43400, Malaysia)

Abstract

The spatial distribution of Leisure Urban Spaces (LUSs) is closely linked to urban sustainability and residents’ quality of life. This study uses the Central Urban Area of Nanjing as the study area. Using POI and AOI data, the locations of LUS were precisely identified and categorized, including parks, squares, waterfront spaces, and leisure blocks. GIS spatial analysis methods, the nearest neighbor index, standard deviation ellipse, and kernel density estimation were used to analyze these spaces’ form, directivity, and density. Population activity intensity (PAI) data at various time points, collected by Baidu heat map, are correlated with LUS distribution through multiple linear regression analysis. (1) Parks and squares exhibit significant clustering tendencies, whereas waterfront spaces show weaker clustering, and leisure blocks are randomly distributed; (2) The central points of all types of LUS are located in the city center, extending from southeast to northwest, with parks and squares offering a broader range of services; (3) The overall LUS layout shows a ‘core and multiple points’ structure, with varying density patterns across different spaces, indicating concentrated and dispersed leisure areas; (4) The correlation between LUS distribution and PAI strengthens throughout the day and is greater on weekends than weekdays. Leisure blocks significantly enhance activity intensity, while parks have a limited effect, and waterfront spaces often show a negative correlation due to their remote locations. These results provide insights for future urban planning in Nanjing and underscore patterns in residents’ leisure activities.

Suggested Citation

  • Xinyang Li & Marek Kozlowski & Sumarni Binti Ismail & Sarah Abdulkareem Salih, 2024. "Spatial Distribution Characteristics of Leisure Urban Spaces and the Correlation with Population Activity Intensity: A Case Study of Nanjing, China," Sustainability, MDPI, vol. 16(16), pages 1-21, August.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:16:p:7160-:d:1460340
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    References listed on IDEAS

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    1. Shumei Zhang & Wenshi Zhang & Ying Wang & Xiaoyu Zhao & Peihao Song & Guohang Tian & Audrey L. Mayer, 2020. "Comparing Human Activity Density and Green Space Supply Using the Baidu Heat Map in Zhengzhou, China," Sustainability, MDPI, vol. 12(17), pages 1-14, August.
    2. Shu Feng & Liding Chen & Ranhao Sun & Zhiqiang Feng & Junran Li & Muhammad Sadiq Khan & Yongcai Jing, 2019. "The Distribution and Accessibility of Urban Parks in Beijing, China: Implications of Social Equity," IJERPH, MDPI, vol. 16(24), pages 1-14, December.
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    4. Lihua Chen & Yuan Ma, 2023. "How Do Ecological and Recreational Features of Waterfront Space Affect Its Vitality? Developing Coupling Coordination and Enhancing Waterfront Vitality," IJERPH, MDPI, vol. 20(2), pages 1-18, January.
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