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

Xinyang Li, Marek Kozlowski (), Sumarni Binti Ismail and Sarah Abdulkareem Salih
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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

Sustainability, 2024, vol. 16, issue 16, 1-21

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.

Keywords: leisure urban spaces; spatial distribution; population activity intensity; GIS spatial analysis; big data; Nanjing (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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Citations: View citations in EconPapers (1)

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