Health-promoting effects of sky gardens in high-density cities: Evidence from subjective restorative evaluation, eye tracking, and machine learning

Sky gardens are increasingly recognized as health-promoting potential strategies in high-density urban environments, yet how specific spatial elements contribute to restorative benefits remains insufficiently understood. This study investigates the relationships between spatial composition, visual attention, and psychological restoration by integrating subjective assessments, eye-tracking data, and machine learning analysis across nine sky gardens in Singapore. The results reveal that restorative effects are primarily driven by natural landscapes, public facilities, and waterscapes, while urban landscapes and high-rise elements tend to undermine restoration. Different spatial elements exhibit distinct restorative roles: natural landscapes support both immediate visual attraction and sustained engagement, whereas waterscapes and people presence mainly enhance short-term attention, and public facilities contribute to longer-term restorative experiences. Importantly, these effects are nonlinear, with identifiable threshold ranges beyond which restorative benefits may diminish. These findings provide evidence-based insights for designing health-promoting sky gardens, emphasizing the need to balance natural landscapes, functional facilities, and visual openness to optimize restorative effects. This study deepens understanding of restorative mechanisms in vertical urban spaces and offers practical guidance for improving environmental quality in dense cities.

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Publication Details

Journal
Journal of Urban Management
Published
2026-09-10
DOI
https://doi.org/10.1016/j.jum.2026.100570
Primary Topic
Urban Green Space and Health
Type
article
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article

Health-promoting effects of sky gardens in high-density cities: Evidence from subjective restorative evaluation, eye tracking, and machine learning

Hongwu Du, Yan Li
Journal of Urban Management
Urban Green Space and Health
article

Health-promoting effects of sky gardens in high-density cities: Evidence from subjective restorative evaluation, eye tracking, and machine learning

Hongwu Du, Yan Li
article en

Abstract

Sky gardens are increasingly recognized as health-promoting potential strategies in high-density urban environments, yet how specific spatial elements contribute to restorative benefits remains insufficiently understood. This study investigates the relationships between spatial composition, visual attention, and psychological restoration by integrating subjective assessments, eye-tracking data, and machine learning analysis across nine sky gardens in Singapore. The results reveal that restorative effects are primarily driven by natural landscapes, public facilities, and waterscapes, while urban landscapes and high-rise elements tend to undermine restoration. Different spatial elements exhibit distinct restorative roles: natural landscapes support both immediate visual attraction and sustained engagement, whereas waterscapes and people presence mainly enhance short-term attention, and public facilities contribute to longer-term restorative experiences. Importantly, these effects are nonlinear, with identifiable threshold ranges beyond which restorative benefits may diminish. These findings provide evidence-based insights for designing health-promoting sky gardens, emphasizing the need to balance natural landscapes, functional facilities, and visual openness to optimize restorative effects. This study deepens understanding of restorative mechanisms in vertical urban spaces and offers practical guidance for improving environmental quality in dense cities.

Journal of Urban ManagementVol. 16(2)
Shanghai Tongji Urban Planning and Design Institute (CN), Shandong Jianzhu University (CN), South China University of Technology (CN)
Sustainable cities and communities
Openalex Percentile: Top 11%
Urban Green Space and Health
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Health-promoting effects of sky gardens in high-density cities: Evidence from subjective restorative evaluation, eye tracking, and machine learning — Hongwu Du, Yan Li · Journal of Urban Management (2026) | TGRS Research Map | TGRS