Abstract
As the threat of urban heat island effect on human health continues to escalate, discussions on how to use landscape vegetation to mitigate high temperatures and improve outdoor thermal comfort have become important research topics. Although existing studies have explored the relationship between urban greenery and outdoor jogging activities, they are still understudied regarding the nonlinear effect and threshold of green cooling from two-dimensional and three-dimensional perspectives. Therefore, this study uses urban remote sensing and street view images to represent multi-dimensional urban greenery. Then, the InVEST model is used to simulate and calculate the cooling effect produced by green spaces. Finally, the multi-dimensional green indicators, the temperature cooling, and a series of control variables are input into the interpretable machine learning model to explore the relationship with jogging activities. The research reveals significant disparities in urban greenery, cooling effect, and jogging vitality between the city center and suburbs. It found that areas with higher cooling effects and street-scale greenery correlate with increased jogging vitality, highlighting the importance of vertical greening and shading in urban environments. This study can further provide references for the significance of urban landscapes at different scales and help urban managers build more climate-adaptive cities.
| Original language | English |
|---|---|
| Article number | 128655 |
| Journal | Urban Forestry and Urban Greening |
| Volume | 104 |
| DOIs | |
| Publication status | Published - Feb 2025 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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SDG 11 Sustainable Cities and Communities
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SDG 13 Climate Action
Keywords
- Heat mitigation
- InVEST
- Jogging activity
- Regression model
- Urban greenery
ASJC Scopus subject areas
- Forestry
- Ecology
- Soil Science
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