Abstract
Urban expansion and the resulting three-dimensional building patterns have significant ecological impacts, particularly the urban heat island (UHI) effect. However, the influence of urban morphology on the thermal environment of a dense city is still not clear. This study investigates the diurnal and seasonal relationships between two-dimensional (2D) and three-dimensional (3D) urban morphology indicators with the remotely sensed land surface temperature (LST) in Hong Kong, a city characterized by extreme urban density and significant vertical development. Using a boosted regression tree (BRT) model, we analyze the spatial variation of LST during both hot and cold months, in daytime and nighttime, and evaluate the marginal impacts of selected 2D/3D indicators on LST. The results reveal pronounced spatial heterogeneity in LST, with high daytime temperatures concentrated in industrial areas and nighttime peaks shifting to commercial and residential zones. The relationships between urban form indicators and LST are complex and nonlinear, differing significantly between day and night. Among all indicators, the sky view factor (SVF) is identified as the most influential, with its marginal effect on LST shifting from positive to negative after a threshold of 0.75 in January daytime and 0.76 in January nighttime. Whereas in July, the SVF threshold decreases to 0.71 in daytime and 0.62 in nighttime. The marginal effect of building height shows a similar trend with 30 m threshold in January in both daytime and nighttime, while 21.57 m in daytime and 20.31 m in nighttime in July, proving a significant cooling benefit in daytime. This study provides urban planners with evidence-based guidelines for optimizing building design and layout to mitigate UHI, potentially through manipulating factors like SVF and building height. These insights can inform sustainable urban development strategies in highly dense cities worldwide.
| Original language | English |
|---|---|
| Article number | 101858 |
| Journal | Remote Sensing Applications: Society and Environment |
| Volume | 41 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 11 Sustainable Cities and Communities
Keywords
- Boosted regression tree
- Diurnally
- Land surface temperature
- Seasonally
- Urban morphology
ASJC Scopus subject areas
- Geography, Planning and Development
- Computers in Earth Sciences
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