| 摘 要： |
The diverse urban features considerably influence land surface temperature (LST). Numerous studies have extensively investigated the impacts of 2D/3D urban features on LST. However, the diurnal impacts have not been comprehensively understood. Therefore, taking 1, 510 blocks within the 4th ring road of Beijing as samples, this study examined the influence of urban features (2D: low vegetation, water, and impervious surface; 3D: buildings and trees) on diurnal LST at the block scale based on ECOSTRESS LST using boosted regression tree (BRT) algorithm. The results showed that trees exhibit better cooling effects than low vegetation except at 3:09. The 3D features exhibited a greater impact on diurnal LST compared with 2D features, and it contributed strongly to daytime LST, which was 27.8 % on average higher than the 2D features. Building and tree densities had the greatest influence on daytime LST, while building height influenced nighttime LST the most. The impacts of key metrics on diurnal LST were nonlinear, and the relationship had diurnal variations. Taller buildings and trees were negatively correlated with LST during the daytime and transition time, but positively correlated with nighttime LST. The findings provide insights into landscape optimization strategies to improve block thermal comfort. |
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