Quantifying the impact of urban trees on land surface temperature in global cities

环境科学 城市热岛 树(集合论) 气候变化 自然地理学 地理 大气科学 气象学 数学 生态学 地质学 生物 数学分析
作者
Tingting He,Yihua Hu,Andong Guo,Yuwei Chen,Jun Yang,Mengmeng Li,Maoxin Zhang
出处
期刊:Isprs Journal of Photogrammetry and Remote Sensing 卷期号:210: 69-79 被引量:19
标识
DOI:10.1016/j.isprsjprs.2024.03.007
摘要

Urban trees are not only a core component of natural infrastructure but also an effective way to mitigate urban heat with nature-based solutions. Comprehensively revealing the cooling effects of trees and their drivers is valuable for enhancing urban climate resilience and promoting sustainable development. While existing studies have investigated the cooling effects of two-dimensional characteristics of trees, there has been limited consideration of the effects of vertical structure, especially in various climatic zones across the globe. In this study, we employed the Google Earth Engine cloud platform and the random forest algorithm to comprehensively assess the impact of three-dimensional (3D) characteristics of trees on land surface temperature across 596 cities worldwide. Results suggest that LST is generally lower in tree-covered areas than their surrounding built-up land, especially in the summer, with an average decrease of about 2.13 °C. We also found a significant negative correlation between tree canopy height and LST (∼−0.83). Specifically, the mean LST decreases by about 0.16 ℃ for every 1m increase in tree height. Globally, the average cooling intensity of trees is 1.86 °C, and is about 1.06 °C higher in summer than in winter. It is worth noting that during winter, the cooling effect of trees is more pronounced closer to the equator. In addition, the 3D characteristics of trees contribute more significantly to cooling intensity compared to their surrounding environmental factors. This study not only fills a global knowledge gap regarding the impact of 3D features of trees on LST, but also provides valuable insights into urban planning and management in response to climate change.
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