How to cool hot-humid (Asian) cities with urban trees? An optimal landscape size perspective

Research output: Contribution to journalJournal articleResearchpeer-review

  • Huiying Fan
  • Zhaowu Yu
  • Gaoyuan Yang
  • Tsz Yiu Liu
  • Tsz Ying Liu
  • Carmem Huang Hung
  • Vejre, Henrik
Urban areas typically experience higher temperatures compared to surrounding rural areas that is known as the urban heat island effect (UHI). Urban greenery is capable of mitigating the UHI by creating microclimates that are lower in temperature than their surroundings, which are known as urban cooling islands (UCI). Previous studies have proved the effectiveness of UCI from different perspectives. However, a specific optimal level of landscape patch size at a regional scale that can be implemented by urban planners has not been identified. In this study, we estimated the optimal patch size in seven selected hot-humid Asian cities with the help of Google Cloud Computing, Python Programming, as well as spatial and statistical analysis. A two-tier (two optimal patch sizes) distribution of the threshold value of efficiency (TVoE) of urban trees in this region was found. Eight landscape-level indexes were used to explore the variance of TVoE. The percentage of landscape (PLAND), edge density (ED), mean landscape shape index (Shape_MN), mean fractal dimension (FRAC_MN), largest patch index (LPI), and mean Euclidian nearest-neighbor distance (ENN_MN) were found to have no significant correlation with TVoE. While the average normalized difference vegetation index (NDVI_MN) and average background temperature (BGT_MN) were found to be highly associated with the variance in TVoE. Further, a concept model that can simulate the effects of NDVI_MN and BGT_MN was also proposed. These findings extend the understanding of the UCI effect of urban trees as well as providing a basis for scientific climate adaption planning in this region.
Original languageEnglish
JournalAgricultural and Forest Meteorology
Volume265
Pages (from-to)338-348
Number of pages11
ISSN0168-1923
DOIs
Publication statusPublished - 2019

ID: 209384233