The seasonal and annual impacts of landscape patterns on the urban thermal comfort using Landsat

Li Feng, Menmen Zhao, Yanan Zhou, Liujun Zhu, Huihui Tian

Research output: Contribution to journalArticleResearchpeer-review

38 Citations (Scopus)


The traditional in situ data based temperature-humidity indexes (THIs) have been widely used in the assessment of the quality of urban thermal environment, with the spatial details of thermal comfort currently unavailable. In this study, the THI is modified replacing the required in situ air temperature and relative humidity with remote sensing retrieved Land Surface Temperature and Normalized Difference Moisture Index, being the modified temperature-humidity index. The proposed remote sensing based index is then used to explore the spatio-temporal characteristics of urban thermal comfort, which are used to describe the urban thermal comfort grading in different seasons and the landscape metrics as well as to investigate the response of urban thermal comfort to landscape patterns seasonally and annually. The results show that at the macro scale, the impacts of landscape patterns on thermal comfort are the most important in summer with water bodies and built-up land being the most desirable and uncomfortable types, respectively. The opposite results are found in spring and winter despite the relatively less important effect in winter. At the micro scale, the variance contribution rate of the Percentage of Landscape to the MTHI is above 70%, and that of the Landscape Division Index and Aggregation Index is from 10% to 38.1%. It indicates that the composition of the landscape is the main factor affecting urban thermal comfort and is better than the landscape structure. The MTHI based on remote sensing data can monitor the spatial distribution of urban thermal comfort and is suitable to explain the reasons for the thermal comfort temporal variations.

Original languageEnglish
Article number105798
Number of pages12
JournalEcological Indicators
Publication statusPublished - Mar 2020


  • Landscape patterns
  • Modified temperature-humidity index (MTHI)
  • Remote sensing data
  • Spatio-temporal characteristics
  • Urban thermal comfort

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