Land surface temperature (LST) and mean radiant temperature (MRT) are commonly used as proxies to evaluate urban heat environments. Many scholars use one of them to represent heat exposure when assessing the urban thermal environment. This research fills a research gap by analyzing two meteorological parameters simultaneously through correlation analysis, hotspot analysis, and the distinctive information they respectively express with the results of vulnerable population distribution based on the case of Linköping. Scatter plots are used to explore the correlation between LST and MRT, and hot spot analysis is applied to investigate their spatial patterns through the clusters of hot and cold spots. Furthermore, the distribution of vulnerable populations is assessed and visualized through a vulnerability index. The results show that there is a moderate positive linear correlation between the mean values of LST and MRT for the whole study area. They have different spatial patterns based on the results of the hot spot analysis. The comparison of different meteorological parameters to the vulnerability index also shows variations in high heat risk areas. All of these conclude that LST or MRT could, to some extent, be presented as references to each other; however, they cannot be used interchangeably as proxies for urban heat exposure. When developing urban thermal adaptation strategies, it is necessary for municipalities to select the parameters appropriately according to the purpose and requirements and to understand what the chosen parameters can and cannot convey.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-195801 |
Date | January 2023 |
Creators | Zhao, Pei |
Publisher | Linköpings universitet, Institutionen för tema, Linköpings universitet, Filosofiska fakulteten |
Source Sets | DiVA Archive at Upsalla University |
Language | English |
Detected Language | English |
Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
Format | application/pdf |
Rights | info:eu-repo/semantics/openAccess |
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