Using Local Climate Zones to investigate Spatio-temporal evolution of thermal environment at the urban regional level: A case study in Xi'an, China

2021 ◽  
pp. 103495
Author(s):  
Bing Han ◽  
Zhixing Luo ◽  
Yan Liu ◽  
Tengyue Zhang ◽  
Liu Yang
Urban Climate ◽  
2018 ◽  
Vol 24 ◽  
pp. 567-576 ◽  
Author(s):  
Ran Wang ◽  
Chao Ren ◽  
Yong Xu ◽  
Kevin Ka-Lun Lau ◽  
Yuan Shi

2019 ◽  
Author(s):  
Parth Bansal

This study was conceptualized to investigate differences in surface temperature profile of Local Climate Zones (LCZ) classes in different seasonal conditions. Manhattan was selected as case study due to its dense, but heterogeneous built-up profile and presence of green area which formed the baseline for temperature comparison. However, this study failed to find significant results, in terms of the distinct Urban Heat Island (UHI) feature often reported in literature. Instead, this study suggests that in the case of Manhattan UHI is predominantly within ± 0.5 C° except during summer season. In summer season, where more difference in built and green LCZ is observed, the noise in data, defined by standard deviation of surface temperature in the class, is also higher. Thus, our study concludes that Landsat based surface temperature should be used with extreme caution to investigate UHI since most imagery is taken during day time.


Atmosphere ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 936
Author(s):  
Hai Yan ◽  
Shimin Yang ◽  
Xiaohui Guo ◽  
Fan Wu ◽  
Renwu Wu ◽  
...  

At present, conflicts between urban development and the climate environment are becoming increasingly apparent under rapid urbanization in China. Revealing the dynamic mechanism and controlling factors of the urban outdoor thermal environment is the necessary theoretical preparation for regulating and improving the urban climate environment. Taking Hangzhou as an example and based on the local climate zones classification system, we investigated the effects of land cover composition and structure on temperature variability at the local scale. The measurement campaign was conducted within four local climate zones (LCZ 2, 4, 5, and LCZ 9) during 7 days in the summer of 2018. The results showed that the temperature difference within the respective LCZ was always below 1.1 °C and the mean temperature difference between LCZs caused by different surface physical properties was as high as 1.6 °C at night. Among four LCZs, LCZ 2 was always the hottest, and LCZ 9 was the coolest at night. In particular, the percentage of pervious surface was the most important land cover feature in explaining the air temperature difference. For both daytime and nighttime, increasing the percentage of pervious surface as well as decreasing the percentage of impervious surface and the percentage of building surface could lower the local temperature, with the strongest influence radius range from 120 m to 150 m. Besides, the temperature increased with the SVF increased at day and opposite at night.


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