Abstract:

As the most important component of the urban surface, impervious surface has been recognized as a main indicator of urban heat island effect. However, the quantitative relationship between impervious surface area (ISA) and land surface temperature (LST) is still unclear as different studies achieved different results. Therefore, the present paper selected six cities from different geographical regions of China to further investigate the quantitative relationship between ISA and LST. The cities involved are Shanghai, Guangzhou, Beijing, Changsha, Lanzhou and Fuzhou. The ISAs of the six cities were derived from Landsat ETM+ images by using linear spectral mixture analysis and the LSTs of the cities were retrieved from the thermal infrared band of the images. Multivariate regression analysis with a large amount of samples was implemented to examine quantitative relationship between ISA and LST. Results showed that the ISAs of the six cities were all positively correlated to the LST, but with an exponential relationship being the best fit model. The correlation coefficients of the exponential relationship were above 0.750 0 and could be up to 0.954 1. This suggested that the area with high percent ISA could accelerate LST rise and the temperature rise was higher than 0.600 to 1.700 ℃ compared to the area with low percent ISA. The weaker transpiration evaporation and lower vegetation cover are the main factors contributing to the higher LST rise in the high percent ISA area.

Key words: impervious surface, urban heat island, land surface temperature, remote sensing