A Study on the Quantitative Relationship between Impervious Surface and Land Surface Temperature Based on Remote Sensing Technology

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 show that the ISAs of the six cities are all positively correlated to the LST, but with an exponential relationship being the best fit model. This suggests that the area with high percent ISA could accelerate LST rise. The weaker transpiration evaporation and lower vegetation cover are the main factors contributing to the higher LST rise in the high percent ISA area.