Abstract
The quantitative relationship between the spatial variation of building's height and the associated land surface temperature (LST) change in six Chinese megacities is investigated in this paper. The six cities involved are Beijing, Shanghai, Tianjin, Chongqing, Guangzhou, and Shenzhen. Based on both remote sensing and building footprint data, we retrieved the LST using a single-channel (SC) algorithm and evaluate the heating/cooling effect caused by building-height difference via correlation analysis. The results show that the spatial distribution of high-rise buildings is mainly concentrated in the center business districts, riverside zones, and newly built-up areas of the six megacities. In the urban area, the number and the floor-area ratio of high to super high-rise buildings (>24m) account for over 5% and 4.74%, respectively. Being highly urbanized cities, most of urban areas in the six megacities are associated with high LST. Ninety-nine percent of the city areas of Shanghai, Beijing, Chongqing, Guangzhou, Shenzhen, and Tianjin are covered by the LST in the range of 30.2~67.8°C, 34.8~50.4°C, 25.3~48.3°C, 29.9~47.2°C, 27.4~43.4°C, and 33.0~48.0°C, respectively. Building's height and LST have a negative logarithmic correlation with the correlation coefficients ranging from -0.701 to -0.853. In the building's height within range of 0~66m, the LST will decrease significantly with the increase of building's height. This indicates that the increase of building's height will bring a significant cooling effect in this height range. When the building's height exceeds 66m, its effect on LST will be greatly weakened. This is due to the influence of building shadows, local wind disturbances, and the layout of buildings.