The urban thermal environment is an important element for the urban ecological environment and climate. As megacities are affected by severe thermal environment, this paper selected Landsat 8 to retrieve land surface temperature (LST) studying the thermal environment of five megacities in China including Beijing, Shanghai, Guangzhou, Tianjin, and Chengdu. Three methods have been applied, quantifying the surface urban heat island intensity, landscape pattern metrics, and spatial autocorrelation. Three main conclusions have been drawn as follows. First, high-LST area is located in the central urban area. Second, the medium-temperature region is the most prevalent. The class-based and the landscape-based metrics can detect the pattern of thermal landscape. The fragmentation is low both in low and high temperature level classes. Third, global Moran’s suggests there is spatial clustering of thermal landscape. Local Moran’s map was able to detect several high-high and low-low clusters, which are the main types of thermal landscape.