Land surface temperature is one of the important parameters of geogas interaction and energy exhange.In order to obtain the land surface temperature data with high spatial resolution,this research improved a method of downscaling thermal infrared remote image, and was verified using Shanghai Landsat 8OLI/TIRS image as the data source. The Normalized Difference Vegetation Index (NDVI) was decomposed into low frequency layer,edge layer and detail layer, in which edge layer and detail layer are scaled up to the thermal infrared data.The proposed algorithm used simulated LST(270 m) as a downscaling data source to achieve downscaling LST(90 m),and compared with the classical thermal infrared downscaling method DisTrad algorithm and TsHARP algorithm.The results show that all three downscaling methods preserve the spatial characteristics of the original land surface temperature, but the DisTrad algorithm and the TsHARP algorithm add the detailed information that does not exist in original land surface temperature data. The improved three-layers decomposition model has a root mean square error of 0.913 K,which is 0.937 K and 0.832 K higher than the DisTrad method and the TsHARP method.