Large numbers of important researches have been done to estimate regional surface heat fluxes using remote sensing data over the past few decades. Due to the spatial heterogeneity of the land surface on a regional scale

many problems still need to be explored. Clearly

for landscapes with significant variability in vegetation cover

type

architecture

and moisture

due to the large contrasts in surface temperature

vegetation cover

surface roughness length and zero plane displacement height

the application of a land surface model to a mixed pixel causes significant errors. In this paper

we discussed the method of combining the land cover information and remotely sensed vegetation index provided by Landsat data and Moderate Resolution Imaging Spectroradiometer （MODIS） data to correct spatial-scale errors. It makes full use of the advantages of the temporal resolutions of MODIS data and spatial resolutions of Landsat data to construct a regional evapotranspiration model

which meets the requirements of spatial heterogeneity scale and makes the higher frequency of large area flux monitoring more operational.