Today, the extraction of land surface temperature (LST) from satellite imagery for many environmental studies, particularly the applications related to water resources management over agricultural sites, is very important. The extracted LST can be used to check the status of plant growth and crop water demand management. Recently the OLI and TIR data sets from Landsat 8 were used in vegetation studies and surface temperature estimation. In this research, the variations of corn surface temperature during its growth stages were examined. In order to minimize the soil influence on canopy spectra, the SAVI were used. The emissivity was estimated by using thresholding on NDVI and vegetation fraction cover and surface temperature were assessed by using single channel algorithm. After that isothermal areas were detected using SAVI and thermal image. Finally, corn growth conditions were studied by examining surface temperature in growth stages. The comparison of results with ground data, show the average correlation efficiency more than 0.92 and average RMSE less than 1.5.