Accurate understanding and estimating Evapotranspiration (ET) is essential for understanding the mechanism of water cycle and water budget. ET has been analyzed by many researchers in worldwide while Ground-based ET has limiation in analyzing the spatio-temporal pattrens of ET. Thus, many researches have been conducted to represent the spatio-temporal variation of ET by using hydrometeorological variables estimated from remote sensing datasets. Previous remote sensing based ET algorithms, however, have disadvantage in that various hydrometeological input datasets were required. In this study, actual ET was estimated by MODIS-based RN and MS-PT algorithm requiring relatively less input data than previous method. The result confirmed that the observed RN and latent heat flux from the eddy-covariance based fluxtowers located at CFK and SMK showed high correlation with the estimated RN and ET. The average determination coefficients (R2) of ET estimated from satellite dataset over study periods were 0.77 (0.72-0.81) in Cheongmi (CFK) and 0.70 (0.67-0.78) in Sulma (SMK), respectively. Comparing with the actual ET of two flux tower sites, however, SMK showed more overestimated patterns than CFK due to the vegetation and radiation related errors.