Remote sensing-based estimation of soil moisture is crucial in many aspects including basinscale w ater resource management, irrigation scheduling, regional scale drought monitoring and crop yield forecasting. In this study, w e evaluate the potential of visible/thermal-infrared remote sensing in soil moisture estimation, by assessing the TVDI-based method and three categories of methods based on evaporative fraction/potential evaporation ratio ( EFM1, EFM2 and EFM3) . In combination w ith ASTER data set, soil moisture in middle reach of the Heihe River Basin is predicted by the above-mentioned four methods and validated by the ground-based measurements from eco-hydrological w ireless sensor netw ork and hydro meteorological observation netw ork in the middle reach of Heihe river basin.Results indicate that uncertainties arise from the empiricism of the TVDI-based method in the process ofdetermining dry and w et edges. On the other hand, the evaporation fraction/potential evaporation ratio methods can to some degree reduce the uncertainties, and among the three methods, EFM1 and EFM3 outperform EFM2. In addition, the thermal-infrared based methods require accurate soil parameters to reproduce the variation of soil moisture.