Estimation of subpixel temperature over a heterogeneous area using an endmember index based technique

Land surface temperature (LST) is a key parameter in numerous environmental studies. In order to lower the subpixel temperature estimation error caused by re-sampling of remote sensing data, a disaggregation method for subpixel temperature using the remote sensing endmember index based technique (DisEMI) was established in this study. To take an advantage of simultaneous, multi-resolution observations at coincident nadirs by the Advanced Spaceborne Thermal Emission Reflection Radiometer (ASTER) and the MODerate-resolution Imaging Spectroradiometer (MODIS), LST products from the two sensors were examined for a portion of suburb area in Beijing, China. The verified results indicate that the estimated temperature distribution was basically consistent with that of ASTER LST product(R² = 0.709 and RMSE = 2.702 K).