Temperature and emissivity separation algorithm for TASI airborne thermal hyperspectral data

This paper proposed a modified TES algorithm for retrieving land surface temperature and emissivity (LST&E) from Thermal Airborne Spectrographic Imager (TASI) hyperspectral data and the results were validated with in situ ground measurements. Firstly, the atmospheric correction of TASI data was performed by MODTRAN model with atmospheric profile extracted from NCEP data which was modified by local meteorological data. Then, the S-G filter was used to smooth the spectral data in order to reduce the noise effect of TASI data. Finally, the Temperature and Emissivity Separation (TES) algorithm was modified to retrieving LST&E from TASI data. The validation results indicated that the derived LST agreed with the ground LSTs well with RMSE lower than 1.5K, and the retrieved emissivity curve showed a good agreement with ground LSEs measured by an Fourier Transform Infrared (FTIR) spectroradiometer.