Comparison of the land surface temperature and emissivity separation method for hyperspectral thermal infrared measur ement

Land surface temperature and emissivity separation (TES) is a basic problem in various thermal infrared (TIR) imagery applications. However, TES is essentially a typical nondeterministic inverse problem. From the late 1990´s, a number of TES algorithms for hyperspectral TIR data have been developed based on various additional constrains. In this paper, different hyperspectral TIR TES methods, including spectral smoothness methods, downwelling radiance residual index (DRRI) method and linear spectral emissivity constraint (LSEC) method, were first recalled. Subsequently, the simulated hyperspectral TIR data were used to evaluate the performance of the TES method. The results shows that spectral smoothness method and DRRI method perform similarly, while the LSEC method may have better performance to retrieve land surface temperature and emissivity.