Evaluation and comparison of hyperspectral temperature and emissivity separation methods influenced by sensor spectral properties

In this article, great efforts are focused on the temperature and emissivity separation (TES) from hyperspectral thermal infrared data. Instead of proposing a new TES method, several published TES methods, including iterative spectrally smooth temperature–emissivity separation method (ISSTES), automatic retrieval of temperature and emissivity using spectral smoothness method (ARTEMISS), spectral smoothness method (SpSm), downwelling radiance residual index method (DRRI), and linear spectral emissivity constraint method (LSEC), are reviewed. The performances of these TES methods are analysed and compared under different instrument characteristics, including spectral shifting and full-width half-maximum broadening, with the simulated data. The results show that LSEC has the most robust and accurate performance. DRRI also has a good performance, in which a channel selection procedure is required before the use of this method. ISSTES, ARTEMISS, and SpSm show more sensitivities.