Comparison of two hyperspectral temperature and emissivity separation methods: CBTES and ISSTES

Land surface temperature and emissivity separation is a critical process for land surface temperature (LST) retrieval from hyperspectral thermal infrared data. This paper compared the iterative spectrally smooth temperature/emissivity separation (ISSTES) and the correlation based temperature/emissivity separation (CBTES) methods for land surface temperature and emissivities retrievals from simulated data under typical atmospheres and different land surface covers. The paper also compared both methods for retrieving low emissivities with simulated data. For typical land cover types, neglecting the instrumental noise, ISSTES is more accurate than CBTES with root mean square error (RMSE) of LSTs less than 0.0005K for the ISSTES and 0.1K for the CBTES. For low emissivity material, considering instrumental noise, both methods have large errors, but the CBTES performs much better.