Simultaneous Estimation Method of Land Surface Temperature and Emissivity Using Hyper-Spectral Thermal Infrared Observations

Abstract

This paper proposes a method for simultaneously estimating land surface temperature (LST) and spectral emissivity using hyper-spectral thermal infrared observations. The main approach is finding the value of LST and atmospheric condition which make estimated emissivity spectrum the most smooth. The proposed method could separate LST, spectral emissivity and atmosphetic effects simultaneously from only an observed radiance data. An evaluation function of the smoothness of emissivity spectrum was also developed. It is based on the characteristic of atmospheric spectrum shape and is robust against the measurement noise. The numerical simulation to verify the proposed method gave a root mean square error (RMSE) of LST of 0.7K and emissivity of 0.011. The method was also applied to Atmospheric Infrared Sounder (AIRS) observations.