Retrieving Land Surface Emissivity from Thermal Hyperspectral Data Using physically Based Methods

Emissivity is one of the important physical properties of the Earth's surface and atmosphere. The knowledge of emissivity plays a valuable role in environment studies, urban climate, evapotranspiration, vegetation assessment, heat flux estimation, hydrological cycle, meteorology, and the interactions between land surface and atmosphere. Also, in order to accurate estimate of Land Surface Temperature, we need to obtain the emissivity. All of the emissivity estimating methods have been divided to semi empirical, Physical and temperature and emissivity separation methods. The aim of this study is to compare physically based methods of emissivity retrieval and finally obtain emissivity. This research consists of 6 main sections: At the first, the noise and water vapor absorption bands of HyTES hyperspectral image were removed, then 202 optimal bands were selected. In the next step, Approximate Expression of the Channel Radiance algorithm was applied. Then, other physically based algorithm that include Reference Channel Method, Emissivity Normalization Method, Emissivity Renormalization Method and Temperature-Independent Spectral Indices were applied. In order to evaluate these methods and for quality assessment, we used the satellite products that have been prepared by NASA. The results of the quality assessment show that RMSE for Approximate Expression of the Channel Radiance, Reference Channel, Temperature-Independent Spectral Indices, Emissivity Normalization Method and Renormalization Methods for band 180 are 0.05, 0.03, 0.05, 0.05 and 0.06 respectively.