Temperature And Emissivity Separation Algortihm For Chinese Gaofen-5 Satelltie Data

In this paper, we proposed a temperature and emissivity separation (TES) algorithm for the simultaneous retrieval of land surface temperature and emissivity (LST&E) from the thermal infrared data of Chinese GaoFen-5 (GF-5) satellite's Multiple Spectral-Imager (MSI) payload. In order to improve the accuracy of the TES algorithm, a water vapor scaling (WVS) method for atmospheric correction was adopted. The Seebor V5.0 global atmospheric profile database and MODTRAN 5 were used to simulate the WVS coefficients. A total of 11 ASTER scenes were used to simulate the MSI images and concurrent ground measurements acquired in the HiWATER experiment were used to validate the algorithm. The results showed that the bias and root mean square error (RMSE) in the retrieved LST were 0.47 K and 1.70 K, respectively, and the absolute emissivity differences between MSI and the ground measurements were smaller than 0.01 for the four MSI TIR bands, which demonstrated that the proposed algorithm can be used to retrieve high accurate and high spatial resolution LST&E from GF-5 MSI data.