Modified and Adaptation of SEBAL Methodology for Estimating LSE from LDCM Data: Fars Province, Iran

Land Surface Emissivity (LSE) is an important intrinsic property of materials which is variable through physical parameters and it is dependent to the Spectral Response Function (SRF) and the effective wavelength of channel. Surface Energy Balance Algorithm for Land (SEBAL) is one of the most widely applied models which is comprised of twenty-five sub-models that calculate different surface variables such as LSE and LST. This algorithm used within 3-14 μm and 8-14 μm spectral domain. Obviously, using of the broadband emissivity in one channel instead of the narrowband emissivity lead to large errors on the surface parameters. This study investigates the effects of SRF and effective wavelength on SEBAL-based LSE estimation method, MLSESEBAL, in the narrow domain of TIRS bands of LDCM. For comparison and validation of MLSESEBAL, it compared to three common LSE estimation methods and LSE product of ASTER as a reference, respectively. The results showed that if there is little difference in the effective wavelength between broadband and narrowband, the LSE estimation is almost identical in the non-vegetated area and there is no significant difference, while it is non-negligible in the vegetated area. In contrast, if there is a relatively large difference between the effective wavelength and SRF between them, in this case, areas with vegetation and no vegetation have the same performance and the greatest difference in LSE estimation. Moreover, the validation results of MLSESEBAL method showed that the RMSE of LSE are 1.59% and 1.21% in thermal band 10 of the first and second examined scenes, respectively. As well as, for the band 11, the error values are 1.56% and 0.98% in the two examined scenes, respectively.