Development a split window algorithm to estimate land surface temperature from Sentinel -3 satellite data

Land Surface Temperature (LST) is an important indicator of the study of energy balance models at the earthchr('39')s surface and the interactions between the Earth and the atmosphere on a regional and global scale. To date, different algorithms have been developed in the last few decades to determine the land surface temperature using various satellite images. In this study, a new split window method for estimating the land surface temperature using Sentinel-3A Satellite Radiometer (SLSTR) images is presented. The advantage of the proposed method is the introduction of atmospheric water vapor into the split window algorithm, which plays an important role in estimating the LST. The LST was calculated by the proposed method and three other split window algorithms. Then the results of the proposed method and three split window algorithms were compared with the ASTER, MODIS and Sentinel-3 LST products. The RMSE value of the proposed method for the study area of ​​East Tehran was 3.49, 1.22 and 1.26 K, respectively, compared to the ASTER, MODIS and Sentinel-3 LST products which is lower than the RMSE obtained from other split window algorithms. Also the proposed method and three split window algorithms were implemented for northwest of Isfahan and Kermanshah. For Kermanshah study area results were much better than the other two cases and also other methods which the RMSE of the proposed method was calculated to be 1.05 Kelvin while the RMSE of the other methods was 1.19, 1.28 and 1.56 Kelvin.