Estimation and Validation of Land Surface Temperature Using Chinese Geostationary FengYun Meteorological Satellite (FY-2D) Data in an Arid Region

This study calibrated a refined split-window algorithm for land surface temperature (LST) retrieval based on Fengyun-2D (FY-2D) meteorological satellite. First, FY-2D emissivity (LSE) was predicted from Moderate-resolution Imaging Spectroradiometer (MODIS) LSE sensors spectral similarities. The retrieved LST data were validated in an arid region where the traditional generally performed unsatisfactorily. Validation results show R 2 (coefficient of determination) and RMSE (root mean square error) values range 0.53–0.67 2.86–6.21 K, respectively, against ground observed LST. Better retrievals over vegetated regions with value ~2.8 K. Spatially, highly correlated (R = 0.83) showed marginal differences (±2 K) MODIS ~40% whole area.