This paper extends a new temperature and emissivity separation(TES)algorithm for retrieving land surface temperature and emissivity(LST and LSE)to the Advanced Geosynchronous Radiation Imager(AGRI)onboard Fengyun-4A,C...This paper extends a new temperature and emissivity separation(TES)algorithm for retrieving land surface temperature and emissivity(LST and LSE)to the Advanced Geosynchronous Radiation Imager(AGRI)onboard Fengyun-4A,China’s newest geostationary meteorological satellite.The extended TES algorithm was named the AGRI TES algorithm.The AGRI TES algorithm employs a modified water vapor scaling(WVS)method and a recalibrated empirical function over vegetated surfaces.In situ validation and cross-validation are utilized to investigate the accuracy of the retrieved LST and LSE.LST validation using the collected field measurements showed that the mean bias and RMSE of AGRI TES LST are 0.58 and 2.93 K in the daytime and−0.30 K and 2.18 K at nighttime,respectively;the AGRI official LST is systematically underestimated.Compared with the MODIS LST and LSE products(MYD21),the average bias and RMSE of AGRI TES LST are−0.26 K and 1.65 K,respectively.The AGRI TES LSE outperforms the AGRI official LSE in terms of accuracy and spatial integrity.This study demonstrates the good performance of the AGRI TES algorithm for the retrieval of high-quality LST and LSE,and the potential of the AGRI TES algorithm in producing operational LST and LSE products.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 42192581,42090012,and 42071308in part by the Second Tibetan Plateau Scientific Expedition and Research Program(STEP)under Grant 2019QZKK0206in part by the open fund of Beijing Engineering Research Center for Global Land Remote Sensing Products.
文摘This paper extends a new temperature and emissivity separation(TES)algorithm for retrieving land surface temperature and emissivity(LST and LSE)to the Advanced Geosynchronous Radiation Imager(AGRI)onboard Fengyun-4A,China’s newest geostationary meteorological satellite.The extended TES algorithm was named the AGRI TES algorithm.The AGRI TES algorithm employs a modified water vapor scaling(WVS)method and a recalibrated empirical function over vegetated surfaces.In situ validation and cross-validation are utilized to investigate the accuracy of the retrieved LST and LSE.LST validation using the collected field measurements showed that the mean bias and RMSE of AGRI TES LST are 0.58 and 2.93 K in the daytime and−0.30 K and 2.18 K at nighttime,respectively;the AGRI official LST is systematically underestimated.Compared with the MODIS LST and LSE products(MYD21),the average bias and RMSE of AGRI TES LST are−0.26 K and 1.65 K,respectively.The AGRI TES LSE outperforms the AGRI official LSE in terms of accuracy and spatial integrity.This study demonstrates the good performance of the AGRI TES algorithm for the retrieval of high-quality LST and LSE,and the potential of the AGRI TES algorithm in producing operational LST and LSE products.
