ELITE land surface temperature: FY-4A/AGRI hourly 4km seamless LST (2019)

The Essential thermaL Infrared remoTe sEnsing (ELITE) product suite currently has four types of products, including land surface temperature (LST: clear-sky and all-sky), emissivity (NBE: narrowband emissivity; BBE: broadband emissivity; and spectral emissivity), the component of surface radiation and energy budget (SLUR: surface longwave upwelling radiation; SLDR: surface longwave downward radiation SLDR; SLNR: surface longwave net radiation), and the component of Earth's radiation budget (OLR; outgoing longwave radiation; RSR: reflected solar radiation). The spatial-temporal resolutions of the ELITE products are mainly determined by the employed satellite data sources. For more information about ELITE products, please refer to the website (https://elite.bnu.edu.cn).

This dataset is the ELITE hourly seamless 4 km LST dataset covering the FY-4A/AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W).  First, an improved temperature and emissivity separation algorithm was used to obtain the clear-sky LST. Then, under the framework of the SEB theory, a unique way was proposed to solve the temperature difference between the cloudy-sky LST and hypothetical clear-sky LST caused by cloud radiative effects. The in situ validation results show that the bias (RMSE) of the AGRI hourly seamless LST is 0.02 K (2.84 K). The temporal resolution and spatial resolution of this dataset are 1 hour and 4 km, respectively.

This is the ELITE FY-4A/AGRI seamless LST product in 2019. Please click here  to download the ELITE LST product in 2020.

Dataset Characteristics:

• Spatial Coverage: AGRI nominal fixed disc (80.6°N-80.6°S, 24.1°E-174.7°W)
• Temporal Coverage: 2019
• Spatial Resolution: 4 km (subsatellite point)
• Temporal Resolution: one hour
• Data Format: HDF
• Scale: 0.01

Citation (Please cite these papers when using the data):

1. Liu, W., Cheng, J. & Wang, Q. (2023). Estimating Hourly All-Weather Land Surface Temperature From FY-4A/AGRI Imagery Using the Surface Energy Balance Theory. IEEE Transactions on Geoscience and Remote Sensing, 61, 5001518

If you have any questions, please contact Prof. Jie Cheng (eliteqrs@126.com).