ELITE emissivity: Landsat NBE over CONUS (2014.7)

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 Landsat narrowband (NBE) emissivity dataset (Landsat8 Channel 10) over the continental United States (Cheng et al. 2021). For the non-vegetated surfaces, the LSEs were estimated using an empirical method that establishes the linkages between the ASTER NBE product and the Landsat SR product. For the vegetated surfaces, the LSEs were derived by using the 4SAIL model established lookup table (LUT) provided with the NBE of the leaf emissivity, soil background emissivity, and leaf area index (LAI).

This is the ELITE Landsat NBE dataset from Landsat 8 in July 2014. Please click here to download the ELITELandsat NBE dataset from Landsat 8 in January 2014.

Dataset Characteristics:

• Spatial Coverage: The Continental United States
• Temporal Coverage: 2014.7
• Spatial Resolution: 30m
• Temporal Resolution: 16 days
• Data Format: Geotiff
• Scale: 0.001

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

1. Cheng, J., Meng, X., Dong, S., & Liang, S. (2021). Generating the 30-m land surface temperature product over continental China and USA from landsat 5/7/8 data. Science of Remote Sensing, 4, 100032

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