Directional Land Surface Emissivity Retrieval From Combined MERSI/FY-3D/E and MODIS Data

• Published in: IEEE transactions on geoscience and remote sensing 2024, Vol.62, p.1-16
• Main Authors: Wang, Yi-Cheng, Jiang, Geng-Ming
• Format: Article
• Language: English
• Subjects: Angle of reflection; Aridity; Atmospheric modeling; Bidirectional reflectance; Data acquisition; Deserts; Directional land surface emissivity (LSE); Distribution functions; Emissivity; Instruments; Land cover; Land surface; Land surface temperature; MODIS; multisatellite data; Radiative transfer; Reflectance; Retrieval; retrieval method; Satellite imagery; Satellites; Semi arid areas; Spectroradiometers; Surface temperature; temperature-independent spectral indices (TISI) concept; Terrestrial atmosphere; validation
• ISSN: 0196-2892; 1558-0644
• DOI: 10.1109/TGRS.2024.3385657

This article addresses the directional land surface emissivity (LSE) retrieval from the data acquired by the MEdium Resolution Spectral Imager (MERSI) on Fengyun 3D and 3E (FY-3D/E) satellites and the Moderate-resolution Imaging Spectroradiometer (MODIS) on Terra and Aqua satellites. First, a method to retrieve directional LSEs from multisatellite data is developed based on the radiative transfer model. Then, the directional LSEs are retrieved from the combined MERSI/FY-3D/E, MODIS/Aqua, and MODIS/Terra data in January 1-16 and July 1-16 of 2022 over a study area with longitude from 100 °E to 130 °E and latitude from 20 °N to 50 °N. Finally, the retrieved LSEs are, respectively, cross-validated with the MODIS/Terra land surface temperature (LST) and emissivity 8-day level 3 global 0.05° V61 (MOD11C2) product and the MODIS/Terra LST/3-band emissivity 8-day level 3 global 0.05° V61 (MOD21C2) product over the entire study area, and validated against the in situ data at three true desert and semi-arid sites. The results show that the multisatellite data provide more information of view angles and solar angles, which makes the determination of bidirectional reflectance distribution function (BRDF) model and the LSE retrieval more robust. The LSEs retrieved in this work have strong dependence on time and land cover types. Over the vegetated areas, the LSEs retrieved in this work basically agree with the MOD11C2 and MOD21C2 products, while over the true desert and semi-arid areas, the LSEs in the MOD11C2 and MOD21C2 products are obviously overestimated, especially the MOD11C2 product, but the LSEs in this work are consistent with the in situ data. In general, the method developed in this work is valid and the retrieved LSEs are accurate.