Hu T., Roujean J. L., Cao B., Mallick K., Boulet Gilles, Li H., Xu Z. H., Du Y. M., Liu Q. H. (2023). Correction for LST directionality impact on the estimation of surface upwelling longwave radiation over vegetated surfaces at the satellite scale. Remote Sensing of Environment, 295, p. 113649 [22 p.]. ISSN 0034-4257.
Titre du document
Correction for LST directionality impact on the estimation of surface upwelling longwave radiation over vegetated surfaces at the satellite scale
Hu T., Roujean J. L., Cao B., Mallick K., Boulet Gilles, Li H., Xu Z. H., Du Y. M., Liu Q. H.
Source
Remote Sensing of Environment, 2023,
295, p. 113649 [22 p.] ISSN 0034-4257
Surface upwelling longwave radiation (SULR) is a major component of the Earth's radiation budget and directly influences the retrieval of evapotranspiration (ET) in the terrestrial ecosystems. Land surface temperature (LST) is an Essential Climate Variable (ECV) for direct estimation of SULR. However, accurate retrieval of SULR from satellite observations may be severely hindered by the anisotropic properties of land surface targets since most of them show marked angular variations in LST. This study aims at investigating the magnitude and impact factors of the directional effects of LST on SULR estimation over vegetated surfaces given that angular variation in emissivity has a limited impact on SULR estimation over most land surface types. It follows an attempt to correct for such effects in SULR estimation. We further explore the possibility to find a viewing direction at which SULR estimated from the directional LST can surrogate the hemispherical integration. To do so, a parametric model mimicking LST anisotropy with the hot spot is incorporated into the physical temperature-emissivity method. Two widely used Moderate Resolution Imaging Spectroradiometer (MODIS) LST products (i.e., MYD11_L2 and MYD21_L2) are analyzed. SULR estimates before and after correcting for LST directionality are compared with insitu measurements acquired at 15 sites from the FLUXNET and SURFRAD networks in different regions. Our analysis reveals that LST directional effects on SULR estimation exhibit diurnal and seasonal variations, which are substantial in spring and summer for the daytime. The effects are negligible (<5 W m 2) in autumn and winter for the daytime except for in arid and semiarid regions. For the night-time, the effects are insignificant over all the biomes. Using MYD21 LST, after correction, the average root-mean-square error (RMSE) and bias of SULR estimates for all sites decrease by 8 and 8.34 W m 2 in spring, and by 8.9 and 12.13 W m 2 in summer. Using MYD11 LST, after correction, the average RMSE is between 10 and 15 W m 2 and the average bias is close to zero in all seasons. The RMSE and absolute bias of SULR estimates for sites with low to moderate vegetation (LAI <3) is lowered substantially (7-14 W m 2) after correction. Interestingly, SULR estimates from LST viewed at 54 degrees backward and hemispherically integrated are close, with differences <3 W m 2 at most of the sites. These findings support a strategy for SULR estimation in ET retrieval over vegetated surfaces from directional LST.
