A Combined Vegetation Cover and Temperature-Emissivity Separation (V-TES) Method to Estimate Land Surface Emissivity.

Land surface emissivity (LSE) is a critical variable in the quantification of the surface energy budget and for the estimation of surface parameters from earth observation data, in particular, the land surface temperature (LST). A new LSE product is proposed that combines two widely used methods: the vegetation cover method (VCM) and the temperature-emissivity separation (TES) algorithm. The so-called V-TES approach maximizes the strengths of each method, considering their different performance over a wide range of surface conditions. As such, over vegetated areas, where thermal spectral contrasts are low and retrievals using TES are less accurate, we use the VCM method, while over bare areas, where the VCM relies entirely on ancillary information, the TES method is preferred. The proposed methodology was applied to observations from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) onboard Meteosat Second Generation (MSG) satellites to derive emissivity channel and broadband emissivities in the 3-14- $\mu \text{m}$ range. Daily LSE maps are then derived using estimates of the fraction of vegetation cover and snow cover. The product shows good agreement with in situ data, with accuracies of 0.009 and 0.014 in the 8-14- and 3-8- $\mu \text{m}$ regions, respectively. The methodology described in this article will be used to improve LST estimates and will be applied by the Satellite Applications Facility on Land Surface Analysis (LSA-SAF) for LST production from EUMETSAT's Meteosat Second and Third Generation (MSG/MTG) and the Polar System-Second Generation (EPS-SG) missions.