Land surface emissivity(LSE) is an essential parameter in the retrieving of land surface temperature(LST) from remote sensing measurements and is a key parameter for the calculation of the surface energy budget. This study focuses on the improvement of the previous emissivity product(Kongju Nat’l Univ. LSE v.2: KNULSE_v2) over the Communication, Ocean and Meteorological Satellite(COMS) observation region. The emissivity was derived using recent(2009?2012) Moderate Resolution Imaging Spectroradiometer(MODIS) data based on the vegetation cover method(VCM). The main issues addressed in this study are as follows: 1) the impacts of snow cover are included using normalized difference snow index(NDSI) data, 2) recent(2009?2012) MODIS normalized difference vegetation index(NDVI) is used and a correction technique(Correction based on Spatial and Temporal Continuity: CSaTC) was applied to the NDVI data, 3) the number of channels is extended from two(11, 12 μm) to four channels(3.7, 8.7, 11, 12 μm), 4) the land cover map data is also updated using the optimized remapping of the five state-of-the-art land cover maps, and 5) the latest lookup table for the emissivity of land surface according to the land cover is used. The improved emissivity data showed a strong seasonal variation with high and low values for the summer and winter, respectively. However, the emissivity over the desert or evergreen forest areas showed a relatively weak seasonal variation irrespective of the channels. Also the snow cover generally increases the emissivity of 3.7, 8.7, and 11 μm but decreases that of 12 μm. The pattern correlation between the KNULSE_v2 and the MODIS LSE data is clearly increased for the winter season, in particular, the 11 μm. However, the differences between the two emissivity data are slightly increased, in particular, the 3.7 μm. The emissivity data updated in this study will contribute to improve accuracy of operational land surface temperature measurements derived from the infrared channel data of COMS.