Hydrometeorological parameters need to be quantified to better understand climate change because unusual weather phenomena around the world are ultimately caused by higher temperature. The Normal Difference Vegetation Index (NDVI) is one of the most significant factors to understand hydrology cycles. Variations in vegetation at Earth’s surface affect the human and natural environment. This factor is important to demonstrate for spatio-temporal variations of energy cycle on the Earth surface. Therefore, the accurate measurement of vegetation is essential. However, measurement of NDVI have limitation of spatial distribution. So, the alternative plan was suggested by using remote sensing technology instead of NDVI measurement. In this study, we drived the NDVI maps of South Korea from the Geostationary Ocean Color Imager (GOCI). And, we conducted comparative analyses between GOCI and MODIS sensor.