Ground surface roughness is an important parameter for land surface models and remote sensing applications. For the first time, a vegetation roughness index (VRI) product was derived from the Second Generation Global Imager (SGLI) sensor onboard the Japanese Global Change Observation Mission-Climate (GCOM-C) satellite. Characterization of the VRI product is therefore necessary for better understanding of the ground surface roughness condition. This study analyzed the monthly VRI data for different land cover types and the relationship between VRI and terrain parameters derived as digital elevation and terrain roughness. The VRI data for forest types are obviously higher than those of the other land cover types. The forest VRI also shows clear seasonal variations, but those of the other land cover types remain stable over the year. The VRI shows a higher relationship with the terrain roughness than the digital elevation. The VRI provides supplementary information to precisely model the land surface structure. It's worthy to understand more characteristics of the VRI product and deeply explore its usefulness.