The land cover (LC) data is an important basic input in land surface and climate models. The LC datasets are introduced in this paper by taking the BCC_AVIM model as an example, including the data resolution, sources of different land types, and especially the vegetation cover with different types and classification methods are comparatively analyzed. The available international and domestic global LC datasets about the sources, classification strategy methods, and spatial resolutions are briefly overviewed. The applications of the various LC datasets into the land surface model are briefly discussed. There are some gaps between LC datasets and model use. Then, the possible solution to the poor consistency among different LC remote sensing datasets and possible application methods of the LC datasets in numerical models are addressed so as to make better use of the global LC datasets.