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In the last 10 years a number of new global datasets have been created and new, moresophisticated algorithms have been designed to classify land cover. GlobCover and MODIS v.5are the most recent global land cover products available, where GlobCover (300 m) has thefinest spatial resolution of other comparable products such as MODIS v.5 (500 m) andGLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain hasdecreased when comparing these two latest products. This disagreement is also evident spatiallywhen examining maps of cropland and forest disagreement between GLC-2000, MODIS andGlobCover. The analysis highlights the continued uncertainty surrounding these products, witha combined forest and cropland disagreement of 893 Mha (GlobCover versus MODIS v.5). Thisletter suggests that data sharing efforts and the provision of more in situ data for training,calibration and validation are very important conditions for improving future global land cover products.JRC.H.3-Global environment monitorin

Highlighting continued uncertainty in global land cover maps for the user community