摘要：In the last 10 years a number of new global datasets have been created and new, more
sophisticated algorithms have been designed to classify land cover. GlobCover and MODIS
v.5 are the most recent global land cover products available, where GlobCover (300 m) has
the finest spatial resolution of other comparable products such as MODIS v.5 (500 m) and
GLC-2000 (1 km). This letter shows that the thematic accuracy in the cropland domain has
decreased when comparing these two latest products. This disagreement is also evident
spatially when examining maps of cropland and forest disagreement between GLC-2000,
MODIS and GlobCover. The analysis highlights the continued uncertainty surrounding
these products, with a combined forest and cropland disagreement of 893 Mha
(GlobCover versus MODIS v.5). This letter 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.
