Abstract The Global Land Cover Facility (GLCF) global forest-cover and -change dataset is a multi-temporal depiction of long-term (multi-decadal), global forest dynamics at high (30-m) resolution. Based on per-pixel estimates of percentage tree cover and their associated uncertainty, the dataset currently represents binary forest cover in nominal 1990, 2000, and 2005 epochs, as well as gains and losses over time. A comprehensive accuracy assessment of the GLCF dataset was performed using a global, design-based sample of 27,988 independent, visually interpreted reference points collected through a two-stage, stratified sampling design wherein experts visually identified forest cover and change in each of the 3 epochs based on Landsat and high-resolution satellite images, vegetation index profiles, and field photos. Consistent across epochs, the overall accuracy of the static forest-cover layers was 91%, and the overall accuracy of forest-cover change was > 88% —among the highest accuracies reported for recent global forest- and land-cover data products. Both commission error (CE) and omission error (OE) were low for static forest cover in each epoch and for the stable classes between epochs (CE 2 and 38.81 ± 1.34 million km 2 of forest were respectively identified in 2000 and 2005 globally, and 33.16 ± 1.36 million km 2 of forest were estimated in the available coverage of Landsat data circa-1990. Forest loss and gain were estimated to have been 0.73 ± 0.38 and 0.28 ± 0.26 million km 2 between 2000 and 2005, and 1.08 ± 0.53 and 0.53 ± 0.47 million km 2 between 1990 and 2000. These estimates of accuracy are required for rigorous use of the data in the Earth sciences (e.g., ecology, economics, hydrology, climatology) as well as for fusion with other records of global change. The GLCF forest -cover and -change dataset is available for free public download at the GLCF website ( http://www.landcover.org ).