Earth science data records of global forest cover and change: Assessment of accuracy in 1990, 2000, and 2005 epochs

Min Feng, Joseph O. Sexton, Chengquan Huang, Anupam Anand, Saurabh Channan, Xiao Peng Song, Dan Xia Song, Do Hyung Kim, Praveen Noojipady, John R. Townshend

Research output: Contribution to journalArticlepeer-review

26 Scopus citations


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 < 3%, OE < 22%), but errors were larger for forest loss (45% ≤ CE < 62%, 47% < OE < 55%) and gain (66% ≤ CE < 85%, 61% < OE < 84%). Accuracy was lower in sparse forests and savannahs, i.e., where tree cover was at or near the 30% threshold used to discriminate forest from non-forest cover. Discrimination of forest had a low rate of commission error and slight negative bias, especially in areas with low tree cover. After adjusting global area estimates to reference data, 39.28 ± 1.34 million km2 and 38.81 ± 1.34 million km2 of forest were respectively identified in 2000 and 2005 globally, and 33.16 ± 1.36 million km2 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 km2 between 2000 and 2005, and 1.08 ± 0.53 and 0.53 ± 0.47 million km2 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 (

Original languageEnglish
Pages (from-to)73-85
Number of pages13
JournalRemote Sensing of Environment
StatePublished - Oct 1 2016


  • Accuracy assessment
  • Forest
  • Global
  • Landsat
  • Sampling


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