Global land cover product created by Gong Peng et al., from Tsinghua University, in 2017.
Based on 10 m resolution Sentinel-2 imagery and was produced using a random forest classifier.
The forest class is coded as 20 and is defined as areas with trees higher than 3 m and tree cover of more than 15%.
300,000 training samples of various sizes from around 93,000 sample points worldwide.
The validation set consists of approximately 140,000 samples from different seasons, covering 38,000 sample points.
The overall accuracy of the product is 72.76%, with a user’s accuracy for the forest class of about 83.47%.