Study Region Accuracy description Zhang et al. [ 16] Global GLC_FCS30-2015 achieved the best performance of 82.5%, compared with 59.1% for FROM_GLC-2015 and 75.9% for GlobeLand30-2010. Validation dataset link: https://zenodo.org/record/3551995#.XdttCugzZPY Kang et al. [ 39] Indonesia GLC_FCS30-2015 has the highest overall accuracy (65.59%), followed by GlobeLand30-2010 (61.65%) and FROM_GLC-2015 (57.71%). Gao et al. [ 45] European Union The overall accuracy coefficient of the GlobeLand30-2010 product is the highest at This is followed by GLC_FCS30-2015 ( . and FROM_GLC-2015 ( ) ). Validation dataset link: https://ec.europa.eu/eurostat/web/lucas/data/lucas-grid Chen et al. [ 14] Global An overall classification accuracy of 80.3% was achieved by GlobeLand30. Tsendbazar et al. [ 87] Africa The overall accuracy of GlobeLand30-2010 is 57.1% over the African continent. Sun et al. [ 46] Central Asia GlobeLand30-2010 data have an overall accuracy of 46% and a kappa coefficient of 0.283. Wang et al. [ 84] China The overall accuracy of GlobeLand30-2010 for China is 84.2%. Yang et al. [ 34] China The overall accuracy of GlobeLand30-2010 is 82.39%. See et al. [ 88] Kenya The GlobeLand30 gave an overall accuracy ranging from 53% to 61%. Fonte et al. [ 89] Nepal The overall accuracy is 61% and 54% in Tanzania and Kathmandu, Nepal, respectively. Brovelli et al. [ 90] Italy The overall accuracy is higher than 80% according to a validation covering eight regions across Italy. Balogun et al. [ 91] Malaysia Overall accuracies of 63.45% and 65.70%, respectively, were obtained from the error matrix using sample counts and the new unbiased area estimator with GlobeLand30. Manakos et al. [ 92] Thessaly, Greece GlobeLand30-2010 achieved an overall accuracy of 84% and a weighted overall accuracy of 86% using 539 validation samples. Zhang et al. [ 93] Siberia GlobeLand30-2000 and GlobeLand30-2010 achieved overall accuracies of 85.8% and 86.9% and kappa coefficients of 0.79 and 0.81 over Siberia. Jokar Arsanjani et al. [ 94] Iran GlobeLand30-2010 achieved an overall accuracy of 77.95% based on 738,900 validation samples from Iran. Jokar Arsanjani et al. [ 95] Germany Overall, good correspondence was confirmed between the GlobeLand30 and the other datasets, ranging from 74% for OSM to 92% for CORINE. Gong et al. [ 12] Global FROM_GLC achieved an overall accuracy of 64.9% for the complete set of validation samples and 71.5% for the homogeneous validation samples. Validation dataset link: http://data.ess.tsinghua.edu.cn/data Yu et al. [ 96] Global The overall accuracy of FROM_GLC is 63.69%, and the kappa coefficient is 0.543. Zhao et al. [ 97] Global The overall accuracy of the improved version of FROM_GLC (FROM_GLC_agg) is 65.51%. Validation dataset link: http://data.ess.tsinghua.edu.cn/data Xu et al. [ 35] Africa The second version of the FROM_GLC African land-cover map has an overall accuracy of 74.40%. Dong et al. [ 98] Beijing, China The overall accuracy for FROM_GLC based on comparable vector datasets, Google Earth images, and field survey data is 71.08%, 79.63%, and 80.36%, respectively. Guo et al. [ 99] Pakistan The overall accuracy of FROM_GLC in summer (61.2%) is slightly higher than that in winter (59.0%).