Journal of Remote Sensing / 2021 / Article / Tab 6

Review Article

Finer-Resolution Mapping of Global Land Cover: Recent Developments, Consistency Analysis, and Prospects

Table 6

Definition and details of the seven global 30 m forest products.

Map namePeriodDefinitionMethodLiterature

GLC_FCS302015, 2020Tree-cover ; tree
Forest is divided into five subclasses (evergreen broadleaf forest, deciduous broadleaf forest, evergreen needleleaf forest, deciduous needleleaf forest, and mixed forest)
Dataset link:,
Local adaptive random forest models, Global Spatial Temporal Spectral Library (GSPECLib), and time series of Landsat imagery are used to automatically generate forest products for each geographical grid cell.Zhang et al. [22]
Liu et al. [15]
FROM_GLC2010, 2015, 2017Tree-cover ; tree
Consists of broadleaf forest, needleleaf forest, mixed forest, and orchards
Dataset link:
Forest is treated as an independent layer and classified using 91,433 training samples and multitemporal Landsat imagery.Gong et al. [12]
GlobeLand302000, 2010, 2017Land covered by trees that cover more than 30% includes deciduous broadleaf forest, evergreen broadleaf forest, deciduous coniferous forest, evergreen coniferous forest, mixed forest, and open woodland with a tree cover of 10–30%.
Dataset link:
Forest is an independent layer and classified by combining pixel-based and object-based methods using multitemporal Landsat and HJ imagery.Chen et al. [14]
GFCC30TC2000, 2005, 2010, 2015“Forest” is defined as a class of land cover wherein tree (canopy) cover, , exceeds a predefined threshold value, . The probability of belonging to “forest,” , is therefore the probability of exceeding the threshold
Dataset link:
The 250 m MODIS Vegetation Continuous Fields (VCF) tree-cover layer is downscaled using c.2000 and 2005 Landsat images. The MODIS cropland layer is included to improve accuracy in agricultural areas.Sexton et al. [108]
Townshend et al. [109]
Sexton et al. [31]
TreeCover2010Forest cover is defined using certain tree canopy cover thresholds without attribution to specific land-cover categories and land use. The forest cover class is identified using a tree canopy cover.
Dataset link:
A regression tree model is applied to estimate the maximum (peak of the growing season) tree-canopy cover for each pixel from cloud-free annual growing season composite Landsat-7 ETM+ data from c.2010.Hansen et al. [30]
Potapov et al. [110]
GLADForest2000–2019 (annual)Trees are defined as vegetation taller than 5 m in height and are expressed as a percentage per output grid cell as “2000 Percent Tree Cover.” “Forest Cover Loss” is defined as a stand-replacement disturbance or a change from a forest to a nonforest state, during the period 2000–2019. “Forest Cover Gain” is defined as the inverse of loss or a nonforest to forest change entirely within the period 2000–2012.
Dataset link:
Tree-cover percentage, forest loss, and forest gain training data are related to the time series metrics using a decision tree. For the tree-cover and change products, a bagged decision tree methodology is employed. Forest loss is disaggregated to annual time scales using a set of heuristics derived from the maximum annual decline in the tree-cover percentage and the maximum annual decline in minimum growing season NDVI.Hansen et al. [30]
GFC302018Land spanning more than 0.5 ha with trees higher than 5 m and a canopy cover of more than 10%, or trees able to reach these thresholds in situ
Dataset link:
The Earth is divided into 45 forest ecological zones. Each zone is classified using the random forest model and time series of Landsat imagery.Zhang et al. [32]