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.
Land 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: http://www.globallandcover.com/GLC30Download/index.aspx
Forest is an independent layer and classified by combining pixel-based and object-based methods using multitemporal Landsat and HJ imagery.
“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: https://lpdaac.usgs.gov/products/gfcc30tcv003/
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.
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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.
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: http://earthenginepartners.appspot.com/science-2013-global-forest/download_v1.7.html
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.