Global Forest Change
Parameter
Global Forest Change
3 classes
Represented classes
Tree cover loss (2000- 2019)
Tree cover gain (2000- 2012)
Tree cover loss and gain
Description
The 'Global Forest Change, 2000-2019' product is derived from processing Hansen Global Forest Cover Change v 1.7 database. It combines the reference tree cover 2000 with gains (recorded from 2000 to 2012) and losses of forest recorded up to 2019 in one map. It is the result from time-series analysis of Landsat images characterizing forest extent and change. Trees are defined as vegetation taller than 5m in height and are expressed as a percentage per output grid cell. 'Forest Cover Loss' is defined as a stand-replacement disturbance, or a change from a forest to non-forest state, during the period 2000-2019. 'Forest Cover Gain' is defined as the inverse of loss, or a non-forest to forest change entirely within the period 2000-2012. 'Forest Loss Year' is a disaggregation of total 'Forest Loss' to annual time scales.
Global Forest Change – Loss by year
1 class
Tree cover loss (2019)
The 'Global Forest Change, 2000-2019' product is derived from processing Hansen Global Forest Cover Change v 1.7 database. It combines the reference tree cover 2000 with gains (recorded from 2000 to 2012) and losses of forest recorded up to 2019 in one map. It is the result from time-series analysis of Landsat images characterizing forest extent and change. Trees are defined as vegetation taller than 5m in height and are expressed as a percentage per output grid cell. 'Forest Cover Loss' is defined as a stand-replacement disturbance, or a change from a forest to non-forest state, during the period 2000-2019. 'Forest Cover Gain' is defined as the inverse of loss, or a non-forest to forest change entirely within the period 2000-2012. 'Forest Loss Year' is a disaggregation of total 'Forest Loss' to annual time scales.
University of Maryland (UMD GLAD)
Source data
Global Land Analysis and Discovery (GLAD) laboratory
University of Maryland (UMD GLAD)
Description
The Global Land Analysis and Discovery (GLAD) laboratory in the Department of Geographical Sciences at the University of Maryland investigates methods, causes and impacts of global land surface change. Earth observation imagery are the primary data source and land cover extent and change the primary topic of interest.
The 'Global Forest Change, 2000-2019' product is derived from processing Hansen Global Forest Cover Change v 1.7 database
Results from time-series analysis of Landsat images characterizing forest extent and change.
Spatial resolution
Global coverage
Pixel size:
30m x 30m
Temporal resolution
Period of observation:
2000-2019