Hansen Global Forest Change
Description
This dataset quantifies tree cover (%) in the year 2000, forest gain from 2000 to 2012, and, if present, the year of forest loss from the year 2000 onwards. Data has global coverage at 30 m spatial resolution.
9659ec1d…Usage notes
New time points are delivered approximately annually. Ongoing improvements in Landsat sensors, land data availability, and algorithms may create inconsistencies in forest change metrics. Consider computing three-year moving averages, where appropriate. This dataset is not proven for rigorous area-based deforestation analysis (e.g. for EUDR).
Variables
tree_cover
Description
The canopy cover of trees for the year 2000. Data is generated using a decision tree trained to predict high resolution imagery and existing tree cover layers from Landsat 7 (2000+), Landsat 8 (2013+), and Landsat 9 (2022+) data.
Usage notes
Tree is defined as vegetation > 5 m height.
forest_gain
Description
Indicates whether a pixel shifted from a non-forest to forest over the period 2000-2012. Data is generated using a decision tree trained to predict high resolution imagery and existing tree cover layers from Landsat 7 (2000+), Landsat 8 (2013+), and Landsat 9 (2022+) data.
Usage notes
Forest is defined as a pixel with > 50% tree cover. Reported global and per-biome accuracy is > 99%. Variable has not been updated since v1.0.
| Index | Name |
|---|---|
| 0 | No gain |
| 1 | Gain |
loss_year
Description
The year a forest pixel became non-forest, Data is generated using a decision tree trained to predict high resolution imagery and existing tree cover layers from Landsat 7 (2000+), Landsat 8 (2013+), and Landsat 9 (2022+) data.
Usage notes
Forest loss is defined as stand-replacement disturbance or shift from forest to non-forest state. Reported global and per-biome accuracy is > 99%. Forest loss does not consider forest degradation (e.g. no change to non-forest state). This dataset version includes reprocessing of loss data from 2011 onwards, possibly leading to inconsistencies before and after this year.
| Value | Name |
|---|---|
| 0 | No loss |
| 1+ | Loss year after 2000. For instance, a value of 9 would indicate forest loss in 2009. |
data_mask
Description
Indicates whether a pixel is land or a permanent water body for the period 2000-2012.
| Index | Name |
|---|---|
| 0 | No data |
| 1 | Land surface |
| 2 | Permanent water body |
Pricing
This dataset has no data acquisition cost.
Resources
Provider
UMD
glad.umd.eduThe Global Land Analysis and Discovery (GLAD) laboratory at the University of Maryland (UMD) studies and develops tools for assessing global land surface change using satellite imagery. GLAD also collaborates on major initiatives including Global Forest Watch and the World Resources Institute Land and Carbon Lab.