Global drivers of forest loss at 1 km resolution

Driver

Definition

Permanent agriculture

Long-term, permanent tree cover loss for small- to large-scale agriculture. This includes perennial tree crops such as oil palm, cacao, orchards, nut trees, and rubber, as well as pasture and seasonal crops and cropping systems, which may include a fallow period. Agricultural activities are considered "permanent" if there is visible evidence that they persist following the tree cover loss event and are not a part of a temporary cultivation cycle. Clearing land for agricultural activities may involve use of fire.      

Hard commodities

Tree cover loss due to the establishment or expansion of mining or energy infrastructure. Mining activities range from small-scale and artisanal mining to large-scale mining.  Energy infrastructure includes power lines, power plants, oil drilling and refineries, wind and solar farms, flooding due to the construction of hydroelectric dams, and other types of energy infrastructure.

Shifting cultivation  

Tree cover loss due to small- to medium-scale clearing for temporary cultivation that is later abandoned and followed by subsequent regrowth of secondary forest or vegetation. Clearing land for temporary cultivation may involve use of fire.

Logging

Forest management and logging activities occurring within managed, natural or semi-natural forests and plantations, often with evidence of forest regrowth or planting in subsequent years. This includes harvesting in wood-fiber plantations, clear-cut and selective logging, establishment of logging roads, and other forest management activities such as forest thinning and salvage or sanitation logging.

Wildfire   

Tree cover loss due to fire with no visible human conversion or agricultural activity afterward. Fires may be started by natural causes (e.g. lightning) or may be related to human activities (accidental or deliberate).

Settlements and infrastructure

Tree cover loss due to expansion and intensification of roads, settlements, urban areas, or built infrastructure (not associated with other classes).

Other natural disturbances

Tree cover loss due to other non-fire natural disturbances, including storms, flooding, landslides, drought, windthrow, lava flows, sediment flow or meandering rivers, natural flooding, insect outbreaks, etc. If tree cover loss due to natural causes is followed by salvage or sanitation logging, it is classified as logging.

Column name

Description

ID

Unique ID for each plot.   

Latitude 

Latitude for center point of 1 km plot. 

Longitude

Longitude for center point of 1 km plot.       

Driver_primary_code

Numeric code assigned to each driver: Permanent agriculture (1), Hard commodities (2), Shifting cultivation (3), Logging (4), Wildfires (5), Settlements & infrastructure (6), Other natural disturbances (7).   *Noise/non-forest (8) *Note– this class is only included in the training data, in place of a separate “Noise” column. See below.

Driver_primary

Primary driver accounts for >50% of all loss area within the study period in 1 km plot.         

Confidence_primary 

Image analyst's confidence in interpretation of primary driver: low, medium or high.      

Driver_secondary

Secondary driver accounts for <50% of all loss area within the study period in 1 km plot. Secondary driver includes a category called Commodity-driven deforestation which includes both permanent agriculture and hard commodities. Most but not all notes fields include the type of commodity-driven deforestation as secondary driver.  

Confidence_secondary

Image analyst's confidence in interpretation of secondary driver: low, medium or high.      

Active_learning*

Binary variable indicating 1 if the plot was collected as part of additional data collection effort via active learning.  *Note: this column is only included in the training data.

Noise* 

True/False field with True label assigned to tree cover loss pixels that are noise (e.g. due to cloud/sensor issues, shadows, etc.) or that never had tree cover or shrubby vegetation throughout the time series. *Note: this column is only included in the validation data.

Region 

Regions are North America, Latin America, Europe, Africa, and Oceania. We split Asia into two subregions: 1) Southeast Asia and the rest (East/South/Central Asia & MiddleEast), and we refer to these areas as Southeast Asia and Asia.                                                

Region_code

Numeric code assigned to each region: North America (1), Latin America (2), Europe (3), Africa (4), Asia (5), Southeast Asia (6), and Oceania (7).          

Tags

Tags are a limited set of labels that provide further information on the category of commodity-driven deforestation in the 1km plot: Mining, Energy, Agriculture, Tree crop management. Tags can be associated with either Driver_primary if Driver_primary_code is 1 or 2, or it can be associated with Driver_secondary if Driver_primary_code is not 1 or 2.

Notes 

Optional field that provides contextual information on the driver in the 1 km plot, or provides information on why a medium or low confidence label was assigned.