This data set includes tree cover extent, humid tropical primary forest extent, aboveground live woody biomass (AGB) stocks and densities, annual tree cover loss, tree cover loss by dominant driver, annual humid tropical primary forest loss, humid tropical primary forest loss by dominant driver, annual forest greenhouse gas (GHG) emissions, average annual forest CO2 removals (sequestration), and average annual net GHG flux at the country and first (state, province) sub-national levels. - Tree cover loss, tree cover loss by driver, and emissions are available as annual data for 2001-2025. - Humid tropical primary forest loss and humid tropical primary forest loss by driver are available as annual data for 2002-2025. - Emissions, removals and net flux are available as annual averages for 2001-2025. - Tree cover is available for 2000 and 2010. - Aboveground biomass stocks and densities are available for 2000. The tree cover data was produced by the University of Maryland's GLAD laboratory in partnership with Google (Hansen et al. 2013). Tree cover loss is defined as “stand replacement disturbance” which is considered to be clearing of at least half of tree cover within a 30-meter pixel. Humid tropical primary forest is defined by Turubanova et al. 2018 as mature natural humid tropical forest cover that has not been completely cleared and regrown in recent history. The tree cover loss by dominant driver data was produced by WRI and Google DeepMind (Sims et al. 2025). The dominant driver is defined as the direct driver that caused the majority of of tree cover loss within each 1 km cell over the time period. Driver classes are defined as follows: - Permanent agriculture: Long-term, permanent tree cover loss for small- to large-scale agriculture. - Hard commodities: Loss due to the establishment or expansion of mining or 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. - 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. - 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 (e.g., landslides, insect outbreaks, river meandering). If loss due to natural causes is followed by salvage or sanitation logging, it is classified as logging. Carbon densities, emissions, removals, and net flux (megagrams or metric tonnes CO2e/yr) are from Harris et al. 2021, updated in Gibbs et al. 2025. The emissions data quantifies the amount of carbon dioxide emissions to the atmosphere where forest disturbances have occurred, and includes CO2, CH4, and N2O and multiple carbon pools. Removals includes the average annual carbon captured by aboveground and belowground woody biomass in forests. Net flux is the difference between average annual emissions and average annual removals; negative values are net sinks and positive values are net sources. Tree cover loss, tree cover extent, and AGB stock and density are presented for percent canopy cover levels >10%, 15%, 20%, 25%, 30%, 50% and 75% in 2000. Emissions, removals, and net flux are presented only for percent canopy cover levels >30%, 50%, and 75% in 2000, plus areas with tree cover gain between 2000 and 2020 (Potapov et al. 2022) regardless of percent canopy cover. We recommend that you select your desired percent canopy cover level before your analysis and use it consistently throughout analyses. The Global Forest Watch website uses a >30% canopy cover threshold as a default for all statistics. Tabs Country tree cover loss: Hectares of tree cover loss at a national level, between 2001-2025, categorized by percent canopy cover in 2000. Country primary loss: Hectares of humid tropical primary forest loss at a national level, between 2002-2025, at 30% tree canopy density only. Country carbon data: Aboveground woody biomass stocks and densities in 2000 (Mg AGB and Mg AGB/ha, respectively); average annual GHG emissions, removals (sequestration), and net flux between 2001 and 2025 (Mg CO2e/yr); annual GHG emissions (Mg CO2e). Provided by percent canopy cover in 2000 (>30%, 50%, and 75% only). Country drivers: Hectares of tree cover loss at a national level, between 2001-2025, at 30% tree canopy density and categorized by dominant driver. Years correspond to the loss year of the annual tree cover loss data. Country primary loss by driver: Hectares of humid tropical primary forest loss at a national level, between 2002-2025, at 30% tree canopy density and categorized by dominant driver. Years correspond to the loss year of the annual tree cover loss data. Subnational 1 tree cover loss: Hectares of tree cover loss at the first sub-national level, between 2001-2025, categorized by percent canopy cover in 2000. Subnational 1 primary loss: Hectares of humid tropical primary forest loss at a sub-national level, between 2002-2025, at 30% tree canopy density only. Subnational 1 carbon data: Aboveground woody biomass stocks and densities in 2000 (Mg AGB and Mg AGB/ha, respectively); average annual GHG emissions, removals (sequestration), and net flux between 2001 and 2025 (Mg CO2e/yr); annual GHG emissions (Mg CO2e). Provided by percent canopy cover in 2000 (>30%, 50%, and 75% only). Subnational 1 drivers: Hectares of tree cover loss at the first sub-national level, between 2001-2025, at 30% tree canopy density and categorized by dominant driver. Years correspond to the loss year of the annual tree cover loss data. Subnational 1 drivers primary loss by driver: Hectares of humid tropical primary forest loss at the first sub-national level, between 2002-2025, at 30% tree canopy density and categorized by dominant driver. Years correspond to the loss year of the annual tree cover loss data. Citations Hansen, M.C., P.V. Potapov, R. Moore, et al. 2013. "High-Resolution Global Maps of 21st-Century Forest Cover Change." Science 342: 850–53. Data available on-line from: https://glad.earthengine.app/view/global-forest-change. Turubanova, S., Potapov, P.V., Tyukavina, A. and Hansen, M.C., 2018. Ongoing primary forest loss in Brazil, Democratic Republic of the Congo, and Indonesia. Environmental Research Letters, 13(7), p.074028. Harris, N.L., D.A. Gibbs, A. Baccini, et al. 2021. "Global maps of twenty-first century forest carbon fluxes." Nature Climate Change 11: 234-240. https://doi.org/10.1038/s41558-020-00976-6. Data available on-line from: https://data.globalforestwatch.org/datasets/gfw::forest-greenhouse-gas-net-flux Gibbs, D.A., M. Rose, et al. 2025. "Revised and updated geospatial monitoring of 21st century forest carbon fluxes." ESSD 17(3): 1217-1243. https://essd.copernicus.org/articles/17/1217/2025/ Gibbs, D.A., N. Harris. 2024. https://www.globalforestwatch.org/blog/data/whats-new-carbon-flux-monitoring/ Sims, M., R. Stanimirova, A. Raichuk, M. Neumann et al. 2025. "Global Drivers of Forest Loss at 1 km Resolution." Environmental Research Letters 20 (7): 074027. doi: 10.1088/1748-9326/add606. Global Administrative Areas Database, version 4.1. Available at http://gadm.org/ Cautions In this data set, “tree cover” is defined as all vegetation greater than 5 meters in height, and may take the form of natural forests or plantations across a range of canopy densities. “Loss” indicates the removal or mortality of tree cover and can be due to a variety of factors, including mechanical harvesting, fire, disease, or storm damage. As such, “loss” does not equate to deforestation. Improvements in the detection of tree cover loss due to the incorporation of new satellite data and methodology changes between 2011 and 2015 may result in higher estimates of loss in recent years compared to earlier years. See https://www.globalforestwatch.org/blog/data-and-research/tree-cover-loss-satellite-data-trend-analysis/ for more information. The emissions, removals, and net flux data are the products of modeling and thus have an inherent degree of error and uncertainty. Users are strongly encouraged to read and fully comprehend the metadata and other available documentation prior to data use. Gross removals and net flux reflect the annual averages over the model period of 2001-2025, not annual time series from which a trend can be derived. Emissions are from stand-replacing disturbances and do not include emissions from forest degradation. Emissions and removals reflect gross estimates, e.g., carbon emissions from any disturbance that occurs without accounting for regrowth. Thus, emissions and removals data must be used with particular caution and in conjunction with each other. Several inputs and constants for emissions, removals, and net flux have been changed since the initial publication of the model. More information on these updates can be found at https://www.globalforestwatch.org/blog/data/whats-new-carbon-flux-monitoring/. The data on the drivers of tree cover loss classifies the dominant driver at 1-km resolution over the full 2001-2025 time period. It does not show multiple drivers if they occur in the same 1-km cell at smaller scales, nor does it detail the sequence of drivers if multiple occurred at different times within the period within the same 1-km cell. Therefore, caution should be used when interpreting drivers for individual years, as the driver of small-scale loss events when multiple drivers are present in each 1-km cell may not always be captured. As a result, drivers for individual years may be over- or under-estimated. See the publication for more information about the data and a full description of limitations: https://doi.org/10.1088/1748-9326/add606. Contact For further questions regarding this data set, please contact Liz Goldman at the World Resources Institute (elizabeth.goldman@wri.org). Version change log v20260427Dataset covering 2001-2025 œÑ