Global Aboveground Biomass 100 m
Description
This dataset quantifies aboveground biomass density (Mg/ha) at 100 m spatial resolution, with global coverage annually from 2000 onwards. Data includes pixel-level residual uncertainty (± standard error).
202b37bb…Usage notes
New time points are delivered annually. Spatial coverage is limited to vegetated land surfaces between 81.8°N and 81.8°S. Estimates for years before 2010 and for regions with sparse reference samples rely more heavily on temporal extrapolation, so are better suited to identifying long-term trends than to precise annual stock assessment.
AOI constraints
AOI area≤ 1,000,000 haGeometryPolygon, MultiPolygonVariables
aboveground_biomass_density
Description
Aboveground biomass density of dry matter in live woody vegetation on a per hectare basis. Data is generated using a DenseNet deep learning model trained on aboveground biomass reference samples from airborne laser scanning, field plots, forest inventories, and mangrove sites, using Landsat optical, ALOS PALSAR L-band backscatter, topographic, and ancillary spaceborne LiDAR canopy height predictors.
Usage notes
Values are returned with scale and offset already applied. Stored values require scaling if decoding is disabled on load. Multiply values by 0.5, or by a forest specific carbon factor where available, to convert to carbon (Mg C/ha). Multiply carbon values by 3.667 to convert to carbon dioxide equivalent (Mg CO₂ eq/ha). Reported accuracy against a reference sample of ~1.01 million pixels has an R² of 0.741, an RMSE of 59.5 Mg/ha, and a bias of -4.82 Mg/ha. Accuracy may overstate performance outside areas covered by reference samples. Values are less reliable in dense canopy forests, where optical predictors saturate above approximately 300-400 Mg/ha and L-band backscatter loses sensitivity above approximately 150 Mg/ha. Reference samples were constrained to a range of 0-800 Mg/ha during model training. Annual predictions are harmonised to a 2020 baseline map using only pixels not flagged as disturbed, so genuine loss and regrowth signals are retained.
aboveground_biomass_density_uncertainty
Description
Residual standard error for aboveground biomass density variable.
Usage notes
Values are returned with scale and offset already applied. Stored values require scaling if decoding is disabled on load. Uncertainty increases with biomass magnitude, consistent with optical and radar saturation in dense canopy conditions.
Pricing
This dataset has no data acquisition cost.
Resources
Provider
CTrees
ctrees.orgCTrees is a nonprofit research organisation based in Pasadena (US). CTrees aims to provide data on carbon in forests and trees worldwide to support climate action.