Tracking terrestrial biomass from space: patterns, trends, and uncertainties

The proliferation of satellite missions targeting observations of terrestrial land surfaces has substantially increased efforts to map and monitor carbon stored in vegetation using remote-sensing datasets. One such effort, ESA’s Climate Change Initiative (CCI) Biomass project, is about to release an 18-year record of global aboveground biomass (AGB) maps covering the periods 2005–2012 and 2015–2024 at a spatial resolution of 1 hectare. This latest release (version 7.0) significantly extends previous data records and reduces temporal inconsistencies caused by the diverse set of satellite observations required to construct such a long time series. With this release, the CCI Biomass dataset enables the tracking of carbon dynamics in terrestrial vegetation over the past two decades and is now comparable with other global, satellite-based, spatially explicit datasets.

In this presentation, we highlight three key findings derived from the CCI Biomass dataset.

• We identify spatially consistent biomass accumulation in tropical secondary forests in Brazil, in agreement with sample-based estimates derived from in situ measurements where available. Spatially resolved growth trends, combined with forest age information from the MapBiomas dataset, indicate higher growth rates in the western Amazon, with peaks of up to 10 Mg ha⁻¹ yr⁻¹ at approximately 10–15 years of forest age. In contrast, growth rates in the eastern Amazon do not exceed 5 Mg ha⁻¹ yr⁻¹.
• We detect contrasting biomass trends in primary forests of the Brazilian Amazon. Below a biomass threshold of 250 Mg ha⁻¹, forests exhibit an average accumulation of approximately 1–2 Mg ha⁻¹ yr⁻¹, whereas above this threshold high-biomass forests show a decline of around −1 Mg ha⁻¹ yr⁻¹. These findings are consistent with recent evidence suggesting a weakening of the Amazon carbon sink. However, they remain unconfirmed and will need further investigation, particularly with respect to statistical significance, given the substantial pixel-level uncertainty in the CCI Biomass estimates.
• A comparison among several global AGB datasets derived from satellite data (e.g., Xu et al., Boitard et al., Li et al., Santoro et al.), including CCI Biomass, reveals broad agreement in the spatial distribution of biomass. However, absolute AGB estimates can differ by up to 100% among datasets, irrespective of geographic location. Moreover, temporal biomass trajectories often diverge, showing differences in the magnitude of fluctuations and, in some cases, opposing growth trends. Overall, our analysis underscores the need for a systematic intercomparison of remote-sensing-based AGB datasets using a common framework to assess their accuracy and uncertainty.