European Space Agency | Source | Dataset |
The dataset at hand presents a collection of estimates pertaining to forest above-ground biomass (AGB) spanning the years 2010, 2017, 2018, 2019, and 2020. These estimations are the outcome of a sophisticated process that combines Earth observation data from various sources, depending on the specific year. These sources include data from the Copernicus Sentinel-1 mission, Envisat's ASAR instrument, and JAXA's Advanced Land Observing Satellite (ALOS-1 and ALOS-2), in conjunction with supplementary information from other Earth observation sources. It's essential to note that this dataset is a product of the European Space Agency's (ESA's) Climate Change Initiative (CCI) program, executed by the capable Biomass CCI team.
This release, designated as version 4, represents a significant update compared to its predecessor, version 3. Version 4 introduces updated AGB maps for the years 2010, 2017, and 2018, along with entirely new AGB maps for 2019 and 2020. Furthermore, it includes novel AGB change maps covering consecutive years (2018-2017, 2019-2018, and 2020-2019) as well as a decadal interval (2020-2010). What sets version 4 apart is the inclusion of multi-temporal L-band observations across all biomes and years, enhancing the dataset's accuracy and comprehensiveness. The AGB maps now incorporate revised allometries, underpinned by an extended dataset of spaceborne LiDAR data sourced from missions such as GEDI and ICESat-2. Additionally, temporal dynamics are integrated into the retrieval algorithm to faithfully represent biomass changes as observed in remote sensing data. Notably, biases between the 2010 dataset and more recent years have been mitigated.
The dataset consists of two global layers:
Above Ground Biomass (AGB): Measured in tons per hectare (i.e., Mg/ha), this layer quantifies the mass of woody components (stem, bark, branches, and twigs) of all living trees, excluding stumps and roots, expressed as oven-dry weight.
Above-Ground Biomass Uncertainty: This layer provides per-pixel estimates of the uncertainty associated with above-ground biomass measurements, expressed as standard deviations in Mg/ha. It offers valuable insights into the precision and reliability of the biomass estimations.