Dataset
ESA Biomass Climate Change Initiative (Biomass_cci): Global datasets of forest above-ground biomass for the years 2010, 2017 and 2018, v3
Abstract
This dataset comprises estimates of forest above-ground biomass for the years 2010, 2017 and 2018. They are derived from a combination of Earth observation data, depending on the year, from the Copernicus Sentinel-1 mission, Envisat’s ASAR instrument and JAXA’s Advanced Land Observing Satellite (ALOS-1 and ALOS-2), along with additional information from Earth observation sources. The data has been produced as part of the European Space Agency's (ESA's) Climate Change Initiative (CCI) programme by the Biomass CCI team.
This release of the data is version 3. Compared to version 2, this is a consolidated version of the Above Ground Biomass (AGB) maps. This version also includes a preliminary estimate of AGB changes for two epochs.
The data products consist of two (2) global layers that include estimates of:
1) above ground biomass (AGB, unit: tons/ha i.e., Mg/ha) (raster dataset). This is defined as the mass, expressed as oven-dry weight of the woody parts (stem, bark, branches and twigs) of all living trees excluding stump and roots
2) per-pixel estimates of above-ground biomass uncertainty expressed as the standard deviation in Mg/ha (raster dataset)
In addition, files describing the AGB change between 2018 and the other two years are provided (labelled as 2018_2010 and 2018_2017). These consist of two sets of maps: the standard deviation of the AGB change and a quality flag of the AGB change. Note that the change itself can be simply computed as the difference between two AGB maps, so is not provided directly.
Data are provided in both netcdf and geotiff format.
Details
| Previous Info: |
No news update for this record
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| Previously used record identifiers: |
No related previous identifiers.
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| Access rules: |
Public data: access to these data is available to both registered and non-registered users.
Use of these data is covered by the following licence(s): https://artefacts.ceda.ac.uk/licences/specific_licences/esacci_biomass_terms_and_conditions_v2.pdf When using these data you must cite them correctly using the citation given on the CEDA Data Catalogue record. |
| Data lineage: |
Data was created by the Biomass CCI team. |
| Data Quality: |
For information on the quality of the data see the documentation and website for the Biomass CCI
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| File Format: |
Data are netCDF and geotiff formatted.
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Related Documents
| ESA CCI Biomass project website |
| Project documentation for Biomass CCI |
| Product User Guide |
| Algorithm Theoretical Basis Document |
Citations: 7
The following citations have been automatically harvested from external sources associated with this resource where DOI tracking is possible. As such some citations may be missing from this list whilst others may not be accurate. Please contact the helpdesk to raise any issues to help refine these citation trackings.
| Jones, M.W., Kelley, D.I., Burton, C.A., et al. (2024) State of Wildfires 2023–2024. Earth System Science Data 16, 3601–3685. https://doi.org/10.5194/essd-16-3601-2024 https://doi.org/10.5194/essd-16-3601-2024 |
| Kruse, S., Shevtsova, I., Heim, B., Pestryakova, L.A., Zakharov, E.S. & Herzschuh, U. (2023) Tundra conservation challenged by forest expansion in a complex mountainous treeline ecotone as revealed by spatially explicit tree aboveground biomass modeling. Arctic, Antarctic, and Alpine Research 55. https://doi.org/10.1080/15230430.2023.2220208 https://doi.org/10.1080/15230430.2023.2220208 |
| Linnenbrink, J., Milà, C., Ludwig, M. & Meyer, H. (2024) kNNDM CV: k-fold nearest-neighbour distance matching cross-validation for map accuracy estimation. Geoscientific Model Development 17, 5897–5912. https://doi.org/10.5194/gmd-17-5897-2024 https://doi.org/10.5194/gmd-17-5897-2024 |
| Málaga, N., de Bruin, S., McRoberts, R.E., Arana Olivos, A., de la Cruz Paiva, R., Durán Montesinos, P., Requena Suarez, D. & Herold, M. (2022) Precision of subnational forest AGB estimates within the Peruvian Amazonia using a global biomass map. International Journal of Applied Earth Observation and Geoinformation 115, 103102. https://doi.org/10.1016/j.jag.2022.103102 https://doi.org/10.1016/j.jag.2022.103102 |
| Nurrohman, R.K., Kato, T., Ninomiya, H., Végh, L., Delbart, N., Miyauchi, T., Sato, H., Shiraishi, T. & Hirata, R. (2024) Future projections of Siberian wildfire and aerosol emissions. Biogeosciences 21, 4195–4227. https://doi.org/10.5194/bg-21-4195-2024 https://doi.org/10.5194/bg-21-4195-2024 |
| Shapiro, A., d’Annunzio, R., Desclée, B., et al. (2023) Small scale agriculture continues to drive deforestation and degradation in fragmented forests in the Congo Basin (2015–2020). Land Use Policy 134, 106922. https://doi.org/10.1016/j.landusepol.2023.106922 https://doi.org/10.1016/j.landusepol.2023.106922 |
| Skulovich, O., Li, X., Wigneron, J.-P. & Gentine, P. (2024) Global L-band equivalent AI-based vegetation optical depth dataset. Scientific Data 11. https://doi.org/10.1038/s41597-024-03810-2 https://doi.org/10.1038/s41597-024-03810-2 |
Process overview
Instrument/Platform pairings
| Sentinel 1 Synthetic Aperture Radar (SAR) | Deployed on: Sentinel 1A |
| PALSAR-2 | Deployed on: ALOS-2 |
| ENVISAT ASAR | Deployed on: Envisat |
| Phased Array type-L band Synthetic Aperture Radar (PALSAR) | Deployed on: Advanced Land Observing Satellite (ALOS) |
Computation Element: 1
| Title | The ESA Biomass Climate Change Initiative above ground biomass retrieval algorithm, v3.0 |
| Abstract | For information on the derivation of the Biomass CCI data, please see the ATBD (Algorithm Theoretical Baseline Document). |
| Input Description | None |
| Output Description | None |
| Software Reference | None |
| Output Description | None |
- units: Mg/ha
- long_name: Above-ground biomass
- var_id: agb
- names: Above-ground biomass
- units: Mg/ha
- long_name: Above-ground biomass change quality flag
- var_id: diff_qf
- names: Above-ground biomass change quality flag
- units: Mg/ha
- long_name: Above-ground biomass change standard_deviation
- var_id: diff_sd
- names: Above-ground biomass change standard_deviation
- long_name: Above-ground biomass standard_error
- units: Mg/ha
- var_id: agb_se
- names: Above-ground biomass standard_error
- var_id: crs
- long_name: CRS definition
- names: CRS definition
- var_id: lat_bnds
- var_id: lon_bnds
- var_id: time_bnds
Co-ordinate Variables
- units: degrees_north
- standard_name: latitude
- var_id: lat
- long_name: WGS84 latitude coordinate
- names: latitude, WGS84 latitude coordinate
- units: degrees_east
- standard_name: longitude
- var_id: lon
- long_name: WGS84 longitude coordinate
- names: longitude, WGS84 longitude coordinate
- standard_name: time
- var_id: time
- long_name: single-year period
- names: time, single-year period
Temporal Range
2010-01-01T00:00:00
2020-12-31T23:59:59
Geographic Extent
90.0000° |
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-180.0000° |
180.0000° |
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-90.0000° |