CCI Biomass


The CCI BIOMASS project delivers spatially explicit estimates of AGB for four epochs and related standard deviations (SDs) as separate map products.

Dataset Description

The CCI BIOMASS project delivers spatially explicit estimates of AGB for four epochs and related standard deviations (SDs) as separate map products. The AGB product consists of global datasets with estimates of AGB (unit: tons/ha = Mg/ha). AGB 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. The AGB SD product is a separate data layer providing per-pixel SD of the AGB estimates in Mg/ha.

The data products currently provided by the project (year 3, Version 3.0, and additional 2020) consist of four maps of AGB and AGB SD based on Earth Observation data acquired in 2010, 2017, 2018 and 2020, respectively. The spatial resolution of the map products is 100 m.

Usage

As a result of our investigation of the three AGB datasets and related changes, users are kindly invited to note the following comments (further details of the 2020 product not currently available (October, 2021):
  • Use of the AGB estimates of individual full resolution pixels should be avoided.
  • The 2018 AGB dataset has (locally) higher quality than the 2017 AGB dataset.
  • The 2010 CCI BIOMASS dataset is an improved version of the GlobBiomass AGB dataset (http://globbiomass.org) but has different properties compared to 2017 and 2018.
  • AGB change maps should be interpreted carefully. It is strongly advised to use the quality flag layer to understand the reliability of the AGB change values.
  • Be extremely cautious when using the CCI Biomass maps to assess AGB changes. We strongly advice to validate changes before further analysis of the data.

Methodology

Requirements on global coverage during each of the three epochs, open access to the data and sensitivity of the observations to forest structural parameters restricted the useful pool of remote sensing observations to images acquired by SAR C-band (Envisat ASAR for 2010 and Sentinel-1 for 2017-2018 and 2020) and L-band (ALOS-1 PALSAR-1 for 2010 and ALOS-2 PALSAR-2 for 2017-2018 and 2020). Initially, separate algorithms (which share the same theoretical basis) were applied to the C-band and L-band datasets. With each algorithm, referred to as BIOMASAR, a global map of AGB was obtained. The BIOMASAR algorithm inverts a semi-empirical model relating the forest backscatter to canopy density and canopy height; these are replaced by two allometries relating canopy density to height (based on ICESat GLAS measurements) and canopy height to AGB (based on ICESat GLAS height metrics and global estimates of AGB, represented here by the GlobBiomass AGB dataset). The model contains three parameters that are unknown a priori, and which correspond to specific backscatter components (ground, canopy) and backscattering properties of the forest. In order to estimate them, auxiliary datasets describing canopy density, microwave transmissivity, maximum biomass etc. are used. A detailed description of these data layers is available in the ATBD of the CCI BIOMASS project. Note that the model training phase does not require in situ observations, such as AGB plot data.

Validation results at 0.1° in different AGB bins. The size of bins is based on the number of plots inside the bin. The error bars indicate the 25th and 75th quantiles of the map value.


Validation results at 0.1° in different AGB bins. The size of bins is based on the number of plots inside the bin. The error bars indicate the 25th and 75th quantiles of the map value.

Uncertainty and Accuracy

Validation of the BiomassCCI 2020 map used a dedicated tool (plot2map) that allowed comparison with an extensive dataset of ground-based tree size measurements collected from small (averaging 0.15 ha; n > 70,549) and medium (0.9 - 3 ha; n > 462) to large-sized (> 6 ha; n > 20) research plots (Tiers 1-3 respectively), with adjustments made for temporal discrepancies and partial forest fractions. Comparison against Tier 1 and Tier 2 plots indicated that globally, the CCI Biomass map at their original 1 ha resolution tended to slightly over-predict up to 300 Mg ha-1 and under-predict beyond that. These differences were attributed in part to within-pixel sampling error that occurred because the AGB of single small plots may significantly differ from the population mean in the pixel. Spatial aggregation of plot and map data to 0.1° cells (a level of aggregation suitable for most climate modellers) considerably improved the agreement. In general, between 50 Mg ha-1 and 400 Mg ha-1, mean differences between the mapped and reference AGB were found to be well within 20% at the 0.1° cell level. The validation at 0.1° of the BiomassCCI 2020 and its comparison with the validation from previous CCI maps are shown below. Validation of the 2010, 2017 and 2018 products can be found in the project PVIR.

Dataset Sustainment

Annual products will continue to be released (2019, 2021, 2022) plus an investigation into the feasibility of products for past years (2005/7 and 2015/16). Change maps have been produced for 2010-18 and 2017-18, which will continue to be developed and improved.

Technical Characteristics

Spatial resolution: ~100 m at the Equator

Geographical coverage: Global

Temporal coverage: 2010, 2017, 2018, 2020

Update frequency: Annual

Format: GeoTIFF

Data Policy: Creative Commons Attribution 4.0 International (CC-BY-4.0)


Associated Guidance or User Manual

Product manual not yet available (October 2021), but it will be available from:https://climate.esa.int/en/projects/biomass/

Validation report not yet available (October 2021), but it will be available from:https://climate.esa.int/en/projects/biomass/

2010, 2017 & 2018 Dataset link available from (2020 not yet available; October 2021):
https://climate.esa.int/en/odp/#/project/biomass


Points of contact for queries

Maurizio Santoro
GAMMA RS
Switzerland
Email: santoro@gamma-rs.ch