Earth Observation-based Quantification of Woody Biomass
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Several terrestrial biosphere Carbon Dioxide Removal (CDR) approaches rely on the capture and storage of carbon in living woody biomass, --including both aboveground biomass (AGB) and below-groundbelowground biomass (BGB). The quantification of BGB is often dependent upon AGB1, which is more directly observable. Thus, for these pathways, accurately and conservatively quantifying the gross storage of carbon in in both AGB and BGB is crucial for demonstrating net CO2 removal.
Aboveground biomass (AGB) encompasses all living vegetation above the soil surface, including stems, branches, foliage, and bark. Woody biomass refers to plants whose structure includes lignified stems, such as bamboo, plants, shrubs, and trees. Belowground woody biomass (BGB) encompasses the subsurface woody biomass in root systems.
This Module provides a transparent, scientifically grounded process by which Isometric quantifies project-scale AGB and BGB using Earth Observation based third-party or internally-developed biomass datasets. These datasets are typically derived from satellite-based remote sensing, ground-based calibration data, and predictive statistical models. This Module outlines the procedures by which Isometric selects, validates, applies, and transparently documents Earth Observation based AGB data products, to ensure consistency with the Isometric Standard and governing Protocol.
Earth Observation aboveground biomass (AGB) maps represent the culmination of decades of remote sensing innovation, ecological research, and data integration methods aimed at quantifying vegetative carbon stocks across large spatial extents. These maps typically integrate satellite observations, airborne remote sensing, and in situ forest inventory data to generate spatially continuous predictions of woody aboveground biomass. The goal is to achieve reliable, wall-to-wall AGB estimates across landscapes where field-based measurement alone is economically or technically infeasible.
AGB maps differ from simpler land cover maps or Normalized Difference Vegetation Index (NDVI) in that they attempt to estimate actual tonnes of dry biomass per hectare — and often include uncertainty quantification layers for each pixel. This integration of empirical data, remote sensing, and modeling has enabled a new generation of biomass maps that underpin conservation policy, MRV systems, and nature-based carbon credit issuances.
Common sources of remotely sensed data that underpin Earth Observation based AGB mapping include:
These data are calibrated and validated against field measurements using statistical models ranging from linear regressions to complex machine learning algorithms like Random Forests, Support Vector Regression, or ensemble approaches. Model outputs are then spatialized across the landscape using remote sensing inputs, yielding gridded AGB predictions -- such as biomass in tonnes per hectare. Some products also include associated error metrics per pixel.
While these datasets have vastly improved our capacity to monitor biomass, limitations persist. These include, but are not limited to:
These uncertainties make it essential that Earth Observation based AGB maps used for crediting are transparently benchmarked, adjusted if necessary, and conservatively interpreted.
This Module was developed based on the current state of the art, publicly available science regarding quantification of woody aboveground biomass and long-term monitoring of terrestrial ecosystems. This Module aims to be scientifically stringent and robust. We recognize that some requirements may exceed the status quo in the market and that there are will be opportunities to improve the rigor of this Module.
Additionally, this Module will be reviewed when there is an update to published scientific literature, government policies, or legal requirements which would affect net CO2e removal quantification or the monitoring guidelines outlined in this Module, or at a minimum of every 2 years.
This Module quantifies the total CO2 equivalent stored as aboveground woody biomass across the project area ([math: M_CO_2e_{AGB,t}] in tonnes) at a given time point, t, through the use of third-party biomass datasets that meet specified eligibility requirements. Where included as a pool, it also quantifies the total CO2 equivalent stored as belowground woody biomass across the project area ([math: CO_2e_{BGB,t}]) at a given time point, t, which is derived from assessed aboveground biomass estimates. This Module applies under the following conditions:
Throughout this Module, the use of “must” indicates a requirement, whereas “should” indicates a recommendation.
Eligibility ofcriteria proposedare third-partyadapted AGBfrom mapsthose willcorresponding beto evaluateda byvalidation Isometric for both overall qualitystage of the2 productor andhigher for suitability of use atin the Projecthierarchy location. Any internally developed data products from Isometric will also be upheld to the same eligibility requirements. Eligibility determination will follow criteria outlinedset by the CEOS validation working group using best practices described in Duncanson et al., (2021)2. ForThese overallinclude:
For acrossapplication representativeto locationsa andspecific timeproject periodsarea, andthe following must be consistent with similar products
To determine whether an AGB map is suitable for use at the project site, the map must have spatial coverage over the full project area and the following conditions must also be metdemonstrated:
Third-party AGB map data products must be developed by an Isometric-approved provider whose processes and products have indicated alignment with the best available science and reliable performance of remote sensing instruments supporting the data product)
Suitabilityproducts. At each use, the data provider must provide an attestation indicating alignment with the above criteria for the projectprovided sitedata, willas well as relevant metadata (e.g., model version) to ensure continuity. Other data products may be permitted with Isometric approval where alignment with the requirements and reliable data performance can be demonstrated.
It is anticipated that the models underlying the map generation may be trained on broader data sets not limited to the project area or conditions. Suitability for application within the project area is further evaluatedassessed against field data collected atwithin the siteproject viaarea as part of the benchmarking procedureprocess described belowin Section 6, and further local calibration to the project area may also be supported with these data.
To calculate the total aboveground biomass in the project area at a given time point ([math: M_{AGB,t}] in tonnes), the map must first be masked to remove any pixels which don’t fully reside within the bounds of the project area to ensure there is not contamination from vegetation dynamics outside of the project. The total biomass is then calculated as:
[math: M_{AGB,t} = \bar{m}_t \times A_{project}]
(Equation 1)
Where:
The total aboveground biomass carbon stock in tonnes CO2 equivalent at time, [math: t], is further calculated as:
[math: CO_2e_{AGB}(t) = \frac{44}{12} \times CF \times M_{AGB}(t)]
(Equation 2)
Where:
The carbon fraction, [math: CF], must be chosen from the following hierarchy:
Where belowground biomass (BGB) is an included as a carbon pool, the belowground biomass is calculated as:
[math: CO_2e_{BGB}(t) = CO_2e_{AGB}(t) \times RS]
(Equation 3)
Where:
Appropriate root-to-shoot ratios should be selected by regional and species-specific factors that are justified based on scientific literature (e.g., USFS's Component Ratio Method or similar national-level species-specific ratios). This is the preferred approach to have the most accurate estimate and avoid overestimation. If sufficient evidence is provided to demonstrate that no suitable project-specific factor can be obtained, matching to the ecological zone and continent of the project area, based on the IPCC 2019 Table 4.44, must be used. In this case, sufficient evidence documenting the unsuccessful search for project specific factors must also be supplied. Acceptable evidence must show (1) a list of search terms used within a research database (e.g., Web of Science, Google Scholar) that encapsulate the region and species relevant to the Project, and (2) the relevant species are not included in the list of species for which root-to-shoot ratio data are available on the TRY Plant Trait Database6.
Where the root:shoot ratios are species or genus specific, the project-area root:shoot ratio must be calculated as a weighted value to represent the species mix within the project area.
The uncertainty in selected [math: RS] factors must be reported from the same source dataset. For example, the IPCC 2019 Chapter on Forest Land4 provides an uncertainty in the root-to-shoot ratio.
The Earth Observation based AGB map must be benchmarked against field plot measurements, at least once every 5 years during the Crediting Period unless otherwise specificed in the Protocol or Module the Project is crediting against. The field plots collected as part of the benchmarking event serve two purposes: (i) providing an assessment of model skill and uncertainty within the project context, and (ii) providing additional calibration data for the map product, as needed. The benchmarking process and outcomes are specific to the data product. If there is a change in data product within the 5 year window, the data product must be benchmarked against either newly collected data or the most recent data before use. Field measurements must follow the requirements set forth in the Area-based Quantification of Above-groundWoody Biomass Module. In addition to the considerations for field sampling included in the referenced Module, fieldthe plotsfollowing apply for the purposepurposes of validating an AGB map should adhere to the followingbenchmarking:
If
The field data are then used to benchmark the earthdata observationproduct prior to its use for quantification and to characterize the uncertainty of its estimates relative to the field-measured AGB. Where the benchmarking reveals a bias in the map’s AGB estimates relative to the withheld validation data, a correction may be applied to the map cannotestimates prior to the assessment of uncertainty.
Cross-validation procedures can allow the full benchmarking dataset to be used directlyfor calibration/training, while still maintaining a robust assessment of model skill and uncertainty. However, this requires additional criteria be met as part of the procedure to ensure transparency and replicability. Projects using cross-validation procedures wherein the full benchmark data are also used to support training must meet the following requirements:
Models and measurements of aboveground biomass inherently include uncertainty from various data sources which contribute to the quantification. While it is not expected that all uncertainties are exhaustively quantified, Project Proponents must evaluate, report, and conservatively account for identifiable and significant sources following the in the approved approaches outlined in the Isometric Standard. Potential sources of uncertainty to consider include, but are not limited to:
Project Proponents must reportfollow the followingrequirements information inwithin the ProjectArea-based Design Document (PDD):
For each verification, Project Proponents must submit a description and copies of any data used and/or collected for the biomassbenchmarking quantificationprocess.
Data providers are responsible for providing the attestation and benchmarkingrelevant metadata for the data products to demonstrate their eligibility in alignment with the requirements of Section 4.0.
Isometric would like to thank Renoster,the forfollowing theirexternal extensivecontributors feedback duringto this Module's:
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