How direct biomass estimation can improve forest carbon accounting

New spaceborne sensors and machine learning innovation have made trustworthy direct measurement, verification and reporting of forest biomass from space a reality, with these tools promising to revolutionize our understanding of forest carbon dynamics.

Forest carbon accounting standards – both for carbon markets and for environmental, social and governance (ESG) applications – can leverage these capabilities to achieve the integrity they need to scale.

The last year has been a rollercoaster in the voluntary carbon markets. Until recently, the market for voluntary carbon credits had seen massive growth, with the primary voluntary carbon markets value growing about tenfold from 2017 to 2022, according to MSCI Carbon Markets.

Then, in early 2023, a series of news and magazine articles called into question the effectiveness of voluntary carbon credits, and in particular that of carbon credits based on nature-based solutions, with claims that up to 90% of those credits do not represent genuine reductions in emissions or sequestration.

Alongside all the other macro disruptions of 2023, this brought a substantial contraction in the primary market value of voluntary carbon, which erased almost all of 2022’s growth.

While critics of market-based solutions to the climate crisis might see this as a good thing, this market correction results in a reduction of private capital flows to critical climate action at a time where public budgets are under pressure from rising interest rates and from increasing defence spending triggered by geopolitical tensions.

To recover, it is clear that voluntary carbon markets need to improve their integrity and transparency. Technological innovation provides an important avenue for these necessary improvements.

New spaceborne sensors and machine learning innovation have made trustworthy direct biomass measurement a reality.

Since the 2000s, the introduction of airborne and spaceborne LiDAR instruments and the advances in machine learning have created the opportunity to directly measure forest biomass at increasingly fine spatial and temporal resolution.

Direct biomass stock and change estimations, like those produced by Chloris Geospatial, provide insights that are impossible to obtain with traditional approaches.

These innovations create more than acceptably accurate overall estimates of carbon fluxes for large areas, which would be both impractical and prohibitively expensive to obtain with airborne and near-surface sensors, while providing spatial and temporal resolution that is impossible to achieve with field campaigns.

At Chloris, this is something that we have proven through extensive validation of our data and through benchmarking against fully independent data sets, like the one carried out by the Ecosystem Restoration Standard.

Like Galileo’s telescope, direct biomass estimation brings a Copernican revolution in our understanding of forest carbon dynamics. It does more than providing a cost-effective and scalable alternative to traditional approaches – it makes a new level of understanding in carbon accounting possible, through three major improvements:

By monitoring all carbon stock changes, direct estimation sees all carbon losses – both deforestation and degradation – but also carbon gains through removals from the growth of forest remaining forest. We can now operationally monitor and include processes that until now were either inferred or simply excluded.

Direct estimates of biomass change don’t tell you only how much the carbon has changed, but also where and when those changes occurred, improving our understanding of the drivers of change and the design of management activities.

A spatially explicit, consistent method from farm to continent enables a much better outcome-based understanding of the impact of projects and programmes, comparing the dynamics of different areas of interest, allowing for dynamic baselining, synthetic controls, and nesting of attribution of outcomes between efforts and processes happening at different levels.

Forest carbon accounting standards – both for carbon markets and for ESG applications – can leverage this technology to achieve the integrity they need to scale.

To date, direct biomass estimation has been excluded from many carbon accounting methodologies, possibly on grounds of concerns about its perceived accuracy, scientific foundation and provider neutrality.

But there is more and more evidence that these concerns are unfounded. The approach is supported by multiple peer-reviewed scientific papers, and an increasing number of service providers can make this technology available to stakeholders and market participants.

At the same time the biggest concerns raised about the integrity of nature-based solutions in the carbon markets have nothing to do with the accuracy of carbon stock and change measurements, but with the approach used to determine baselines and additionality. These are areas where a scalable approach like direct biomass estimation offers massive benefits.

Finally, direct biomass measurement is simpler, more direct, and easier to understand than the current emission factor and activity data approach, making it a better choice to ensure carbon accounting is not only robust and accurate, but also understandable to all participants.

All in all, direct biomass estimation offers a golden opportunity to improve the transparency and scalability of carbon accounting at a time where climate action is more urgent than ever – let’s embrace this innovation.