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Remote Sensing: Quality Unlocks Scale
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By Warren Reed
In Spring 2026, ACR published a new Framework for Remotely Sensed Quantification of Forest Carbon. The Framework fulfills a longtime market need for a transparent, scientifically based benchmark against which the efficacy of remotely sensed forest carbon estimates can be assessed. As the technology continues to advance, forest carbon projects listed with ACR now have a way of integrating remote sensing into project development, monitoring and verification.
In carbon markets, quality leads to results at scale. This Framework puts quality at the forefront, with a few important goals in mind:
- Results over method. There are many ways of leveraging remote sensing to derive an estimate of forest carbon. ACR saw no need to create barriers to entry by being overly prescriptive on how estimates are made. Rather, we set benchmarks for accuracy and uncertainty against which we can directly compare results. If a remote sensing approach meets or exceeds the benchmarks, it can be used.
- Scale matters. Forests are diverse and the accuracy of remote sensing estimates vary by circumstance. As a registry we have a portfolio of forest carbon projects that spans biomes. Assessing remote sensing models at the scale at which they are utilized ensures project-specific quality and rigor.
- Efficiencies lead to impact. Remotely sensed technologies offer great potential to increase accessibility to the carbon market. Leveraging remotely sensed estimates of forest carbon has potential to lower the barrier to entry and lead to higher rates of development of forest carbon projects using ACR methodologies.
As reliance on tech-based carbon measurement and estimation techniques advance, ACR and the carbon market need reliable assurance of their accuracy. The ACR Framework validates remotely sensed forest carbon estimates against a sub-set of field plots, setting a known and transparent benchmark for quality that aligns with market expectations.
Under the ACR Framework, quality remains front and center.