We combine earth observation foundation models with rigorous counterfactual science to build more credible forest carbon baselines.
Supported by
Backed by the European Space Agency through a Business Applications Kick-start activity. Supported by Innosuisse, the Swiss innovation agency, and Venture.
Support this work→The Bornean ironwood is called belian in Bahasa Melayu, the Malaysian language. It is a tree that can live for more than 1,000 years, and it stores an exceptional amount of carbon because of its very high wood density. Read about belian, the Bornean ironwood tree we're named after.
Forest conservation and carbon projects face a fundamental challenge: how do you credibly estimate what would have happened without the conservation intervention? Getting counterfactuals right is essential for carbon markets to deliver real climate impact.
We're building new approaches to this problem, bringing together state-of-the-art geospatial foundation models with rigorous causal inference methods.
Science-backed counterfactuals
Foundation model powered
A tree of the Lauraceae family that lives for more than a thousand years, grows wood so dense it sinks, and is now Vulnerable after a century of logging. What it is, where it grows, and why it stands for permanent carbon storage.
Read about the belian tree
Plain-English explainers on the rules that decide whether forests get financed: Article 6 of the Paris Agreement, SBTi’s corporate net-zero standards, and the ICVCM’s integrity bar, with belian’s commentary as the frameworks move.
Permanence has been a sticking point for Nature-Based Solutions since the Kyoto debates. The ICVCM Permanence Trust may finally unlock long-term durability. Even then, the deeper question of how nature gets financed will remain.
Combining cutting-edge technology with established scientific methods for credible baseline estimation.
Leveraging the latest advances in Earth observation AI to understand landscape-scale patterns of forest change and condition.
Applying rigorous statistical methods to estimate counterfactual outcomes—what would have happened without the conservation intervention.
Deep domain knowledge in forest carbon monitoring, project assessment, and the challenges facing credible baseline estimation.
We'd love to hear from researchers, developers, and project teams.
