Research
Monitoring, modelling and managing beaver (Castor fiber) populations in the River Otter catchment, Great Britain
Hugh Graham et al.
Ecological Solutions and Evidence, 2022
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Evaluating GEDI for quantifying forest structure across a gradient of degradation in Amazonian rainforests
Emily Doyle et al.
Environmental Research Letters, 2025
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning
Brianna Pickstone et al.
Sustainable Environment, 2025
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Repeated drone photogrammetry surveys demonstrate that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions
Glenn Slade et al.
International Journal of Remote Sensing, 2025
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Posts
VM0047's brave call is your ARR project's defining moment
VM0047 locks the developer's matched reference areas at validation and keeps them fixed for the full crediting period. That single choice defines your ARR project's baseline for decades.
ML4EO 2026: Why Pixels Aren't Enough for Carbon Market Integrity
We're sponsoring ML4EO again this year. Here's why the machine learning for earth observation community matters for carbon markets — and what it still gets wrong about pixels.
The carbon baseline problem nobody wants to talk about
The carbon market has an integrity problem. But while the industry obsesses over which biomass map to trust, the real uncertainty is in the carbon baseline.
belian.earth receives ESA funding to advance forest carbon baseline methods
belian.earth has been awarded funding from the European Space Agency (ESA) for our project 'Conservation Integrity: Geo-AI powered transparency for Nature-Based Solutions.'
Why Forest Restoration Projects Need Robust Counterfactual Baselines
Every forest carbon project depends on a counterfactual baseline to demonstrate its impact. Whether avoiding deforestation or restoring degraded land, the underlying question is the same: what would have happened without the intervention?
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