Research papers on biomass mapping
Mapped aboveground carbon stocks to advance forest conservation and recovery in Malaysian Borneo
Gregory Asner et al.
Biological Conservation, 2017
High-resolution aboveground carbon density mapping across the entire state of Sabah, Malaysian Borneo, combining airborne LiDAR with field plot data. The resulting maps directly informed conservation priorities and restoration investment across degraded and intact forest landscapes.
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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
An evaluation of NASA GEDI spaceborne lidar for quantifying forest structure across degradation gradients in Amazonian rainforests. The study assessed how well GEDI captures canopy height and biomass variation in forests at different stages of degradation.
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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
New methods for estimating tropical forest canopy height by combining airborne LiDAR with multi-spectral optical satellite data using machine learning. Demonstrates that reliable canopy height estimation does not require expensive data sources or complex deep learning methods.
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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
UAV-based structure-from-motion photogrammetry is widely used to measure plant structure and biomass, but reproducibility under varying field conditions has been poorly characterised. This study found that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination, guiding survey design for digital MRV applications in forest carbon monitoring.
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Global application of an unoccupied aerial vehicle photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems
Andrew Cunliffe et al.
Remote Sensing in Ecology and Conservation, 2021
A globally applicable drone photogrammetry protocol for predicting aboveground biomass in non-forest ecosystems.
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Estimating aboveground carbon density and its uncertainty in Borneo's structurally complex tropical forests using airborne laser scanning
Tommaso Jucker et al.
Biogeosciences, 2018
The model behind the Asner 2017 Sabah-wide carbon map. Traditional LiDAR biomass models use only top-of-canopy height; this one adds canopy cover at 20 metres, which differentiates forest types much better.
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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.
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