Tropical forest canopy viewed from above
Research

Biomass Mapping

Repeated drone photogrammetry surveys demonstrate that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions

Slade, G. et al.

International Journal of Remote Sensing · 2025

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What this paper found

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.

How this informs belian.earth’s work

Drone photogrammetry is increasingly used in digital MRV. Hugh and Andy co-authored this work characterising how reconstructed canopy heights respond to wind and illumination, guidance that matters for any project relying on UAV-based biomass monitoring.

Frequently asked questions

How reliable are drone photogrammetry surveys for measuring vegetation canopy height under different field conditions?

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UAV-based structure-from-motion (SfM) photogrammetry is increasingly used by ecologists to measure plant structure and biomass, but its reproducibility under varying operational conditions has not been well characterised. This study found that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions, providing important guidance for survey design. For digital MRV applications, this finding helps practitioners understand which environmental conditions introduce measurement error when using drone surveys to estimate forest biomass and carbon stocks.

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Citation

Slade, G. et al. (2025). Repeated drone photogrammetry surveys demonstrate that reconstructed canopy heights are sensitive to wind speed but relatively insensitive to illumination conditions. International Journal of Remote Sensing. https://doi.org/10.1080/01431161.2024.2377832

DOI: 10.1080/01431161.2024.2377832