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September 5, 2025BiogeosciencesOpen Access

Assessing the effect of forest management on above-ground carbon stock by remote sensing

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This analysis reports on carbon stock differences in managed versus unmanaged forests, suggesting remote sensing can enhance monitoring.

The study finds that differences in carbon stocks between managed and unmanaged forests were not detectable through remote sensing.
Using a combination of Sentinel-1 and Sentinel-2 improved the carbon stock estimation model accuracy to R2=0.73 compared to R2=0.56 with just Sentinel-2.
The approach incorporated remote sensing data from Sentinel-2, Sentinel-1, and GEDI into a generalized additive model to estimate carbon stock.
This study highlights the challenges of utilizing remote sensing technology for accurate carbon monitoring, particularly the effects of signal saturation.

Winckel et al. (2025) studied this question.

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September 5, 2025BiogeosciencesOpen Access

View Full Paper

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Authors

This analysis reports on carbon stock differences in managed versus unmanaged forests, suggesting remote sensing can enhance monitoring.

The study finds that differences in carbon stocks between managed and unmanaged forests were not detectable through remote sensing.
Using a combination of Sentinel-1 and Sentinel-2 improved the carbon stock estimation model accuracy to R2=0.73 compared to R2=0.56 with just Sentinel-2.
The approach incorporated remote sensing data from Sentinel-2, Sentinel-1, and GEDI into a generalized additive model to estimate carbon stock.
This study highlights the challenges of utilizing remote sensing technology for accurate carbon monitoring, particularly the effects of signal saturation.

Winckel et al. (2025) studied this question.

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