November 30, 2025ForestsOpen Access

Forest Aboveground Biomass Estimation Using High-Resolution Imagery and Integrated Machine Learning

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This study finds that machine learning improves aboveground biomass estimation in forests, suggesting enhanced applications for carbon monitoring.

Aboveground biomass estimation showed significant improvement using machine learning techniques and remote sensing data.
Random Forest and ensemble methods effectively enhanced estimation accuracy with an R2 of 0.62 and RMSE of 57.34 Mg/ha.
Analysis utilized high-resolution GaoFen-7 satellite imagery and features like texture and vegetation indices for model training and validation.
Results highlight the potential of advanced machine learning models in forest biomass assessment and carbon monitoring applications.

Liu et al. (2025) studied this question.

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This study finds that machine learning improves aboveground biomass estimation in forests, suggesting enhanced applications for carbon monitoring.