Measurement-Driven Estimates of Above-Ground Biomass Change in the Eastern Canadian Boreal Forests from Permanent Sample Plots and Landsat Time Series

Monitoring boreal above-ground biomass (AGB) change requires approaches that are both measurement-based and spatially explicit. We integrated permanent sample plots from Quebec and Ontario with Landsat-7 spectral trajectories (1999–2023) to quantify non-fire-related AGB change after excluding wildfire-affected intervals and to evaluate whether annualized AGB change can be predicted from spectral change at the plot-interval scale. Tree height was estimated using a multilayer perceptron model (R2 = 0.83) and combined with species-specific allometry to derive plot-level AGB and interval ΔAGB. These estimates were aggregated to ecodistricts using effective sample sizes and confidence intervals. Across well-sampled ecodistricts, mean annualized ΔAGB ranged from −0.82 to +3.54 t ha−1 yr−1, with lower or negative changes mainly occurring in eastern regions. Spectral indices derived from NIR–SWIR bands showed relatively stronger associations with ΔAGB than greenness-based indices, consistent with the sensitivity of moisture- and disturbance-related metrics to canopy stress, including defoliation. An XGBoost ensemble correctly predicted the direction of change in 77% of intervals. These results provide a measurement-constrained and scalable framework for monitoring non-fire-related biomass change and supporting greenhouse-gas reporting across boreal forest landscapes.