Accurate estimation of individual tree above-ground biomass (AGB)its component-wise allocation is crucial for advancing ecological researchforest management. However, current biomass estimation methods, such as destructive samplingallometric equation–based approaches, face limitations in both operational efficiencycost-effectiveness,only destructive sampling can provide component-wise biomass measurements, which is impractical for large-scale studiesrepeated measurements.

In this study, we present a terrestrial laser scanning (TLS)-based workflow integrating wood–leaf separation, voxel-based foliage estimationdetailed 3D reconstruction of tree architecture to achieve accurate estimation of individual tree AGBits component-wise allocation. A total of 68 trees were scanned to obtain high-resolution TLS datasubsequently destructively harvested to acquire field reference measurements for validation.

The results demonstrate that the workflow achieved high accuracy in predicting AGB at the individual tree level (coefficient of determination/R² = 0.88, root mean squared error/RMSE = 16.83 kg, mean absolute error/MAE = 12.18 kg), significantly outperforming estimates derived from locally calibrated allometric equations (R² = 0.61, RMSE = 29.86 kg, MAE = 24.52 kg). Furthermore, this study provides evidence of the strong capability of TLS in estimating branch-level biomass, with high accuracy achieved across branch orders (R² ranging from 0.66 to 0.91, RMSE from 3.55 to 380 gMAE from 2.97 to 290 g).

By providing precise, non-destructive estimates of biomass distribution across branchesleaves, this workflow demonstrates strong potential for improving the accuracy of tree biomass quantification, supporting investigations of resource allocation strategies,enhancing forest carbon monitoring.