Tree Structural Parameter Extraction and Aboveground Biomass Estimation Using Low-Cost Backpack LiDAR

Accurate estimation of tree structural parameters and aboveground biomass (AGB) is crucial for carbon monitoring and sustainable forest management. While terrestrial and airborne LiDAR have been widely used, their high cost and limited ability to capture understory structures constrain broader applications. This study demonstrates, for the first time in a heterogeneous tropical urban forest, that a low-cost Backpack LiDAR system combined with the Adaptive Quantitative Structural Model (AdQSM) can achieve comparable accuracy at a fraction of the cost. The extracted parameters showed strong agreement with field measurements (R2 = 0.9855 for DBH and 0.9992 for tree height; RMSE = 4.63 cm and 0.044 m). Biomass estimation across 25 trees revealed substantial interspecies variation, reflecting structural diversity. These findings highlight the novelty of applying affordable Backpack LiDAR for individual tree biomass assessment in complex environments. Beyond technical accuracy, the approach reduces barriers to advanced 3D forest monitoring, offering practical significance for urban forest evaluation, carbon accounting, and scalable deployment in resource-limited regions.