In Situ Calibration and Trajectory Enhancement of UAV and Backpack LiDAR Systems for Fine-Resolution Forest Inventory

Forest inventory has been relying on labor-intensive manual measurements. Using remote sensing modalities for forest gained increasing attention in the last few decades. However, tools deriving accurate tree-level metrics are limited. This paper investigates feasibility of using LiDAR units onboard uncrewed aerial vehicle (UAV) and Backpack mobile mapping systems (MMSs) equipped with an integrated Global Navigation Satellite System/Inertial System (GNSS/INS) to provide high-quality point clouds accurate, fine-resolution inventory. To improve quality acquired clouds, a system-driven strategy mounting parameters estimation trajectory enhancement terrain patches tree trunks is proposed. By minimizing observed discrepancies among conjugate features captured at different timestamps from multiple tracks by single/multiple systems, while considering absolute relative positional/rotational information provided GNSS/INS trajectory, system calibration can be refined. Furthermore, some metrics, such as trunk radius orientation, derived process. evaluate performance proposed strategy, three UAV two datasets covering young mature plantations were used this study. Through sequential enhancement, spatial accuracy improved 20 cm 5 cm. For datasets, when initial was reasonable quality, conducting significantly alignment cloud 30 3 cm, 10 level achieved. lower-quality 1 m misalignment reduced 6 through enhancement. derive products accuracy, required reference process dataset.