IN-SITU CALIBRATION AND TRAJECTORY ENHANCEMENT OF UAV AND BACKPACK LIDAR SYSTEMS FOR HIGH-RESOLUTION FOREST INVENTORY

Abstract

Abstract. Using remote sensing modalities for forest inventory has gained increasing attention in the last few decades. However, tools for deriving accurate tree-level metrics are limited. This paper investigates the feasibility of using LiDAR units onboard uncrewed aerial vehicle (UAV) and Backpack mobile mapping systems (MMS) equipped with an integrated Global Navigation Satellite System/Inertial Navigation System (GNSS/INS) to provide high quality point clouds for accurate, high-resolution forest inventory. To improve the quality of acquired point clouds, a system-driven strategy for mounting parameters refinement and trajectory enhancement using terrain patches and tree trunks is proposed. To evaluate the performance of the proposed strategy, two UAV and one Backpack datasets covering a forest plantation are used in this study. Through sequential system calibration and trajectory enhancement, the spatial accuracy of the UAV point clouds improves from 20 cm to 5 cm. For the Backpack dataset, when the initial trajectory is of reasonable accuracy, conducting trajectory enhancement significantly improves the alignment of the point cloud from 30 cm to 3cm. For a lower-quality trajectory, using the UAV data as a reference, the misalignment is reduced from 1 m to 3 cm.