Abstract. Bathymetric Laser Scanning (BLS) enables high-resolution mapping of underwater topography using green-wavelength laser pulses that penetrate the water column. However, precise georeferencing of the BLS data is affected by refraction at the air–water interface, which displaces submerged features and affects conventional strip adjustment methods. This paper introduces an integrated refraction-aware georeferencing workflow that combines refraction correction with trajectory and boresight optimization within a unified adjustment framework. Implemented using the scientific OPALS laser scanning software, the workflow starts with direct georeferencing of uncorrected laser returns, derives a water surface model, applies Snell’s law-based refraction correction, and performs iterative strip adjustment until convergence. The approach was validated using UAV-borne topo-bathymetric LiDAR data from Lake Alm (Almsee) in Upper Austria, captured with a RIEGL VQ-840-GE sensor system. Comparative analysis across multiple processing scenarios demonstrates that the proposed integrated method significantly improves internal consistency between overlapping flight strips. The residual height discrepancies, quantified by the median absolute deviation (σMAD), were reduced from 4.5 cm using standard processing workflows to 2.1 cm with the integrated approach — an improvement exceeding 50%. A single processing pass was sufficient for the relatively calm conditions of the test site, though iterative refinement may benefit more dynamic water surfaces. The presented methodology is generic and can be embedded in any laser scanning framework supporting modular georeferencing and refraction correction.
Gottfried Mandlburger, Lucas Dammert, Jan Rhomberg-Kauert et al.· The International Archives o...· 0 citations
Abstract. Airborne laser bathymetry (ALB) is an efficient and accurate tool for mapping submerged environments, particularly shallow water bodies that are difficult to access with surface vessels. Modern ALB systems can achieve accuracies comparable to SONAR. However, multiple factors, including geo-referencing, water surface modelling, and range measurements, influence the resulting point cloud, making analytical error propagation challenging. Empirical evaluation against reference data is therefore essential, but difficult: ALB accuracy is typically in the low centimetre range, requiring reference data of equal or higher accuracy. Robotic total stations enable acquisition of underwater reference data for shallow water depths, e.g., up to 4.5m, with expected accuracies between 3mm to 10mm, depending on water depth, which approaches the inherent accuracy of ALB and limits the evaluation significance. In this study, we assess a UAS-based ALB data set from a mountain lake in Austria using reference planes and points acquired by robotic total stations. We separate the accuracy analysis into trueness and precision to isolate the effects of geo-referencing and water surface modelling from the intrinsic uncertainty of the LiDAR sensor. The results show that geo-referencing introduces the largest systematic bias, while the precision of the ALB data remains approximately 1 cm to 2 cm, even for submerged measurements. These findings demonstrate the high accuracy of state-of-the-art ALB systems and provide a framework for rigorous accuracy assessment in shallow aquatic environments.
Lucas Dammert, Jan Rhomberg-Kauert, P. Amon et al.· The International Archives o...· 0 citations
