Mandlburger, G., Pfennigbauer, M., Schwarz, R., & Pöppl, F. (2023). A decade of progress in topo-bathymetric laser scanning exemplified by the pielach river dataset. In ISPRS Geospatial Week 2023 (pp. 1123–1130). International Society for Photogrammetry and Remote Sensing. https://doi.org/10.5194/isprs-annals-X-1-W1-2023-1123-2023
Topo-bathymetric laser scanning featuring high spatial resolution and a seamless transition within the littoral zone from land to water evolved considerably in the last decade due to progress in both sensor technology and processing methods. Unlike early systems that focused solely on maximizing depth of penetration, topo-bathymetric scanners enable detailed description of coastal and inland waters at a level of detail that opens up applications in hydromorphology, hydraulic engineering, ecohydraulics, and hydrobiology. Since 2013, a near-natural river section of the pre-alpine Pielach River has been repeatedly surveyed with bathymetric LiDAR sensors from manned and unmanned aerial platforms. The captured time series not only constitutes a valuable data basis for analyzing morphometric change in response to recurring flood peaks, but also allows to trace the progress in sensor, platform and data processing technology. In this contribution we demonstrate that over the last ten years, the depth performance could be increased by approximately 60 %, starting from 1 Secchi depths to more than 2 Secchi depths with sub-m spatial resolution. We furthermore focus on current approaches for improving the geometric sensor calibration, which allow integrated processing of GNSS-, IMU- and LiDAR observations for concurrent calculation of both flight trajectories and 3D point clouds with an absolute accuracy better than 5 cm. This is specifically important for repeat surveys and monitoring of fluvial processes. While this contribution confirms substantial progress in the field, further topics like precise modeling of dynamic water surfaces, full waveform processing in complex target situations including littoral vegetation and submerged deadwood, and detection and modeling of underwater vegetation are identified as future research areas.
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Research Areas:
Environmental Monitoring and Climate Adaptation: 100%