Airborne LiDAR Bathymetry (ALB) has been rapidly evolving in recent years and now allows fluvial topography to be mapped in high resolution (>20 points/m²) and height accuracy (<10 cm) for both the aquatic and the riparian area. This article presents methods for enhanced modeling and monitoring of instream meso- and microhabitats based on multitemporal data acquisition. This is demonstrated for a near natural reach of the Pielach River, with data acquired from April 2013 to October 2014, covering two flood events. In comparison with topographic laser scanning, ALB requires a number of specific processing steps. We present, firstly, a novel approach for modeling the water surface in the case of sparse water surface echoes and, secondly, a strategy for improved filtering and modeling of the Digital Terrain Model of the Watercourse (DTM-W). Based on the multitemporal DTM-W we discuss the massive changes of the fluvial topography exhibiting deposition/erosion of 10³ m³ caused by the 30-years flood event in May 2014. Furthermore, for the first time, such a high-resolution data source is used for monitoring of hydro-morphological units (mesohabitat scale) including the consequences for the target fish species nase (Chondrostoma nasus, microhabitat scale). The flood events caused a spatial displacement of the hydro-morphological units but did not effect their overall frequency distribution, which is considered an important habitat feature as it documents resilience against disturbances.

We present the sensor concept and first performance and accuracy assessment results of a novel lightweight topo-bathymetric laser scanner designed for integration on Unmanned Aerial Vehicles (UAVs), light aircraft, and helicopters. The instrument is particularly well suited for capturing river bathymetry in high spatial resolution as a consequence of (i) the low nominal flying altitude of 50–150 m above ground level resulting in a laser footprint diameter on the ground of typically 10–30 cm and (ii) the high pulse repetition rate of up to 200 kHz yielding a point density on the ground of approximately 20–50 points/m². The instrument features online waveform processing and additionally stores the full waveform within the entire range gate for waveform analysis in post-processing. The sensor was tested in a real-world environment by acquiring data from two freshwater ponds and a 500 m section of the pre-Alpine Pielach River (Lower Austria). The captured underwater points featured a maximum penetration of two times the Secchi depth. On dry land, the 3D point clouds exhibited (i) a measurement noise in the range of 1–3 mm; (ii) a fitting precision of redundantly captured flight strips of 1 cm; and (iii) an absolute accuracy of 2–3 cm compared to terrestrially surveyed checkerboard targets. A comparison of the refraction corrected LiDAR point cloud with independent underwater checkpoints exhibited a maximum deviation of 7.8 cm and revealed a systematic depth-dependent error when using a refraction coefficient of n = 1.36 for time-of-flight correction. The bias is attributed to multi-path effects in the turbid water column (Secchi depth: 1.1 m) caused by forward scattering of the laser signal at suspended particles. Due to the high spatial resolution, good depth performance, and accuracy, the sensor shows a high potential for applications in hydrology, fluvial morphology, and hydraulic engineering, including flood simulation, sediment transport modeling, and habitat mapping.

Diameter at breast height (DBH) is one of the most important parameter in forestry. With increasing use of terrestrial and airborne laser scanning in forestry, new exceeding possibilities to directly derive DBH emerge. In particular, high resolution point clouds from laser scanners on board unmanned aerial systems (UAS) are becoming available over forest areas. In this case study, DBH estimation from a UAS point cloud based on modeling the relevant part of the tree stem with a cylinder, is analyzed with respect to accuracy and completeness. As reference, manually measured DBHs and DBHs from terrestrial laser scanning point clouds are used for comparison. We demonstrate that accuracy and completeness of the cylinder fit are depending on the stem diameter. Stems with DBH > 20 cm feature almost 100% successful reconstruction with relative differences to the reference DBH of 9% (DBH 20–30 cm) down to 1.8% for DBH > 40 cm.