For more than a decade, a near natural reach of the pre-alpine Pielach River in eastern Austria has been repeatedly surveyed with laser and photo bathymetry. In this contribution, the authors present an open benchmark dataset (DOI: 10.48436/taz19-r6618), which was captured in October 2024 following a devastating flood event in September 2024 with multicopter drones. They present the measurement campaign including airborne and terrestrial surveys and the data processing steps. Next to standard processing, they introduce new and innovative image-based bathymetry techniques for rivers with dynamic, wavy water surfaces. They show that image sequences can be used to mitigate the water surface dynamics; synchronous oblique drone images can be used to reconstruct the undulating water surface; and Neural Radiance Fields are an alternative option to classical methods for mapping bathymetry.

The authors first captured the entire study area including the alluvial forest with a RIEGL miniVUX-3UAV laser scanner operating a near-infrared (NIR) laser with a wavelength of 905 nm and a pulse repetition frequency of 300 kHz. The sensor is equipped with a RiLOC-E navigation unit, consisting of a helix GNSS antenna, a u-blox dual-band GNSS receiver and a MEMS IMU.

To obtain continuous underwater data, they conducted a topo-bathymetric UAV survey with the RIEGL VQ-840-GL laser scanner.

The full article is published on the DHyG platform, and can be found here.