Quantifying riverscape topography is challenging because riverscapes comprise of both wet and dry surfaces. Advances have been made in demonstrating the capability of mounting topo-bathymetric LiDAR (Light Detection and Ranging) sensors on crewed, occupied aircraft to quantify riverscape topography. However, only recently has miniaturisation of electronic components enabled topo-bathymetric LiDAR to be mounted on consumer-grade Unoccupied Aerial Vehicles (UAVs). We evaluate the capability of a demonstration YellowScan Navigator topo-bathymetric, full waveform LiDAR sensor, mounted on a DJI Matrice 600 UAV, to survey a 1 km long reach of the braided River Feshie, Scotland. Ground-truth data, with centimetre accuracy, were collected across wet areas using an echo-sounder, and in wet and dry areas using RTK-GNSS (Real-Time Kinematic Global Navigation Satellite System). The processed point cloud had a density of 62 points/m². Ground-truth mean errors (and standard deviation) across dry gravel bars were 0.06 ± 0.04 m, along shallow channel beds were −0.03 ± 0.12 m and for deep channels were −0.08 m ± 0.23 m. Geomorphic units with a concave three-dimensional shape (pools, troughs), associated with deeper water, had larger negative errors and wider ranges of residuals than planar or convex units. The case study demonstrates the potential of using UAV topo-bathymetric LiDAR to enhance survey efficiency but a need to evaluate spatial error distribution.

Quantifying riverscape topography is challenging because riverscapes comprise of both wet and dry surfaces. Over the last decade, considerable advances have been made in demonstrating the capability of mounting topo-bathymetric LiDAR sensors on crewed, occupied aircraft to quantify riverscape topography. However, only recently has miniaturisation of electronic components enabled topo-bathymetric LiDAR to be mounted on consumer-grade Unoccupied Aerial Vehicles (UAVs). Here we evaluate the capability of YellowScan Navigator topo-bathymetric LiDAR sensor, mounted on a DJI Matrice 600 UAV, to survey a 1 km long braided riverscape. This sensor uses full waveform returns, to ensure continuity between underwater points and the surrounding terrain, and has a 44° field of view. In August 2024, a point cloud was collected across a 1 km long, 200 m wide reach of the braided River Feshie, Scotland. Ground-truth data were collected across wet areas using a Sontek M9 Acoustic Doppler Current Profiler (ADCP) as an echo-sounder, and also survey-grade RTK-GNSS (Global Navigation Satellite System) in both wet and dry areas. The processed LiDAR point cloud featured over 10 million points, with a density of approximately 62 points / m2. These points were compared to the ground truth data to assess the vertical accuracy of the survey. Ground-truth mean errors (and standard deviation) across dry gravel bars surveyed with RTK-GNSS were 0.06 ± 0.04 m (n=237). Mean errors along the bed of the shallow channels surveyed with RTK-GNSS were -0.04 ± 0.23 m (n=562). Additionally, mean errors for deeper channels measured with the ADCP’s echo sounder were -0.08m ± 0.23 m (n = 2673). Overall, this case study demonstrates the potential of using a new generation of topo-bathymetric LiDAR sensors that can be mounted on UAVs. This has the potential to further enhance field surveys of wet-dry environments by reducing logistical workloads and increasing efficiency of these surveys. Compared to the various techniques for correcting bathymetric data from Structure-from-Motion imagery or point clouds this direct measurement needs less processing to achieve to continuous topo-bathymetric surface.