Reconstructing bed topography of a shallow river from close-range aerial imagery: Multi-UAV experimental campaign in the Izera river (SW Poland/N Czechia)

The objective of the study is to reconstruct the bathymetry of a shallow river using the Structure-from-Motion algorithm and to evaluate the robustness of the approach by exploring its repeatability and reproducibility. To address this issue, the multi-UAV experimental campaign was organized in SW Poland/N Czechia, and focused on the smoothly flowing Izera river. Unmanned aerial vehicles used to conduct the experiment were: one fixed-wing aircraft (eBee by SenseFly) and three multi-rotor aircrafts (DJI Matrice 210-RTK V2, DJI Mavic 2 Pro, DJI Phantom 4 Pro). Riverbed topography was reconstructed 48 times (2 sites × 4 platforms × 3 resolutions × 2 repetitions) using Structure-from-Motion algorithm, corrected for refraction. The reference elevations of riverbed were obtained using leveling, while water surface elevations were determined by a terrestrial laser scanner. Root mean square errors (RMSE) of the reconstructions of river bottom topography (mostly underestimated) varied between 2.6 cm and 109.3 cm, with the median of 17.5 cm. The error of reconstruction of river bottom topography falls within a typical error range known for through-water photogrammetry. RMSE of the repeatability test for all platforms is smaller than 10 cm in 57 % (up to 76 % for only multi-rotor aircrafts) of the cases and for the reproducibility test in 47 % (up to 60 % for only multi-rotor aircrafts) of the cases. Hence, it was found that the studied approach is robust in terms of its repeatability and reproducibility, predominantly when multi-rotor aircrafts are utilized. The effectiveness of the bottom reconstruction, however, depends on the channel morphology, and specifically decreases at the vicinity of the river banks. • 48 river bathymetry reconstructions: 2 sites, 4 UAVs, 3 resolutions, 2 repetitions. • Structure-from-Motion algorithm and refraction correction were employed. • Median RMSE of riverbed reconstructions was 17.5 cm, varying from 2.6 to 109.3 cm. • Better accuracies were obtained for multi-rotors; resolution revealed no influence. • Reproducibility and repeatability tests confirmed the robustness of this approach.

Authors

Institutions

Publication Details

Journal
Geomorphology
Published
2024-12-07
DOI
https://doi.org/10.1016/j.geomorph.2024.109544
Citations
6
Primary Topic
Remote Sensing and LiDAR Applications
Type
article
Field-Weighted Citation Impact
1.23
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Reconstructing bed topography of a shallow river from close-range aerial imagery: Multi-UAV experimental campaign in the Izera river (SW Poland/N Czechia)

Łukasz Kasprzak, Jakub Langhammer, Michał Halicki, Tomasz Niedzielski et al.
6 citations
Geomorphology
Remote Sensing and LiDAR Applications
1.23
article

Reconstructing bed topography of a shallow river from close-range aerial imagery: Multi-UAV experimental campaign in the Izera river (SW Poland/N Czechia)

Łukasz Kasprzak, Jakub Langhammer, Michał Halicki, Tomasz Niedzielski, Robert Minařík, Joanna Remisz, Grzegorz Walusiak, Stanislav Popelka, Dorota Borowicz, Ján Šašak, Krzysztof Parzóch, Ján Kaňuk, Theodora Lendzioch, Michal Gallay, Jakub Miřijovský, Matylda Witekcor
article en
6 citations

Abstract

The objective of the study is to reconstruct the bathymetry of a shallow river using the Structure-from-Motion algorithm and to evaluate the robustness of the approach by exploring its repeatability and reproducibility. To address this issue, the multi-UAV experimental campaign was organized in SW Poland/N Czechia, and focused on the smoothly flowing Izera river. Unmanned aerial vehicles used to conduct the experiment were: one fixed-wing aircraft (eBee by SenseFly) and three multi-rotor aircrafts (DJI Matrice 210-RTK V2, DJI Mavic 2 Pro, DJI Phantom 4 Pro). Riverbed topography was reconstructed 48 times (2 sites × 4 platforms × 3 resolutions × 2 repetitions) using Structure-from-Motion algorithm, corrected for refraction. The reference elevations of riverbed were obtained using leveling, while water surface elevations were determined by a terrestrial laser scanner. Root mean square errors (RMSE) of the reconstructions of river bottom topography (mostly underestimated) varied between 2.6 cm and 109.3 cm, with the median of 17.5 cm. The error of reconstruction of river bottom topography falls within a typical error range known for through-water photogrammetry. RMSE of the repeatability test for all platforms is smaller than 10 cm in 57 % (up to 76 % for only multi-rotor aircrafts) of the cases and for the reproducibility test in 47 % (up to 60 % for only multi-rotor aircrafts) of the cases. Hence, it was found that the studied approach is robust in terms of its repeatability and reproducibility, predominantly when multi-rotor aircrafts are utilized. The effectiveness of the bottom reconstruction, however, depends on the channel morphology, and specifically decreases at the vicinity of the river banks. • 48 river bathymetry reconstructions: 2 sites, 4 UAVs, 3 resolutions, 2 repetitions. • Structure-from-Motion algorithm and refraction correction were employed. • Median RMSE of riverbed reconstructions was 17.5 cm, varying from 2.6 to 109.3 cm. • Better accuracies were obtained for multi-rotors; resolution revealed no influence. • Reproducibility and repeatability tests confirmed the robustness of this approach.

GeomorphologyVol. 471
University of Pavol Jozef Šafárik (SK), Charles University (CZ), University of Wrocław (PL), Institute of Experimental Physics of the Slovak Academy of Sciences (SK), Agro Business Park (DK), Palacký University Olomouc (CZ)
Life below water
Openalex Percentile: Top 22%
Remote Sensing and LiDAR Applications
1.23
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.