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Published VersionCC BY V4.0, Open Access
Journal article
Drone-Derived Nearshore Bathymetry: A Comparison of Spectral and Video-Based Inversions
Drones, Vol.9(11), pp.1-19
2025
Abstract
Accurate nearshore bathymetry is an essential dataset for coastal modelling and coastal hazard management, but traditional surveys are expensive and dangerous to conduct in energetic surf zones. Remotely piloted aircraft (RPA) offer a flexible way to collect high spatial and temporal resolution bathymetric data. This study applies deliberately simple workflows with accessible instrumentation to compare video-based and spectral inversion techniques at two contrasting coastal settings: an exposed open beach with relative higher wave energy and turbidity, and a sheltered embayed beach with lower energy conditions. The video-based (UBathy) approach achieved lower errors (0.22–0.41 m RMSE) than the spectral approach (Stumpf) (0.30–0.71 m RMSE), confirming its strength in semi-turbid, low- to moderate-energy settings. Stumpf’s accuracy matched prior findings (~0.5 m errors in clear water) but declined with depth. Areas with sun glint areas and breaking waves are challenging but UBathy performed better in mixed wave conditions. While these errors are higher than traditional hydrographic surveys, they fall within expected RPA-derived ranges presenting opportunities for use in specific coastal management applications. Future improvements may come from reducing reliance on ground control and advancing deep learning-based hybrid methods to filter outliers and improve prediction accuracy on sub-optimal imagery caused by environmental conditions.
Details
- Title
- Drone-Derived Nearshore Bathymetry: A Comparison of Spectral and Video-Based Inversions
- Authors
- Isaac P. Goessling (Corresponding Author) - University of the Sunshine Coast, Queensland, School of Science, Technology and EngineeringJavier X. Leon - University of the Sunshine Coast, Queensland, School of Science, Technology and Engineering
- Publication details
- Drones, Vol.9(11), pp.1-19
- Publisher
- MDPI AG
- Date published
- 2025
- DOI
- 10.3390/drones9110761
- ISSN
- 2504-446X
- Copyright note
- © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
- Data Availability
- The raw data supporting the conclusions of this article will be made available by the authors on request.
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991181428002621
- Output Type
- Journal article
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