Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry

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David, C.G.; Kohl, N.; Casella, E.; Rovere, A.; Ballesteros, P. et al.: Structure-from-Motion on shallow reefs and beaches: potential and limitations of consumer-grade drones to reconstruct topography and bathymetry. In: Coral reefs : journal of the International Society for Reef Studies 40 (2021), Nr. 3, S. 835-851. DOI: https://doi.org/10.1007/s00338-021-02088-9

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Abstract: 
Reconstructing the topography of shallow underwater environments using Structure-from-Motion—Multi View Stereo (SfM-MVS) techniques applied to aerial imagery from Unmanned Aerial Vehicles (UAVs) is challenging, as it involves nonlinear distortions caused by water refraction. This study presents an experiment with aerial photographs collected with a consumer-grade UAV on the shallow-water reef of Fuvahmulah, the Maldives. Under conditions of rising tide, we surveyed the same portion of the reef in ten successive flights. For each flight, we used SfM-MVS to reconstruct the Digital Elevation Model (DEM) of the reef and used the flight at low tide (where the reef is almost entirely dry) to compare the performance of DEM reconstruction under increasing water levels. Our results show that differences with the reference DEM increase with increasing depth, but are substantially larger if no underwater ground control points are taken into account in the processing. Correcting our imagery with algorithms that account for refraction did not improve the overall accuracy of reconstruction. We conclude that reconstructing shallow-water reefs (less than 1 m depth) with consumer-grade UAVs and SfM-MVS is possible, but its precision is limited and strongly correlated with water depth. In our case, the best results are achieved when ground control points were placed underwater and no refraction correction is used.
License of this version: CC BY 4.0 Unported
Document Type: Article
Publishing status: publishedVersion
Issue Date: 2021
Appears in Collections:Fakultät für Bauingenieurwesen und Geodäsie

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pos. country downloads
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1 image of flag of Germany Germany 16 50.00%
2 image of flag of United States United States 9 28.12%
3 image of flag of Indonesia Indonesia 3 9.38%
4 image of flag of Netherlands Netherlands 1 3.12%
5 image of flag of China China 1 3.12%
6 image of flag of Bahrain Bahrain 1 3.12%
7 image of flag of Belgium Belgium 1 3.12%

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