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Remote Sens. 2018, 10(9), 1362; https://doi.org/10.3390/rs10091362

Merging Unmanned Aerial Systems (UAS) Imagery and Echo Soundings with an Adaptive Sampling Technique for Bathymetric Surveys

1
Center for Autonomous Sensing and Sampling, University of Oklahoma, Norman, OK 73072, USA
2
School of Meteorology, University of Oklahoma, Norman, OK 73072, USA
3
Department of Geography and Environmental Sustainability, University of Oklahoma, Norman, OK 73019, USA
4
School of Civil Engineering and Environmental Science, University of Oklahoma, Norman, OK 73019, USA
5
School of Electrical and Computer Engineering, University of Oklahoma, Norman, OK 73019, USA
*
Author to whom correspondence should be addressed.
Received: 19 July 2018 / Revised: 15 August 2018 / Accepted: 21 August 2018 / Published: 28 August 2018
(This article belongs to the Special Issue Remote Sensing from Unmanned Aerial Vehicles (UAVs))
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Abstract

Bathymetric surveying to gather information about depths and underwater terrain is increasingly important to the sciences of hydrology and geomorphology. Submerged terrain change detection, water level, and reservoir storage monitoring demand extensive bathymetric data. Despite often being scarce or unavailable, this information is fundamental to hydrodynamic modeling for imposing boundary conditions and building computational domains. In this manuscript, a novel, low-cost, rapid, and accurate method is developed to measure submerged topography, as an alternative to conventional approaches that require significant economic investments and human power. The method integrates two types of Unmanned Aerial Systems (UAS) sampling techniques. The first couples a small UAS (sUAS) to an echosounder attached to a miniaturized boat for surveying submerged topography in deeper water within the range of accuracy. The second uses Structure from Motion (SfM) photogrammetry to cover shallower water areas no detected by the echosounder where the bed is visible from the sUAS. The refraction of light passing through air–water interface is considered for improving the bathymetric results. A zonal adaptive sampling algorithm is developed and applied to the echosounder data to densify measurements where the standard deviation of clustered points is high. This method is tested at a small reservoir in the U.S. southern plains. Ground Control Points (GCPs) and checkpoints surveyed with a total station are used for properly georeferencing of the SfM photogrammetry and assessment of the UAS imagery accuracy. An independent validation procedure providing a number of skill and error metrics is conducted using ground-truth data collected with a leveling rod at co-located reservoir points. Assessment of the results shows a strong correlation between the echosounder, SfM measurements and the field observations. The final product is a hybrid bathymetric survey resulting from the merging of SfM photogrammetry and echosoundings within an adaptive sampling framework. View Full-Text
Keywords: unmanned aerial systems; bathymetry; adaptive sampling; structure from motion; echo sounding; geomorphology; hydrology; reservoirs unmanned aerial systems; bathymetry; adaptive sampling; structure from motion; echo sounding; geomorphology; hydrology; reservoirs
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

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Alvarez, L.V.; Moreno, H.A.; Segales, A.R.; Pham, T.G.; Pillar-Little, E.A.; Chilson, P.B. Merging Unmanned Aerial Systems (UAS) Imagery and Echo Soundings with an Adaptive Sampling Technique for Bathymetric Surveys. Remote Sens. 2018, 10, 1362.

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