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An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems

Pearce, Sophie ORCID: https://orcid.org/0000-0002-7428-4793, Ljubičić, R., Peña-Haro, S., Perks, M., Tauro, F. ORCID: https://orcid.org/0000-0002-5176-3492, Pizarro, A., Dal Sasso, S.F., Strelnikova, D., Grimaldi, S., Maddock, Ian ORCID: https://orcid.org/0000-0001-5072-8700, Paulus, G., Plavšić, J., Prodanović, D. and Manfreda, S. (2020) An Evaluation of Image Velocimetry Techniques under Low Flow Conditions and High Seeding Densities Using Unmanned Aerial Systems. Remote Sensing, 12 (2). e232. ISSN 2072-4292

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Abstract

Image velocimetry has proven to be a promising technique for monitoring river flows using remotely operated platforms such as Unmanned Aerial Systems (UAS). However, the application of various image velocimetry algorithms has not been extensively assessed. Therefore, a sensitivity analysis has been conducted on five different image velocimetry algorithms including Large Scale Particle Image Velocimetry (LSPIV), Large-Scale Particle Tracking Velocimetry (LSPTV), Kanade−Lucas Tomasi Image Velocimetry (KLT-IV or KLT), Optical Tracking Velocimetry (OTV) and Surface Structure Image Velocimetry (SSIV), during low river flow conditions (average surface velocities of 0.12−0.14 m s - 1 , Q60) on the River Kolubara, Central Serbia. A DJI Phantom 4 Pro UAS was used to collect two 30-second videos of the surface flow. Artificial seeding material was distributed homogeneously across the rivers surface, to enhance the conditions for image velocimetry techniques. The sensitivity analysis was performed on comparable parameters between the different algorithms, including the particle identification area parameters (such as Interrogation Area (LSPIV, LSPTV and SSIV), Block Size (KLT-IV) and Trajectory Length (OTV)) and the feature extraction rate. Results highlighted that KLT and SSIV were sensitive to changing the feature extraction rate; however, changing the particle identification area did not affect the surface velocity results significantly. OTV and LSPTV, on the other hand, highlighted that changing the particle identification area presented higher variability in the results, while changing the feature extraction rate did not affect the surface velocity outputs. LSPIV proved to be sensitive to changing both the feature extraction rate and the particle identification area. This analysis has led to the conclusions that for surface velocities of approximately 0.12 m s - 1 image velocimetry techniques can provide results comparable to traditional techniques such as ADCPs. However, LSPIV, LSPTV and OTV require additional effort for calibration and selecting the appropriate parameters when compared to KLT-IV and SSIV. Despite the varying levels of sensitivity of each algorithm to changing parameters, all configuration image velocimetry algorithms provided results that were within 0.05 m s - 1 of the ADCP measurements, on average.

Item Type: Article
Additional Information:

This article is part of the special issue "Unmanned Aerial Systems for Surface Hydrology". The full-text of the online published article can be accessed via the official URL.

Uncontrolled Keywords: image velocimetry, UAS, river flow monitoring, LSPIV, LSPTV, KLT, OTV, SSIV, surface flow velocity
Divisions: College of Health, Life and Environmental Sciences > School of Science and the Environment
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Copyright Info: Open access article
SWORD Depositor: Prof. Pub Router
Depositing User: Ian Maddock
Date Deposited: 14 Jan 2020 12:26
Last Modified: 16 Jan 2020 11:58
URI: https://eprints.worc.ac.uk/id/eprint/9037

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