Articles | Volume 25, issue 9
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-5105-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
22 Sep 2021
Research article |
| 22 Sep 2021
| 22 Sep 2021
A comparison of tools and techniques for stabilising unmanned aerial system (UAS) imagery for surface flow observations
Robert Ljubičić
CORRESPONDING AUTHOR
Department of Hydraulic and Environmental Engineering, Faculty of
Civil Engineering, University of Belgrade, Belgrade 11120, Serbia
Dariia Strelnikova
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Matthew T. Perks
School of Geography, Politics and Sociology, Newcastle University,
Newcastle upon Tyne NE1 7RU, United Kingdom
Anette Eltner
Institute of Photogrammetry and Remote Sensing, Technische
Universität Dresden, 01069 Dresden, Germany
Salvador Peña-Haro
Photrack AG, Ankerstrasse 16a, 8004 Zurich, Switzerland
Alonso Pizarro
Escuela de Ingeniería en Obras Civiles, Universidad Diego
Portales, 8370109 Santiago, Chile
Silvano Fortunato Dal Sasso
Department of European and Mediterranean Cultures: Architecture,
Environment and Cultural Heritage (DICEM), University of Basilicata, 75100
Matera, Italy
Ulf Scherling
School of Geoinformation, Carinthia University of Applied Sciences, Villach 9524, Austria
Pietro Vuono
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
Salvatore Manfreda
Department of Civil, Architectural and Environmental Engineering,
University of Naples Federico II, 80125 Naples, Italy
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Cited
17 citations as recorded by crossref.
- Measuring zero water level in stream reaches: A comparison of an image‐based versus a conventional method A. Herzog et al. 10.1002/hyp.14658
- Estimating the Average River Cross‐Section Velocity by Observing Only One Surface Velocity Value and Calibrating the Entropic Parameter F. Bahmanpouri et al. 10.1029/2021WR031821
- VISION: VIdeo StabilisatION using automatic features selection for image velocimetry analysis in rivers A. Pizarro et al. 10.1016/j.softx.2022.101173
- River Surface Velocity Estimation Using Optical Flow Velocimetry Improved With Attention Mechanism and Position Encoding Y. Cao et al. 10.1109/JSEN.2022.3186972
- The impacts of low flow, ice‐cover and ice thickness on sediment load in a sub‐arctic river – Modelling sediment transport with particle image velocimetry calibration data sets V. Pajunen et al. 10.1002/esp.5809
- Moving Aircraft River Velocimetry (MARV): Framework and Proof‐of‐Concept on the Tanana River C. Legleiter et al. 10.1029/2022WR033822
- SSIMS-Flow: Image velocimetry workbench for open-channel flow rate estimation R. Ljubičić et al. 10.1016/j.envsoft.2023.105938
- An Active Vibration Isolation and Compensation System for Improving Optical Image Quality: Modeling and Experiment M. Wang et al. 10.3390/mi14071387
- Surface Velocity to Depth-Averaged Velocity—A Review of Methods to Estimate Alpha and Remaining Challenges H. Biggs et al. 10.3390/w15213711
- Comparative Assessment of Different Image Velocimetry Techniques for Measuring River Velocities Using Unmanned Aerial Vehicle Imagery F. Wijaya et al. 10.3390/w15223941
- Satellite Video Remote Sensing for Estimation of River Discharge C. Masafu et al. 10.1029/2023GL105839
- Open-channel flow rate measurement estimation using videos R. Ljubičić & D. Ivetić 10.5937/GK23055045L
- Unmanned Aerial Vehicles Motion Control with Fuzzy Tuning of Cascaded-PID Gains F. Andrade et al. 10.3390/machines10010012
- A Method for Analysis of Spatial Uncertainty in Image Based Surface Velocimetry S. Schweitzer & E. Cowen 10.3389/frwa.2022.744278
- Recent Advancements and Perspectives in UAS-Based Image Velocimetry S. Dal Sasso et al. 10.3390/drones5030081
- Considerations When Applying Large-Scale PIV and PTV for Determining River Flow Velocity M. Jolley et al. 10.3389/frwa.2021.709269
- A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management N. Ubina & S. Cheng 10.3390/drones6010012
13 citations as recorded by crossref.
- Measuring zero water level in stream reaches: A comparison of an image‐based versus a conventional method A. Herzog et al. 10.1002/hyp.14658
- Estimating the Average River Cross‐Section Velocity by Observing Only One Surface Velocity Value and Calibrating the Entropic Parameter F. Bahmanpouri et al. 10.1029/2021WR031821
- VISION: VIdeo StabilisatION using automatic features selection for image velocimetry analysis in rivers A. Pizarro et al. 10.1016/j.softx.2022.101173
- River Surface Velocity Estimation Using Optical Flow Velocimetry Improved With Attention Mechanism and Position Encoding Y. Cao et al. 10.1109/JSEN.2022.3186972
- The impacts of low flow, ice‐cover and ice thickness on sediment load in a sub‐arctic river – Modelling sediment transport with particle image velocimetry calibration data sets V. Pajunen et al. 10.1002/esp.5809
- Moving Aircraft River Velocimetry (MARV): Framework and Proof‐of‐Concept on the Tanana River C. Legleiter et al. 10.1029/2022WR033822
- SSIMS-Flow: Image velocimetry workbench for open-channel flow rate estimation R. Ljubičić et al. 10.1016/j.envsoft.2023.105938
- An Active Vibration Isolation and Compensation System for Improving Optical Image Quality: Modeling and Experiment M. Wang et al. 10.3390/mi14071387
- Surface Velocity to Depth-Averaged Velocity—A Review of Methods to Estimate Alpha and Remaining Challenges H. Biggs et al. 10.3390/w15213711
- Comparative Assessment of Different Image Velocimetry Techniques for Measuring River Velocities Using Unmanned Aerial Vehicle Imagery F. Wijaya et al. 10.3390/w15223941
- Satellite Video Remote Sensing for Estimation of River Discharge C. Masafu et al. 10.1029/2023GL105839
- Open-channel flow rate measurement estimation using videos R. Ljubičić & D. Ivetić 10.5937/GK23055045L
- Unmanned Aerial Vehicles Motion Control with Fuzzy Tuning of Cascaded-PID Gains F. Andrade et al. 10.3390/machines10010012
4 citations as recorded by crossref.
- A Method for Analysis of Spatial Uncertainty in Image Based Surface Velocimetry S. Schweitzer & E. Cowen 10.3389/frwa.2022.744278
- Recent Advancements and Perspectives in UAS-Based Image Velocimetry S. Dal Sasso et al. 10.3390/drones5030081
- Considerations When Applying Large-Scale PIV and PTV for Determining River Flow Velocity M. Jolley et al. 10.3389/frwa.2021.709269
- A Review of Unmanned System Technologies with Its Application to Aquaculture Farm Monitoring and Management N. Ubina & S. Cheng 10.3390/drones6010012
Latest update: 19 Apr 2024
Short summary
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed widespread use of image velocimetry techniques in place of more traditional, usually slower, methods during hydrometric campaigns. In order to minimize the velocity estimation errors, one must stabilise the acquired videos. In this research, we compare the performance of different UAS video stabilisation tools and provide guidelines for their use in videos with different flight and ground conditions.
The rise of new technologies such as drones (unmanned aerial systems – UASs) has allowed...
