A framework to facilitate development and testing of image‐based river velocimetry algorithms

Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact pur...

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Published inEarth surface processes and landforms Vol. 49; no. 4; pp. 1361 - 1382
Main Authors Legleiter, Carl J., Kinzel, Paul J.
Format Journal Article
LanguageEnglish
Published Bognor Regis Wiley Subscription Services, Inc 30.03.2024
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ISSN0197-9337
1096-9837
DOI10.1002/esp.5772

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Abstract Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image‐derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image‐derived velocities were generally in close agreement with those from the flow model (root mean square error <10% and mean bias <3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge ( R2=0.97 at baseflow) and became less reliable as the mean flow velocity increased ( R2=0.92 for an intermediate discharge and R2=0.86 at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV‐based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms. The Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER) framework facilitates testing of image‐based river velocimetry algorithms and can foster their improvement. The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as directed by the local velocity field, and thus construct an image sequence specific to the reach of interest. Using this time series as input to a velocimetry algorithm enables exhaustive accuracy assessment via comparison to the modelled flow field.
AbstractList Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image‐derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image‐derived velocities were generally in close agreement with those from the flow model (root mean square error <10% and mean bias <3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge ( R2=0.97 at baseflow) and became less reliable as the mean flow velocity increased ( R2=0.92 for an intermediate discharge and R2=0.86 at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV‐based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms. The Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER) framework facilitates testing of image‐based river velocimetry algorithms and can foster their improvement. The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as directed by the local velocity field, and thus construct an image sequence specific to the reach of interest. Using this time series as input to a velocimetry algorithm enables exhaustive accuracy assessment via comparison to the modelled flow field.
Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image‐derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image‐derived velocities were generally in close agreement with those from the flow model (root mean square error <10% and mean bias <3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge (R2=0.97 at baseflow) and became less reliable as the mean flow velocity increased (R2=0.92 for an intermediate discharge and R2=0.86 at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV‐based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms.
Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image‐derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image‐derived velocities were generally in close agreement with those from the flow model (root mean square error <10% and mean bias <3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge ( at baseflow) and became less reliable as the mean flow velocity increased ( for an intermediate discharge and at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV‐based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms.
Author Legleiter, Carl J.
Kinzel, Paul J.
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  surname: Kinzel
  fullname: Kinzel, Paul J.
  organization: US Geological Survey, Observing Systems Division
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Cites_doi 10.1016/j.jhydrol.2023.130233
10.3390/rs12030384
10.1016/j.cageo.2017.07.009
10.3390/w12071874
10.1080/15715124.2007.9635310
10.1029/2022WR032251
10.3390/w13030247
10.1007/s10661-018-6848-3
10.3390/drones5030081
10.1201/b22619-145
10.1016/j.advwatres.2015.09.017
10.3390/rs12020232www.mdpi.com/journal/remotesensing
10.1029/2008WR006950
10.1029/2020WR029279
10.1029/2021WR031878
10.1002/hyp.13919
10.1016/j.softx.2020.100537
10.3390/rs10122010
10.3390/rs12081282
10.3390/hydrology7030065
10.1002/rra.3773
10.3389/frwa.2021.709269
10.5194/hess-24-1429-2020
10.1016/j.softx.2022.101173
10.3389/frwa.2021.652213
10.1016/j.geomorph.2010.09.030
10.3390/w15010123
10.1016/B978-0-323-85283-8.00012-6
10.1061/JHEND8.HYENG-13591
10.1002/esp.4787
10.5194/hess-27-2051-2023
10.5194/gmd-13-6111-2020
10.1002/rra.893
10.1088/1361-6501/ab808a
10.5194/esurf-7-841-2019
10.3390/w13162206
10.1029/2022WR033822
10.1002/rra.4147
10.3389/frwa.2022.744278
10.1002/esp.2094
10.3390/rs12111789
10.1061/(ASCE)HY.1943-7900.0001922
10.1002/esp.5205
10.5334/jors.334
10.1029/2020WR027833
10.5194/hess-24-5173-2020
10.1002/rra.3973
10.1007/BF03181465
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References 2021; 9
2019; 7
2021; 46
2021; 5
2021; 3
2010; 35
2011
2023; 59
2010
2023; 15
2021; 147
2023; 149
2020; 13
2023; 626
2020; 12
2023a
2016; 93
2020; 34
2018; 190
2021; 57
2017; 109
2021; 13
2020; 7
2021; 37
2020; 31
2023
2022
2022; 4
2006; 22
2023; 27
2020
2003; 6
2022; 58
2020; 24
2007; 5
2008; 44
2020; 45
2012; 137
2018; 10
2023b; 39
2022; 38
2022; 19
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e_1_2_9_33_1
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e_1_2_9_14_1
e_1_2_9_39_1
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e_1_2_9_28_1
e_1_2_9_47_1
e_1_2_9_30_1
e_1_2_9_53_1
Eltner A. (e_1_2_9_16_1) 2022
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e_1_2_9_11_1
e_1_2_9_34_1
e_1_2_9_13_1
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e_1_2_9_40_1
e_1_2_9_46_1
e_1_2_9_23_1
e_1_2_9_44_1
e_1_2_9_7_1
e_1_2_9_5_1
e_1_2_9_3_1
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References_xml – year: 2011
– volume: 149
  issue: 11
  year: 2023
  article-title: Discharge estimation using video recordings from small unoccupied aircraft systems
  publication-title: Journal of Hydraulic Engineering
– volume: 12
  year: 2020
  article-title: PIV‐image‐generator: An image generating software package for planar PIV and optical flow benchmarking
  publication-title: SoftwareX
– volume: 93
  start-page: 62
  issue: Part A
  year: 2016
  end-page: 74
  article-title: The international river interface cooperative: Public domain flow and morphodynamics software for education and applications
  publication-title: Advances in Water Resources
– volume: 5
  issue: 3
  year: 2021
  article-title: Recent advancements and perspectives in UAS‐based image velocimetry
  publication-title: Drones
– start-page: 231
  year: 2023
  end-page: 269
– volume: 10
  issue: 12
  year: 2018
  article-title: Optical tracking velocimetry (OTV): Leveraging optical flow and trajectory‐based filtering for surface streamflow observations
  publication-title: Remote Sensing
– volume: 5
  start-page: 105
  issue: 2
  year: 2007
  end-page: 114
  article-title: Development of a non‐intrusive and efficient flow monitoring technique: the space‐time image velocimetry (STIV)
  publication-title: International Journal of River Basin Management
– volume: 13
  issue: 3
  year: 2021
  article-title: Optical methods for river monitoring: A simulation‐based approach to explore optimal experimental setup for LSPIV
  publication-title: Water
– volume: 44
  issue: W00D19
  year: 2008
  article-title: Large‐scale particle image velocimetry for measurements in riverine environments
  publication-title: Water Resources Research
– volume: 34
  start-page: 5167
  issue: 25
  year: 2020
  end-page: 5175
  article-title: Refining image‐velocimetry performances for streamflow monitoring: Seeding metrics to errors minimization
  publication-title: Hydrological Processes
– volume: 3
  start-page: 151
  issue: December
  year: 2021
  article-title: Considerations when applying large‐scale PIV and PTV for determining river flow velocity
  publication-title: Frontiers in Water
– volume: 12
  issue: 7
  year: 2020
  article-title: Macro‐turbulent flow and its impacts on sediment transport potential of a subarctic river during ice‐covered and open‐channel conditions
  publication-title: Water
– volume: 12
  issue: 8
  year: 2020
  article-title: Inferring surface flow velocities in sediment‐laden Alaskan rivers from optical image sequences acquired from a helicopter
  publication-title: Remote Sensing
– volume: 27
  start-page: 2051
  issue: 10
  year: 2023
  end-page: 2073
  article-title: Adaptively monitoring streamflow using a stereo computer vision system
  publication-title: Hydrology and Earth System Sciences
– volume: 12
  issue: 11
  year: 2020
  article-title: Metrics for the quantification of seeding characteristics to enhance image velocimetry performance in rivers
  publication-title: Remote Sensing
– volume: 35
  start-page: 1867
  issue: 15
  year: 2010
  end-page: 1872
  article-title: Remote sensing of rivers: The emergence of a subdiscipline in the river sciences
  publication-title: Earth Surface Processes and Landforms
– volume: 31
  issue: 9
  year: 2020
  article-title: Application of masked two‐dimensional Fourier spectra for improving the accuracy of STIV‐based river surface flow velocity measurements
  publication-title: Measurement Science and Technology
– volume: 57
  issue: 2
  year: 2021
  article-title: How to avoid and correct biased riverine surface image velocimetry
  publication-title: Water Resources Research
– volume: 46
  start-page: 2773
  issue: 14
  year: 2021
  end-page: 2787
  article-title: Hydro‐morphological mapping of river reaches using videos captured with UAS
  publication-title: Earth Surface Processes and Landforms
– volume: 24
  start-page: 1429
  issue: 3
  year: 2020
  end-page: 1445
  article-title: Technical note: flow velocity and discharge measurement in rivers using terrestrial and unmanned‐aerial‐vehicle imagery
  publication-title: Hydrology and Earth System Sciences
– year: 2022
– volume: 13
  start-page: 6111
  issue: 12
  year: 2020
  end-page: 6130
  article-title: KLT‐IV v1.0: Image velocimetry software for use with fixed and mobile platforms
  publication-title: Geoscientific Model Development
– volume: 38
  start-page: 1192
  issue: 6
  year: 2022
  end-page: 1198
  article-title: Surface image velocimetry: Aerial tracer particle distribution system and techniques for reducing environmental noise with coloured tracer particles
  publication-title: River Research and Applications
– start-page: 12
  year: 2010
– volume: 7
  issue: 3
  year: 2020
  article-title: On the uncertainty of the image velocimetry method parameters
  publication-title: Hydrology
– volume: 45
  start-page: 157
  issue: 1
  year: 2020
  end-page: 188
  article-title: Remotely sensed rivers in the Anthropocene: State of the art and prospects
  publication-title: Earth Surface Processes and Landforms
– volume: 59
  issue: 2
  year: 2023
  article-title: Moving aircraft river velocimetry (MARV): framework and proof‐of‐concept on the Tanana River
  publication-title: Water Resources Research
– volume: 24
  start-page: 5173
  year: 2020
  end-page: 5185
  article-title: Spatial distribution of tracers for optical sensing of stream surface flow
  publication-title: Hydrology and Earth System Sciences Discussions
– volume: 57
  issue: 8
  year: 2021
  article-title: Instantaneous river‐wide water surface velocity field measurements at centimeter scales using infrared quantitative image velocimetry
  publication-title: Water Resources Research
– volume: 15
  issue: 1
  year: 2023
  article-title: Uncertainty analysis for image‐based streamflow measurement: The influence of ground control points
  publication-title: Water
– volume: 626
  year: 2023
  article-title: An automatic ANN‐based procedure for detecting optimal image sequences supporting LS‐PIV applications for rivers monitoring
  publication-title: Journal of Hydrology
– volume: 4
  year: 2022
  article-title: A method for analysis of spatial uncertainty in image based surface velocimetry
  publication-title: Frontiers in Water
– volume: 6
  start-page: 245
  issue: 3
  year: 2003
  end-page: 252
  article-title: Unseeded and seeded PIV measurements of river flows videotaped from a helicopter
  publication-title: Journal of Visualization
– volume: 12
  issue: 3
  year: 2020
  article-title: Drone‐based optical measurements of heterogeneous surface velocity fields around fish passages at hydropower dams
  publication-title: Remote Sensing
– volume: 22
  start-page: 79
  issue: 1
  year: 2006
  end-page: 89
  article-title: Applying spatial hydraulic principles to quantify stream habitat
  publication-title: River Research and Applications
– volume: 58
  issue: 12
  year: 2022
  article-title: Synthetic river flow videos for evaluating image‐based velocimetry methods
  publication-title: Water Resources Research
– volume: 137
  start-page: 74
  issue: 1
  year: 2012
  end-page: 86
  article-title: Making riverscapes real
  publication-title: Geomorphology
– volume: 13
  issue: 16
  year: 2021
  article-title: Probabilistic evaluation and filtering of image velocimetry measurements
  publication-title: Water
– year: 2023a
– volume: 59
  issue: 1
  year: 2023
  article-title: Validation of an uncertainty propagation method for moving‐boat acoustic Doppler current profiler discharge measurements
  publication-title: Water Resources Research
– volume: 39
  start-page: 1457
  issue: 8
  year: 2023b
  end-page: 1468
  article-title: The toolbox for river velocimetry using images from aircraft (TRiVIA)
  publication-title: River Research and Applications
– volume: 37
  start-page: 555
  issue: 4
  year: 2021
  end-page: 568
  article-title: The optical river bathymetry toolkit
  publication-title: River Research and Applications
– volume: 109
  start-page: 323
  year: 2017
  end-page: 330
  article-title: Rectification of Image Velocity Results (RIVeR): A simple and user‐friendly toolbox for large scale water surface particle image velocimetry (PIV) and particle tracking velocimetry (PTV)
  publication-title: Computers & Geosciences
– year: 2020
– year: 2023
– volume: 7
  start-page: 841
  year: 2019
  end-page: 857
  article-title: Quantifying the restoration success of wood introductions to increase coho salmon winter habitat
  publication-title: Earth Surface Dynamics
– volume: 190
  start-page: 460
  issue: 8
  year: 2018
  article-title: Exploring the optimal experimental setup for surface flow velocity measurements using PTV
  publication-title: Environmental Monitoring and Assessment
– volume: 147
  start-page: 1
  issue: 10
  year: 2021
  end-page: 11
  article-title: Dynamic selection of exposure time for turbulent flow measurements
  publication-title: Journal of Hydraulic Engineering
– volume: 3
  year: 2021
  article-title: Surface flow velocities from space: particle image velocimetry of satellite video of a large, sediment‐laden river
  publication-title: Frontiers in Water
– volume: 12
  issue: 2
  year: 2020
  article-title: An evaluation of image velocimetry techniques under low flow conditions and high seeding densities using unmanned aerial systems
  publication-title: Remote Sensing
– volume: 19
  year: 2022
  article-title: VISION: VIdeo StabilisatION using automatic features selection for image velocimetry analysis in rivers
  publication-title: SoftwareX
– volume: 9
  start-page: 12
  issue: 1
  year: 2021
  article-title: Particle image velocimetry for MATLAB: Accuracy and enhanced algorithms in PIVlab
  publication-title: Journal of Open Research Software
– ident: e_1_2_9_2_1
  doi: 10.1016/j.jhydrol.2023.130233
– ident: e_1_2_9_51_1
  doi: 10.3390/rs12030384
– ident: e_1_2_9_37_1
  doi: 10.1016/j.cageo.2017.07.009
– ident: e_1_2_9_32_1
  doi: 10.3390/w12071874
– ident: e_1_2_9_20_1
  doi: 10.1080/15715124.2007.9635310
– ident: e_1_2_9_5_1
  doi: 10.1029/2022WR032251
– ident: e_1_2_9_44_1
  doi: 10.3390/w13030247
– ident: e_1_2_9_10_1
  doi: 10.1007/s10661-018-6848-3
– ident: e_1_2_9_9_1
  doi: 10.3390/drones5030081
– ident: e_1_2_9_50_1
  doi: 10.1201/b22619-145
– ident: e_1_2_9_36_1
  doi: 10.1016/j.advwatres.2015.09.017
– ident: e_1_2_9_38_1
  doi: 10.3390/rs12020232www.mdpi.com/journal/remotesensing
– ident: e_1_2_9_24_1
– ident: e_1_2_9_35_1
  doi: 10.1029/2008WR006950
– ident: e_1_2_9_47_1
  doi: 10.1029/2020WR029279
– ident: e_1_2_9_11_1
  doi: 10.1029/2021WR031878
– start-page: 12
  volume-title: Proceedings of the 4th Federal Interagency Hydrologic Modeling Conference and the 9th Federal Interagency Sedimentation Conference
  year: 2010
  ident: e_1_2_9_21_1
– ident: e_1_2_9_41_1
  doi: 10.1002/hyp.13919
– ident: e_1_2_9_34_1
  doi: 10.1016/j.softx.2020.100537
– ident: e_1_2_9_53_1
  doi: 10.3390/rs10122010
– ident: e_1_2_9_55_1
– ident: e_1_2_9_26_1
  doi: 10.3390/rs12081282
– ident: e_1_2_9_45_1
  doi: 10.3390/hydrology7030065
– ident: e_1_2_9_25_1
  doi: 10.1002/rra.3773
– ident: e_1_2_9_49_1
– ident: e_1_2_9_23_1
  doi: 10.3389/frwa.2021.709269
– ident: e_1_2_9_17_1
  doi: 10.5194/hess-24-1429-2020
– ident: e_1_2_9_42_1
  doi: 10.1016/j.softx.2022.101173
– ident: e_1_2_9_27_1
  doi: 10.3389/frwa.2021.652213
– volume-title: UAVs for the environmental sciences
  year: 2022
  ident: e_1_2_9_16_1
– ident: e_1_2_9_6_1
  doi: 10.1016/j.geomorph.2010.09.030
– ident: e_1_2_9_31_1
  doi: 10.3390/w15010123
– ident: e_1_2_9_52_1
  doi: 10.1016/B978-0-323-85283-8.00012-6
– ident: e_1_2_9_14_1
  doi: 10.1061/JHEND8.HYENG-13591
– ident: e_1_2_9_40_1
  doi: 10.1002/esp.4787
– ident: e_1_2_9_22_1
  doi: 10.5194/hess-27-2051-2023
– ident: e_1_2_9_28_1
– ident: e_1_2_9_39_1
  doi: 10.5194/gmd-13-6111-2020
– ident: e_1_2_9_7_1
  doi: 10.1002/rra.893
– ident: e_1_2_9_19_1
  doi: 10.1088/1361-6501/ab808a
– ident: e_1_2_9_3_1
  doi: 10.5194/esurf-7-841-2019
– ident: e_1_2_9_46_1
  doi: 10.3390/w13162206
– ident: e_1_2_9_30_1
  doi: 10.1029/2022WR033822
– ident: e_1_2_9_29_1
  doi: 10.1002/rra.4147
– ident: e_1_2_9_48_1
  doi: 10.3389/frwa.2022.744278
– ident: e_1_2_9_33_1
  doi: 10.1002/esp.2094
– ident: e_1_2_9_8_1
  doi: 10.3390/rs12111789
– ident: e_1_2_9_13_1
  doi: 10.1061/(ASCE)HY.1943-7900.0001922
– ident: e_1_2_9_15_1
  doi: 10.1002/esp.5205
– ident: e_1_2_9_54_1
  doi: 10.5334/jors.334
– ident: e_1_2_9_12_1
  doi: 10.1029/2020WR027833
– ident: e_1_2_9_43_1
  doi: 10.5194/hess-24-5173-2020
– ident: e_1_2_9_4_1
  doi: 10.1002/rra.3973
– ident: e_1_2_9_18_1
  doi: 10.1007/BF03181465
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Snippet Image‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must...
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SubjectTerms Accuracy
algorithm development and testing
Algorithms
Base flow
Discharge
Estimates
Flow velocity
Fluid flow
Hydraulics
hydrodynamic modelling
Hydrodynamic models
Hydrodynamics
Image processing
Image sequencing
image simulation
image velocimetry
Interrogation
Particle image velocimetry
Rivers
Sensitivity analysis
Sequencing
Simulators
uncertainty characterization
Vectors
Velocity
Velocity estimation
Title A framework to facilitate development and testing of image‐based river velocimetry algorithms
URI https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fesp.5772
https://www.proquest.com/docview/2954639312
Volume 49
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