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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Veröffentlicht in: | Earth surface processes and landforms 2024-03, Vol.49 (4), p.1361-1382 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | 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 |
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ISSN: | 0197-9337 1096-9837 |
DOI: | 10.1002/esp.5772 |