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Dataset (video sequences and orientation information) to measure river surface flow velocities
Metadaten
| Weitere mitwirkende Personen, Institutionen oder Unternehmen | eu - Funder | |
| Für den Inhalt der Forschungsdaten verantwortliche Person(en) | Eltner, Anette - TU Dresden (ORCID: 0000-0003-2065-6245) | |
| Entstehungsjahr oder Entstehungszeitraum | 2019 | |
| Veröffentlichungsjahr | 2019 | |
| Herausgeber | Technische Universität Dresden | |
| Referenzen auf ergänzende Materialien | IsPartOf: 123456789/1403 (Handle) | |
| Inhalt der Forschungsdaten | Audiovisual, Dataset: video sequences used to estimate flow velocity from terrestrial and aerial perspective orientation data to reference image-based measurements | |
| Eigene Spezifikation der Nutzungsrechte | ||
| Inhaber der Nutzungsrechte | Technische Universität Dresden | |
| Nutzungsrechte des Datensatzes | CC-BY-NC-ND-4.0 | |
| Angabe der Fachgebiete | Geography | de |
| Titel des Datensatzes | Dataset (video sequences and orientation information) to measure river surface flow velocities |
Dateien zu dieser Ressource
Die Datenpakete erscheinen in:
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Flow velocity and discharge measurement in rivers using terrestrial and UAV imagery [1]
An automatic workflow is introduced, including an image-based tracking tool, to measure surface flow velocities in rivers. The method is based on PTV and comprises an automatic definition of the search area for particles to track. Tracking is performed in the original images. Only the final tracks are geo-referenced, intersecting the image observations with water surface in object space. Detected particles and corresponding feature tracks are filtered considering particle and flow characteristics to mitigate the impact of sun glare and outliers. The method can be applied to different perspectives, including terrestrial and aerial (i.e. UAV) imagery. To account for camera movements images can be co-registered in an automatic approach. In addition to velocity estimates, discharge is calculated using the surface velocities and wetted cross-section derived from surface models computed with SfM and multi-media photogrammetry. The workflow is tested at two river reaches (paved and natural) in Germany. Reference data is provided by ADCP measurements. At the paved river reach highest deviations of flow velocity and discharge reach 5% and 4%, respectively. At the natural river deviations are larger (26% and 20%, respectively) due to the irregular cross-section shapes hindering accurate contrasting of ADCP- and image-based results. The provided tool enables the measurement of surface flow velocities independently of the perspective from which images are acquired. With the contact-less measurement spatially distributed velocity fields can be estimated and river discharge in previously ungauged and unmeasured regions can be calculated.