Hydro-morphological mapping of river reaches using videos captured with UAS

dc.contributor.authorEltner Anette
dc.contributor.authorBertalan Lászlo
dc.contributor.authorGrundmann Jens
dc.contributor.authorPerks Matthew Thomas
dc.contributor.authorLotsari Eliisa
dc.contributor.organizationfi=maantieteen ja geologian laitos|en=Department of Geography and Geology|
dc.contributor.organization-code1.2.246.10.2458963.20.23186815876
dc.converis.publication-id67452967
dc.converis.urlhttps://research.utu.fi/converis/portal/Publication/67452967
dc.date.accessioned2022-10-28T13:01:27Z
dc.date.available2022-10-28T13:01:27Z
dc.description.abstract<p>Unoccupied aerial systems (UASs) are frequently used in the field of fluvial geomorphology due to their capabilities for observing the continuum rather than single sample points. We introduce a (semi-)automatic workflow to measure river bathymetry and surface flow velocities of entire river reaches at high resolution, based on UAS videos and imagery. Video frame filtering improved the visibility of the riverbed using frame co-registration and averaging with a median filter. Subsequently, these video frames were incorporated with still images acquired by UASs into a structure from motion (SfM) photogrammetry approach to reconstruct the camera poses (i.e. positions and orientations) and the 3D point cloud of the river reach. The heights of submerged points were further processed using small-angle and multi-view refraction correction approaches to account for the refraction impact. The flow velocity pattern of the river surface was measured using the estimated camera pose from SfM, the reconstructed bathymetric point cloud and the co-registered video frames in combination with image velocimetry analysis. Finally, discharge was estimated at selected cross-sections, considering the average surface velocity and the bathymetry. Three case studies were considered to assess the performance of the workflow under different environmental conditions. The studied river reaches spanned a length between 0.15 and 1 km. The bathymetry was reconstructed with average deviations to RTK-GNSS point measurements as low as 1 cm with a standard deviation of 6 cm. If frames were processed with the median filter, the number of underwater points increased by up to 21%. The image-based surface velocities revealed an average deviation to reference measurements between 0.05 and 0.08 m s(-1). The image-based discharge was estimated with deviations to ADCP references of up to 5%, however this was sensitive to errors in water-level retrieval. The output of our workflow can provide a valuable input to hydro-morphological models.</p>
dc.identifier.eissn1096-9837
dc.identifier.jour-issn0197-9337
dc.identifier.olddbid179164
dc.identifier.oldhandle10024/162258
dc.identifier.urihttps://www.utupub.fi/handle/11111/48514
dc.identifier.urlhttps://onlinelibrary.wiley.com/doi/10.1002/esp.5205
dc.identifier.urnURN:NBN:fi-fe2021102752643
dc.language.isoen
dc.okm.affiliatedauthorLotsari, Eliisa
dc.okm.discipline1171 Geosciencesen_GB
dc.okm.discipline1171 Geotieteetfi_FI
dc.okm.internationalcopublicationinternational co-publication
dc.okm.internationalityInternational publication
dc.okm.typeA1 ScientificArticle
dc.publisherWILEY
dc.publisher.countryUnited Kingdomen_GB
dc.publisher.countryBritanniafi_FI
dc.publisher.country-codeGB
dc.relation.doi10.1002/esp.5205
dc.relation.ispartofjournalEarth Surface Processes and Landforms
dc.source.identifierhttps://www.utupub.fi/handle/10024/162258
dc.titleHydro-morphological mapping of river reaches using videos captured with UAS
dc.year.issued2021

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