Sangam: A Confluence of Knowledge Streams

Remote in channel 3D models of riverine environments for hydromorphological characterization

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dc.creator Vandrol, Jan
dc.creator Rivas Casado, Monica
dc.creator Blackburn, Kim
dc.creator Waine, Toby W.
dc.creator Leinster, Paul
dc.creator Wright, Ros
dc.date 2018-09-12T10:57:27Z
dc.date 2018-09-12T10:57:27Z
dc.date 2018-06-25
dc.date.accessioned 2022-05-25T16:38:26Z
dc.date.available 2022-05-25T16:38:26Z
dc.identifier Jan Vandrol, Monica Rivas Casado, Kim Blackburn, et al., Remote in channel 3D models of riverine environments for hydromorphological characterization. Remote Sensing, Volume 10, Issue 7, Article number 1005
dc.identifier 2072-4292
dc.identifier https://doi.org/10.3390/rs10071005
dc.identifier http://dspace.lib.cranfield.ac.uk/handle/1826/13476
dc.identifier.uri http://localhost:8080/xmlui/handle/CUHPOERS/182333
dc.description Recent legislative approaches to improve the quality of rivers have resulted in the design and implementation of extensive and intensive monitoring programmes that are costly and time consuming. An important component of assessing the ecological status of a water body as required by the Water Framework Directive is characterising the hydromorphology. Recent advances in autonomous operation and the spatial coverage of monitoring systems enables more rapid 3D models of the river environment to be produced. This study presents a Structure from Motion (SfM) semi-autonomous based framework for the estimation of key reach hydromorphological measures such as water surface area, wetted water width, bank height, bank slope and bank-full width, using in-channel stereo-imagery. The framework relies on a stereo-camera that could be positioned on an autonomous boat. The proposed approach is demonstrated along three 40 m long reaches with differing hydromorphological characteristics. Results indicated that optimal stereo-camera settings need to be selected based on the river appearance. Results also indicated that the characteristics of the reach have an impact on the estimation of the hydromorphological measures; densely vegetated banks, presence of debris and sinuosity along the reach increased the overall error in hydromorphological measure estimation. The results obtained highlight a potential way forward towards the autonomous monitoring of freshwater ecosystems.
dc.language en
dc.publisher MDPI
dc.rights Attribution 4.0 International
dc.rights http://creativecommons.org/licenses/by/4.0/
dc.subject Structure from Motion
dc.subject river monitoring
dc.subject point cloud
dc.subject hydromorphology
dc.subject multi-view stereo-camera
dc.subject terrestrial laser scanning
dc.title Remote in channel 3D models of riverine environments for hydromorphological characterization
dc.type Article


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