Earth Surface Dynamics
Earth Surface Dynamics
ESurf
Articles | Volume 10, issue 5
Articles | Volume 10, issue 5
https://doi.org/10.5194/esurf-10-953-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-10-953-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 10, issue 5
Research article
 | 
07 Oct 2022
Research article |  | 07 Oct 2022

Grain size of fluvial gravel bars from close-range UAV imagery – uncertainty in segmentation-based data

David Mair, Ariel Henrique Do Prado, Philippos Garefalakis, Alessandro Lechmann, Alexander Whittaker, and Fritz Schlunegger

Viewed

Total article views: 3,461 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
2,520 863 78 3,461 191 78 94
  • HTML: 2,520
  • PDF: 863
  • XML: 78
  • Total: 3,461
  • Supplement: 191
  • BibTeX: 78
  • EndNote: 94
Views and downloads (calculated since 23 May 2022)
Cumulative views and downloads (calculated since 23 May 2022)

Viewed (geographical distribution)

Total article views: 3,461 (including HTML, PDF, and XML) Thereof 3,330 with geography defined and 131 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 08 Nov 2025
Download
Short summary
Grain size data are important for studying and managing rivers, but they are difficult to obtain in the field. Therefore, methods have been developed that use images from small and remotely piloted aircraft. However, uncertainty in grain size data from such image-based products is understudied. Here we present a new way of uncertainty estimation that includes fully modeled errors. We use this technique to assess the effect of several image acquisition aspects on grain size uncertainty.
Read more
Share