Articles | Volume 10, issue 6
https://doi.org/10.5194/esurf-10-1211-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/esurf-10-1211-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| Highlight paper
| 
02 Dec 2022
Research article | Highlight paper |
| 02 Dec 2022
| 02 Dec 2022
Size, shape and orientation matter: fast and semi-automatic measurement of grain geometries from 3D point clouds
Philippe Steer
CORRESPONDING AUTHOR
Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France
Laure Guerit
CORRESPONDING AUTHOR
Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France
Dimitri Lague
Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France
Alain Crave
Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France
Aurélie Gourdon
Univ. Rennes, CNRS, Géosciences Rennes, UMR 6118, 35000 Rennes, France
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- Seamless Quantification of Wet and Dry Riverscape Topography Using UAV Topo-Bathymetric LiDAR C. MacDonell et al. https://doi.org/10.3390/drones9120872
- Roughness analysis of the riverbed in the study of torrential events using terrestrial photogrammetry data V. Nikolova et al. https://doi.org/10.52215/rev.bgs.2024.85.3.277
- Sediment shape as a proxy for fluvial processes: A factorial analysis in the Yarlung Tsangpo Grand Canyon K. Li et al. https://doi.org/10.1111/sed.70108
- The variability of grain size metrics in gravel-bed rivers D. Vázquez-Tarrío & A. Recking https://doi.org/10.1016/j.catena.2025.108974
- Source-to-sink patterns of grain size along the Yamuna River in the Indian Himalaya N. Patel et al. https://doi.org/10.1016/j.geomorph.2025.109909
- Gravel automatic sieving method fusing macroscopic and microscopic characteristics S. Gao et al. https://doi.org/10.1016/j.ijsrc.2024.05.002
- Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography T. Wong et al. https://doi.org/10.1002/esp.5709
- Coarse sediment grain size variability along gravel-bed rivers via automatic grain size detection (a case study of the Ondava River, Slovakia) A. MD et al. https://doi.org/10.1080/19475705.2025.2582752
- 3DPatBody: 3D dataset of human bodies of a patagonian population and their anthropometric measurements M. Trujillo-Jiménez et al. https://doi.org/10.1038/s41597-024-04189-w
- Pro+: Automated protrusion and critical shear stress estimates from 3D point clouds of gravel beds E. Yager et al. https://doi.org/10.1002/esp.5822
- Curvature-based pebble segmentation for reconstructed surface meshes A. Rheinwalt et al. https://doi.org/10.5194/esurf-13-923-2025
- The influence of grain size sorting on the roughness parametrization of gravel riverbeds A. do Prado et al. https://doi.org/10.1016/j.geomorph.2024.109565
- A geometry-driven pipeline for particle size distribution analysis of contacting particles in complex industrial settings J. Lu et al. https://doi.org/10.1016/j.mineng.2026.110279
- Limited influence of bedrock strength on river profiles: the dominant role of sediment dynamics N. Yamanishi & H. Naruse https://doi.org/10.5194/esurf-14-247-2026
- GraphFlood 1.0: an efficient algorithm to approximate 2D hydrodynamics for landscape evolution models B. Gailleton et al. https://doi.org/10.5194/esurf-12-1295-2024
- Enhancing quality inspection efficiency and reliability of unscreened recycled coarse aggregates (RCA) streams using innovative mobile sensor-based technology C. Chang et al. https://doi.org/10.1016/j.dibe.2025.100611
- Quantifying Torrential Watershed Behavior over Time: A Synergistic Approach Using Classical and Modern Techniques A. Petrović et al. https://doi.org/10.3390/earth7010001
- Improving predictions of critical shear stress in gravel bed rivers: Identifying the onset of sediment transport and quantifying sediment structure R. Hodge et al. https://doi.org/10.1002/esp.5842
- OrthoSAM: multi-scale extension of the Segment Anything Model for river pebble delineation from large orthophotos V. Chan et al. https://doi.org/10.5194/esurf-14-391-2026
- Spatial distribution and transport characteristics of debris flow sediment using high resolution UAV images in the Ohya debris flow fan S. Yousefi et al. https://doi.org/10.1016/j.geomorph.2024.109533
- Automated detecting, segmenting and measuring of grains in images of fluvial sediments: The potential for large and precise data from specialist deep learning models and transfer learning D. Mair et al. https://doi.org/10.1002/esp.5755
- Uncertainty analysis of sediment size estimations in gravel-bed reaches in Southern Brazil F. Zambrano et al. https://doi.org/10.1016/j.jsames.2025.105544
24 citations as recorded by crossref.
- Intelligent optimization of particle size distribution in unscreened recycled coarse aggregates using 3D surface analysis C. Chang et al. https://doi.org/10.1016/j.jii.2025.100864
- Downstream rounding rate of pebbles in the Himalaya P. Pokhrel et al. https://doi.org/10.5194/esurf-12-515-2024
- Seamless Quantification of Wet and Dry Riverscape Topography Using UAV Topo-Bathymetric LiDAR C. MacDonell et al. https://doi.org/10.3390/drones9120872
- Roughness analysis of the riverbed in the study of torrential events using terrestrial photogrammetry data V. Nikolova et al. https://doi.org/10.52215/rev.bgs.2024.85.3.277
- Sediment shape as a proxy for fluvial processes: A factorial analysis in the Yarlung Tsangpo Grand Canyon K. Li et al. https://doi.org/10.1111/sed.70108
- The variability of grain size metrics in gravel-bed rivers D. Vázquez-Tarrío & A. Recking https://doi.org/10.1016/j.catena.2025.108974
- Source-to-sink patterns of grain size along the Yamuna River in the Indian Himalaya N. Patel et al. https://doi.org/10.1016/j.geomorph.2025.109909
- Gravel automatic sieving method fusing macroscopic and microscopic characteristics S. Gao et al. https://doi.org/10.1016/j.ijsrc.2024.05.002
- Grain size estimation in fluvial gravel bars using uncrewed aerial vehicles: A comparison between methods based on imagery and topography T. Wong et al. https://doi.org/10.1002/esp.5709
- Coarse sediment grain size variability along gravel-bed rivers via automatic grain size detection (a case study of the Ondava River, Slovakia) A. MD et al. https://doi.org/10.1080/19475705.2025.2582752
- 3DPatBody: 3D dataset of human bodies of a patagonian population and their anthropometric measurements M. Trujillo-Jiménez et al. https://doi.org/10.1038/s41597-024-04189-w
- Pro+: Automated protrusion and critical shear stress estimates from 3D point clouds of gravel beds E. Yager et al. https://doi.org/10.1002/esp.5822
- Curvature-based pebble segmentation for reconstructed surface meshes A. Rheinwalt et al. https://doi.org/10.5194/esurf-13-923-2025
- The influence of grain size sorting on the roughness parametrization of gravel riverbeds A. do Prado et al. https://doi.org/10.1016/j.geomorph.2024.109565
- A geometry-driven pipeline for particle size distribution analysis of contacting particles in complex industrial settings J. Lu et al. https://doi.org/10.1016/j.mineng.2026.110279
- Limited influence of bedrock strength on river profiles: the dominant role of sediment dynamics N. Yamanishi & H. Naruse https://doi.org/10.5194/esurf-14-247-2026
- GraphFlood 1.0: an efficient algorithm to approximate 2D hydrodynamics for landscape evolution models B. Gailleton et al. https://doi.org/10.5194/esurf-12-1295-2024
- Enhancing quality inspection efficiency and reliability of unscreened recycled coarse aggregates (RCA) streams using innovative mobile sensor-based technology C. Chang et al. https://doi.org/10.1016/j.dibe.2025.100611
- Quantifying Torrential Watershed Behavior over Time: A Synergistic Approach Using Classical and Modern Techniques A. Petrović et al. https://doi.org/10.3390/earth7010001
- Improving predictions of critical shear stress in gravel bed rivers: Identifying the onset of sediment transport and quantifying sediment structure R. Hodge et al. https://doi.org/10.1002/esp.5842
- OrthoSAM: multi-scale extension of the Segment Anything Model for river pebble delineation from large orthophotos V. Chan et al. https://doi.org/10.5194/esurf-14-391-2026
- Spatial distribution and transport characteristics of debris flow sediment using high resolution UAV images in the Ohya debris flow fan S. Yousefi et al. https://doi.org/10.1016/j.geomorph.2024.109533
- Automated detecting, segmenting and measuring of grains in images of fluvial sediments: The potential for large and precise data from specialist deep learning models and transfer learning D. Mair et al. https://doi.org/10.1002/esp.5755
- Uncertainty analysis of sediment size estimations in gravel-bed reaches in Southern Brazil F. Zambrano et al. https://doi.org/10.1016/j.jsames.2025.105544
Saved (final revised paper)
Latest update: 09 Jun 2026
Editorial statement
Understanding how sediment moves in rivers is fundamental to the shape of our landscapes and how they evolve. A key part of this understanding is measuring the size and shape of cobbles, pebbles and grains in the bed of a river. Often this measuring task is laborious and carried out by hand. However, this paper presents code and describes a method for measuring this using 3d point cloud data (from a laser scan for example) enabling the automation and rapid measurement.
Understanding how sediment moves in rivers is fundamental to the shape of our landscapes and how...
Short summary
The morphology and size of sediments influence erosion efficiency, sediment transport and the quality of aquatic ecosystem. In turn, the spatial evolution of sediment size provides information on the past dynamics of erosion and sediment transport. We have developed a new software which semi-automatically identifies and measures sediments based on 3D point clouds. This software is fast and efficient, offering a new avenue to measure the geometrical properties of large numbers of sediment grains.
The morphology and size of sediments influence erosion efficiency, sediment transport and the...
