11 citations as recorded by crossref.

1. On the use of packing models for the prediction of fluvial sediment porosity C. Rettinger et al. 10.5194/esurf-11-1097-2023
2. Robust estimations of areal grain size distribution from geometric surface roughness in a proglacial outwash area C. Hiller et al. 10.1016/j.geomorph.2023.108857
3. Check dam impact on sediment loads: example of the Guerbe River in the Swiss Alps – a catchment scale experiment A. do Prado et al. 10.5194/hess-28-1173-2024
4. Comparison of three grain size measuring methods applied to coarse-grained gravel deposits P. Garefalakis et al. 10.1016/j.sedgeo.2023.106340
5. Sediment controls on the transition from debris flow to fluvial channels in steep mountain ranges A. Neely & R. DiBiase 10.1002/esp.5553
6. Automated grain sizing from uncrewed aerial vehicles imagery of a gravel‐bed river: Benchmarking of three object‐based methods R. Miazza et al. 10.1002/esp.5782
7. 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. 10.1002/esp.5755
8. The grain size of sediments delivered to steep debris‐flow prone channels prior to and following wildfire A. Neely et al. 10.1002/esp.5819
9. Drone-based photogrammetry for riverbed characteristics extraction and flood discharge modeling in taiwan’s mountainous rivers L. Liu 10.1016/j.measurement.2023.113386
10. 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. 10.1002/esp.5755
11. Grain size of fluvial gravel bars from close-range UAV imagery – uncertainty in segmentation-based data D. Mair et al. 10.5194/esurf-10-953-2022