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This repository houses data and code associated with d50 estimations made by the 'You Only Look Once' computer vision algorithm.

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d50_computer_vision

Data associated with “Different methods of estimating riverbed sediment grain size diverge at the basin scale ” (v2)

Peter Regier, Yunxiang Chen, Kyongho Son, Jie Bao, Brieanne Forbes, Amy E. Goldman, Matthew H. Kaufman, Kenton A. Rod, and James C. Stegen

Summary

This data package is associated with the publication “Different methods of estimating riverbed sediment grain size diverge at the basin scale” published in Frontiers in Earth Science (Regier et al., 2025).

The distribution of sediment grain size in streams and rivers is often quantified by the median grain size (d50), a key metric for understanding and predicting hydrologic and biogeochemical function of streams and rivers. Manual methods to measure d50 are time-consuming and ignore larger grains, while model-based methods to estimate d50 often over-generalize basin characteristics, and therefore cannot accurately represent site-scale heterogeneity. Here, we apply a machine learning-enabled photogrammetry methodology (You Only Look Once, or YOLO) for estimating d50 for grains > 2 mm based on images collected from streams and rivers throughout the Yakima River Basin (YRB). To understand how such methods may help bridge the gaps in resolution and accuracy between manual and catchment characteristics model-based d50 estimates, we compared YOLO d50 values to manual and model-based estimates across the YRB. We found distinct differences among methods for d50 averages and variability, and relationships between d50 estimates and basin characteristics. Source images can be found at https://data.ess-dive.lbl.gov/view/doi:10.15485/1892052.

This data package was originally published in May 2023. It was updated August 2025 (v2; new and modified files). File and folder names were not revised to indicate changes. See the commit history for more details.

Manuscript Reference

The manuscript associated with this repo and Data Package can be cited as follows:

Regier P, Chen Y, Son K, Bao J, Forbes B, Goldman A, Kaufman M, Rod KA and Stegen J (2025) Different methods of estimating riverbed sediment grain size diverge at the basin scale. Front. Earth Sci. 13:1529503. doi: 10.3389/feart.2025.1529503

Data Reference

In addition to this repo, the Data Package is published and publicly available on ESS-DIVE. If using these data, please cite the Data Package with the following citation and DOI:

[data package citation will be added here once the data package is published]

Contact

Peter Regier; peter.regier@pnnl.gov

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This repository houses data and code associated with d50 estimations made by the 'You Only Look Once' computer vision algorithm.

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