Channel types predictions for the South Fork Eel River basin

Hervé Guillon, Colin F. Byrne, Belize A. Lane, Samuel Sandoval Solis & Gregory B. Pasternack
Hydrologic and geomorphic classifications have gained traction in response to the increasing need for basin-wide water resources management. Regardless of the selected classification scheme, an open scientific challenge is how to extend information from limited field sites to classify tens of thousands to millions of channel reaches across a basin. To address this spatial scaling challenge, we leveraged machine learning to predict reach-scale geomorphic channel types using publicly available geospatial data.
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11 downloads reported since publication in 2020.

These counts follow the COUNTER Code of Practice, meaning that Internet robots and repeats within a certain time frame are excluded.
What does this mean?