ABSTRACT:

This resource is the end product of my project work at the Pixels to Enviro Patterns 2026 workshop, hosted at the University of Nebraska - Lincoln.

For this project, I extracted 3 images per day from 09-05-2025 to 02-20-2026 from GRIME-AI at the USGS site CO Eagle River near Minturn. Using the CVAT annotation tool, I then annotated 15 images spread out at even intervals across that time period for the presence of water, earth, sky, snow, and human infrastructure. I attempted to train GRIME-AI to detect the presence of water in the river by using this annotated set of data to train a water detection model. Finally, I applied the model to the entire initial set of images I extracted and used GRIME-AI's image segmentation tool to produce masks identifying where water was present in each image.

The resource contains all fifteen images I used to train the model with, the file containing my annotations, and a selection of masks demonstrating the output of the model.

This material is based in part upon work supported by the United States Geological Survey.