Open-source Software for Image Analysis and Machine Learning using Watershed Imagery
Publications
GaugeCam lab performance study: we evaluated uncertainty in the image-based water level system based on GRIME2 (published in Journal of Hydrology)
GaugeCam field performance study: we evaluated the performance of GaugeCam relative to traditional measurement methods in the field (published in PLOS Water)
GaugeCam technical note: we describe the algorithms and GRIME2 software used in the lab, field, and current studies (published open access in Water Resources Research)
Improving streamflow monitoring with machine learning: we are using image analysis and machine learning to fill data gaps in hydrologic records; these workflows are inspiration for several GRIME-AI features