target discrimination on portable radar
Description
This application of machine learning is intended as a pilot effort to discriminate among radar target types, specifically between flying animals and precipitation.
Detailed example
The algorithm outputs a probability of whether a radar target is biological or precipitation.
AI / analytics pattern
Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relationships.
Automation level / stage
b) Pilot – The use case has been deployed in a limited test or pilot capacity.
Expected benefit
quantify moth movement into the Yellowstone ecosystem, or rather, the calories they represent as a food source. Army cutworm moths are a critical but poorly understood food for grizzly bears
Controls / human review
ATO: No; PIA: Not published
Data needed
Training data were derived from USGS-operated portable radars and scored by USGS personnel. No data was provided to the agency.