OMB Individually Reported
Mapping vegetation classes to understand wildfire fuel conditions
Low riskExact public inventory row
Description
Mapping vegetation classes that can be used to understand wildfire fuel condition across space and through time.
Detailed example
Predicted ecological states for the upper Colorado River Basin
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
The machine learning mapping process we have developed can be use to more efficiently and effectively manage fuels for wildland fire
Controls / human review
ATO: No; PIA: Not published
Data needed
Machine learning model was trained and tested using field data collected by BLM, NPS, and USGS, and predicted out using remote sensing data (LandSat)