Bugnet
Description
Detect and map locations of tree damage caused by insects and disease, separate from fire and harvest-caused damage.
Detailed example
The outputs predict locations where forest change is likely caused by insect or disease damage as opposed to fire or harvest activity.
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 detection of forest damage using satellite imagery and AI is a safer, faster, and cost-efficient way to monitor forest conditions across entire states and in difficult to reach locations.
Controls / human review
ATO: No; PIA: Not published
Data needed
High-resolution satellite imagery; aerial detection surveys; Forest Service Activity Tracking System (FACTS) forest management activity database; Monitoring Trends in Burn Severity (MTBS) fire data.