Forest Health Protection: Survey and mapping of forest damage from insects and diseases using machine learning
Description
Forest Health Protection is responsible for surveying ~500 million acres of forest for forest damage and mapping the risk of mortality from insects and diseases.
Detailed example
Predictions (GIS data and maps) used in decision making
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
Cost savings, increased work efficiency, expanded coverage over hard to reach locations
Controls / human review
ATO: Yes; PIA: Not published
Data needed
Predictors: Satellite and airborne imagery, other Geographical Information System (GIS) data (e.g., soils, topography, pest ranges). Training data: Field collected and other observational data from sources such as Forest Inventory and Analysis, Insect and Disease Surveys, and photointerpretation.