Forest disease detection and screening
Description
To improve tree disease diagnosis and screening.
Detailed example
Prediction (e.g., tree is diseased or not diseased, tree is resistant or susceptible).
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
a) Pre-deployment – The use case is in a development or acquisition status.
Expected benefit
Facilitate ongoing efforts within and outside the Forest Service to manage diseases of forest trees. Provide tools for point-of-care diagnosis of tree diseases.
Controls / human review
ATO: No; PIA: Not published
Data needed
Research datasets containing spectral and image data and data on tree disease status, tree size, tree genotype, tree location. Datasets are generated through research activities conducted by and in collaboration with Forest Service and university personnel.