USDA · USDA-148 · record R1446
Forest Health Protection: Survey and mapping of forest damage from insects and diseases using machine learning
Department of Agriculture · Natural Resources and Environment
Overview
- Development stage
- PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.
- High-impact designation
- Not high-impactSource: c) Not high-impact
- Impact justification
- Not reported
- Start date
- 2015-12-01 (day precision)Source: 12/1/2015
- Withheld from public reporting
- Not reported
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
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.
Expected benefits
Cost savings, increased work efficiency, expanded coverage over hard to reach locations
System outputs
Predictions (GIS data and maps) used in decision making
Technology
- AI classification
- Classical / predictive MLSource: Classical/Predictive Machine Learning: Models trained on data to make predictions or classifications based on identified patterns or relatio…
- System name(s)
- Natural Resources and Environment (NRE) Forest Service (FS) Advanced platform for Technical Learning and Analytics in the Sciences (ATLAS), USFS Geospatial Platform
- Custom-developed code
- Yes
- Public source code
- Not reported
Sourcing
- How it was built
- Contract and in-houseSource: c) Developed with both contracting and in-house resources
- Vendor (as reported)
- Kikaha Solutions, LLC
- Vendors (standardized)
- None on the standard list
A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.
Data and privacy
- Involves PII
- No
- Privacy Impact Assessment
- Not reported
- Authorization to Operate
- Yes
- Demographic features
- k) None of the above
- Training and evaluation data
- 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.
- Federal Data Catalog
- Not reported
Governance
0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.
Pre-deployment testingNo answer reported
AI impact assessmentNo answer reported
Independent reviewNo answer reported
Ongoing monitoringNo answer reported
Operator trainingNo answer reported
Fail-safeNo answer reported
Appeal processNo answer reported
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported