USDA · USDA-152 · record R1450
Forest Inventory and Cruising using GAIA AI
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
- 2025-04-15 (day precision)Source: 4/15/2025
- 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
Intended to solve the problem of collecting forest inventory data in large areas with limited staff and time.
Expected benefits
The AI use case has the potential to generate accurate forest inventory data with less staff and at a higher pace. Increasing the pace and scale of forest management and restoration.
System outputs
A tree list for forest inventory and volume determination (cruising), forest growth, and management data.
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)
- Not reported
- Custom-developed code
- No
- Public source code
- Not reported
Sourcing
- How it was built
- Purchased from vendorSource: a) Purchased from a vendor
- Vendor (as reported)
- GAIA AI
- 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
- No
- Demographic features
- k) None of the above
- Training and evaluation data
- The data used to train the AI ouput is forest plot data collected onsite using the AI system
- 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