USDA · USDA-074 · record R1375
Fire Resilient Landscapes
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
- 2021-08-01 (day precision)Source: 8/1/2021
- 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
Assists in planning treatments to reduce wildfire risk and calculate treatment costs
Expected benefits
Cost savings and improving efficiencies
System outputs
Raster and vector surfaces, summary statistics, and graphics
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
- Yes
- Public source code
- github.com ↗
Sourcing
- How it was built
- Developed in-houseSource: b) Developed in-house
- Vendor (as reported)
- Not reported
- 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
- Data is a mixture of tabular, text, and geospatial data, including: map data on roads, streams, and water bodies from OpenStreetMap webservice, existing fuels, TreeMap data, potential operational delineations (PODs), desired future conditions text documents, machine rates cost/calculator excel documents, US Forest Service engineering tables
- 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