USDA · USDA-151 · record R1449

Predicting fire severity potential in future wildfires in California

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: 2025-08-01 (day precision)Source: 8/1/2025
Withheld from public reporting: Not reported

Mission

Topic area: Energy and the Environment
Operational functions: No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Provide information on where high fire severity (high vegetation mortality) is likely to occur during future wildfires. Provides information for planning where to conduct management activities to lower the adverse effects of future wildfire.

Expected benefits

Cost savings. Reducing adverse effects of wildfire on forest resources and human communities.

System outputs

End product is a series of fire severity maps that estimate or predict where future wildfire will burn hotter and cause more vegetation mortality.

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: Not reported

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: Used observed fire severity data collected on all wildfires with size greater than 1000 acres in California.
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