USDA · USDA-154 · record R1452

App for predicting soil temperature during prescribed burns

Department of Agriculture · Natural Resources and Environment

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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: 2025-09-08 (day precision)Source: 9/8/2025
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

It is a tool to assist managers with determining the predicted soil temperature based on fuel load.

Expected benefits

By determining the expected soil temperature, managers can determine how best to do a prescribed burn without damaging tree root systems which could lead to tree death

System outputs

Prediction of soil temperature

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: Soil temperatures at multiple depths during a prescribed burn
Federal Data Catalog: www.fs.usda.gov ↗