USDA · USDA-018 · record R1324

TreeMap and FuelMap (all versions)

Department of Agriculture · Natural Resources and Environment

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Overview

Development stage: DeployedSource: c) Deployed – The use case is being actively authorized or utilized to support the functions or mission of an agency.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: 2016-10-12 (day precision)Source: 10/12/2016
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

Produce tree-level model of the forests of the US, and corresponding model of fuel loading.

Expected benefits

TreeMap and FuelMap enable modeling of fuel treatments (amount of wood removed, reduction in fire risk), smoke emissions, and biomass estimation

System outputs

The AI outputs maps at 30x30m scale for the Conterminous United States (CONUS) of the imputed Forest Inventory and Analysis (FIA) plot identifier. From these maps, we also create maps of attributes such as forest type, number of live and dead trees per acre, biomass, carbon, etc.

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: Forest inventory plot data from Forest Inventory and Analysis (FIA), and data from Landscape Fire and Resource Management Planning Tools (LANDFIRE) and Daymet
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