DOI · DOI-0063 · record R2690

Mapping wood and wood hazards in the Willamette Basin, Oregon

Department of the Interior · USGS

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: 2025-10-01 (day precision)Source: 10/1/2025
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: Image and video analysis Derived by keyword rules; see methodology

Problem the AI is intended to solve

Large wood in rivers pose hazards to people and infrastructure, particularly post wildfire. This work uses neural network models to map large wood in rivers from aerial imagery to understand how wood is distributed throughout river systems pre and post wildfire.

Expected benefits

This work will help inform infrastructure hazards such as at dams and bridges, as well as to river users, such as rafters, inter-tubers, and fishermen.

System outputs

The system output is mapping the location and extent of large wood pre and post wildfires

Technology

AI classification: Other
System name(s): Not reported
Custom-developed code: No
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: Training data is labeled imagery, such as "wood", "water", "sediment", "vegetation", and cross-learning from a previous iteration of the model developed in a different watershed.
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