DOI · DOI-0164 · record R2596

Mapping ecohydrological headwater refugia

Department of the Interior · USGS

Overview

Development stage: In development or acquisitionSource: a) Pre-deployment – The use case is in a development or acquisition status.
High-impact designation: Not high-impactSource: c) Not high-impact
Impact justification: Not reported
Start date: Not reported
Withheld from public reporting: NoSource: a) No

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

This application of machine learning is being used to aggregate complex spatial data to develop a statistical model used to create detailed maps of headwater stream resources and habitat.

Expected benefits

cut costs by producing more accurate results when mapping headwater stream resources and habitat that can be used to help ensure water security for the nation and healthy aquatic habitat necessary to maintain safe water resources

System outputs

The supervised machine learning output will include a statistical model that produces raster files of spatial data with habitability scores for each pixel and used to produce high resolution maps of the output.

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: No
Public source code: Not reported

Sourcing

How it was built: Not reported
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: Not reported
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