DOI · DOI-0112 · record R2648
RSCC and TCA projects [2024 INV#WO0000000108017]
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
- 2023-06-21 (day precision)Source: 6/21/2023
- Withheld from public reporting
- NoSource: a) No
Mission
- Topic area
- Science
- Operational functions
- No function tag matched Derived by keyword rules; see methodology
Problem the AI is intended to solve
Automated identification of coastal features in remote sensing data, reduced analyst time
Expected benefits
Increased efficiency in identifying coastal features in remote sensing data compared to existing methods that are human analyst time intensive. Increased efficiency was tested by timing traditional methods versus AI/ML methods
System outputs
Elevation and position of dune crest and toe, position of shoreline
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
- marine.usgs.gov ↗
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
- Data used to train and evaluate the model came from various USGS data releases of dune morphology and shorelines.
- Federal Data Catalog
- marine.usgs.gov ↗
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