DOI · DOI-0087 · record R2666
Developing land cover maps for barrier islands using satellite imagery
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
- 2023-07-19 (day precision)Source: 7/19/2023
- 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
The objective of this ML/AL use case was to map land cover on barrier islands using satellite imagery.
Expected benefits
Prediction of land cover types based on signatures from training data (i.e., pixels with class labels).
System outputs
Prediction of land cover types based on signatures from training data (i.e., pixels with class labels).
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
- 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
- Satellite imagery was used for the mapping process. Photointerpetation and existing land cover maps were used for the training and testing dataset development.
- Federal Data Catalog
- www.sciencebase.gov ↗
Governance
5 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 reviewReported in placeSource: a) Yes – by another appropriate agency office or reviewer not directly involved in the AI’s development
Ongoing monitoringReported in placeSource: a) Yes, sufficient monitoring protocols have been established
Operator trainingReported in placeSource: a) Yes, sufficient and periodic training has been established
Fail-safeNot applicableSource: b) Not applicable
Appeal processReported in progressSource: c) Establishment of an appropriate appeal process is in-progress
User and public consultationNo answer reported
Potential impacts and how they were identified
Not reported