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Snapshot · OMB 2025 inventory · processed Oct 11, 2026
DOI · DOI-0133 · record R2626

Global Detection of Historical Harmful Algal Blooms via combined Satellite Data and Deep Learning Methods

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
Science
Operational functions
No function tag matched Derived by keyword rules; see methodology

Problem the AI is intended to solve

Create a global-scale geospatial database of HABs occurrences over the past 40 years and compile in-situ measured HAB events and related parameters, remotely sensed data, and machine learning methods.

Expected benefits

Provide resource managers, researchers, and the public with a novel ability to track and compare HABs occurrences across time and space, which could identify systematic trends and patterns that affect multiple inland water bodies.

System outputs

Create a global-scale geospatial database of HABs occurrences over the past 40 years and compile in-situ measured HAB events and related parameters, remotely sensed data, and machine learning methods.

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