DOI · DOI-0158 · record R2604

HOTLink: identifying elevated thermal anomalies at volcanoes [2024 INV#WO0000000109217]

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: 2025-06-09 (day precision)Source: 6/9/2025
Withheld from public reporting: NoSource: a) No

Mission

Topic area: Science
Operational functions: Forecasting and prediction Derived by keyword rules; see methodology

Problem the AI is intended to solve

Moves beyond threshold-based hotspot detection algorithms using computer vision and CNN for improved detection of weka thermal signals that may be the first indiciation of volcanic unrest

Expected benefits

Detects 22% more hotspots at volcanoes and produces 12% fewer false positivies across multiple satellite sensor platforms to accurately characterize background and eruptive periods, as well as providing probabilistic measures of detection confidence.

System outputs

Hotspot detections with probabilities, quantitative time series of volcanic radiative power

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: github.com ↗

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: Yes
Demographic features: k) None of the above
Training and evaluation data: Satellite thermal images
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