Tailings Dam Deformation Monitoring
Uses SBAS-InSAR satellite analysis to provide repeatable, wide-area monitoring of tailings dam movement, helping mining operators detect deformation trends earlier and strengthen environmental and safety compliance oversight.
The Problem
“Early detection of tailings dam deformation using repeatable satellite time-series monitoring”
Organizations face these key challenges:
Manual inspection coverage is spatially limited and intermittent
Large InSAR datasets are difficult for engineers to review consistently
False positives from atmospheric noise, decorrelation, and terrain effects can overwhelm teams
Deformation signals must be linked to operational context to be actionable
Impact When Solved
The Shift
Human Does
- •Conduct periodic field inspections and review survey, GNSS, prism, and piezometer readings
- •Compare current measurements with prior campaigns to identify possible deformation concerns
- •Decide when to escalate geotechnical review or order additional site checks
- •Prepare compliance and safety reporting from inspection records and monitoring results
Automation
Human Does
- •Review prioritized deformation hotspots and decide which areas require field verification
- •Approve geotechnical escalation, remediation actions, and operational responses
- •Investigate exceptions where satellite signals conflict with site conditions or instrument readings
AI Handles
- •Continuously analyze SBAS-InSAR time series to detect abnormal displacement, velocity, and acceleration trends
- •Filter noise and rank anomalies by persistence, spatial clustering, and potential severity
- •Link deformation signals to historical baselines and available operational context to prioritize alerts
- •Generate monitoring summaries, hotspot narratives, and evidence packages for oversight reporting
Operating Intelligence
How Tailings Dam Deformation Monitoring runs once it is live
AI watches every signal continuously.
Humans investigate what it flags.
False positives train the next watch cycle.
Who is in control at each step
Each column marks the operating owner for that step. AI-led actions sit above the divider, human decisions and feedback loops sit below it.
Step 1
Observe
Step 2
Classify
Step 3
Route
Step 4
Exception Review
Step 5
Record
Step 6
Feedback
AI lead
Autonomous execution
Human lead
Approval, override, feedback
AI observes and classifies continuously. Humans only engage on flagged exceptions. Corrections sharpen future detection.
The Loop
6 steps
Observe
Continuously take in operational signals and events.
Classify
Score, grade, or categorize what is coming in.
Route
Send routine items to the right path or queue.
Exception Review
Humans validate flagged edge cases and adjust standards.
Authority gates · 1
The system must not approve geotechnical escalation, remediation actions, or operational responses without human review and sign-off [S1].
Why this step is human
Exception handling requires contextual reasoning and organizational judgment the model cannot reliably provide.
Record
Store outcomes and create the operating audit trail.
Feedback
Corrections and outcomes improve future performance.
1 operating angles mapped
Operational Depth
Technologies
Technologies commonly used in Tailings Dam Deformation Monitoring implementations:
Key Players
Companies actively working on Tailings Dam Deformation Monitoring solutions: