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Machine-learning assisted mining detection product over multispectral imagery in Peru
Solutions library
SAR AnalysisPeru

ILLICIT MINING / PERU

Machine learning accelerated candidate detection while human analysts retained confidence and activity attribution.

MISSION PROFILE05 / 08
01 / OPERATIONAL BRIEF

THE
OBJECTIVE.

Detect and characterize likely illicit mining activity across difficult-to-monitor terrain.

CONSTRAINTS
  • Large search area
  • Visually similar land disturbance
  • Need for reviewable confidence
SOURCE STACK
  • SAR
  • Multispectral imagery
  • Geologic context
  • Open-source reference data
02 / ANALYTICAL METHOD
01

Train candidate detection workflows in Google Earth Engine

02

Generate semi-automated activity polygons

03

Apply analyst confidence and activity-type attribution

03 / MISSION OUTCOMES

WHAT
CHANGED.

Reviewable intelligence built for the next decision, not the final presentation.

01

Candidate mining areas surfaced at scale

02

False positives reduced through analyst review

03

Attributed polygons ready for follow-on monitoring

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THE NEXT COORDINATE

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THE MISSION.

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