01 / The constraint
Specialists repeatedly placed and reviewed map features across large datasets. The manual process limited coverage and made decisions harder to keep consistent.
Geospatial ML automation
Using machine learning to propose map placements for review.
02Prior-role exampleMap annotation automation
02 / The system
We built a training and inference workflow from historical expert decisions. The system scores proposed placements, routes uncertain cases to human review, and adds approved corrections to the next training set.
03 / The change
The system proposed routine placements. Specialists reviewed uncertain cases, and their corrections returned to the training data.
What this demonstrates
The workflow reduced repeat manual placement while keeping uncertain decisions with specialists.
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