Change Detection
Provided by 
The service compares two super-resolved Sentinel-2 images of the same area acquired on different dates and returns polygons of what actually changed: new construction, demolition, earthworks, land-use conversion.
The initial change map comes from principal component analysis followed by K-means clustering on the difference image — an unsupervised approach that needs no training data. The real value, though, is in what comes next: the two great producers of false change — shadows, which move with the solar angle between acquisitions, and vegetation, which changes with the season — are masked explicitly. Shadows are detected with multiple thresholds and then projected according to each scene’s actual solar angle, so a shadow shifting position is never mistaken for a change on the ground.
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