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Building Detection Filter

Detects buildings from 2 SAR images.


Building Detection Filter detects newly built buildings with two time-different SAR images from Sentinel-1.

Automatic change detection on SAR images has been a very difficult task because of its noisy structures. This block uses a deep learning algorithm to achieve overwhelming performances on SAR images.

Supported Workflows

  • Sentinel-1 L1C (GeoTIFF) -> SAR Building Detection Filter
Important: Please note that the input data block Sentinel-1 L1C (GeoTIFF) is currently not available, which affects the usage of this block. An alternative workflow based on Sentinel-1 L1C (SAFE) will be supported soon.
General InformationDescription
Block TypeProcessing
Supported Input DataSentinel 1 L1C (GeoTIFF)
Input parametersSet time = null, time_series with different two times for older and newer image (see example for time here), and limit = 1. Set orbit_direction = 'DESCENDING' or 'ASCENDING' in order to compare with imageries with the same direction. Check with “Dry Run” whether two images are selected properly.
Output DataGeoTIFF
Resolutionidentical to the input
PerformancePrediction Accuracy: 0.99 / IoU: 0.35. This algorithm is optimized for detecting large buildings and aggregated residential housings. In some cases, changes on crop fields are detected, which will be improved in the next version.


To know more please check the block capabilities specifications.

Terms & Conditions

View the End User License Agreement conditions.

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