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Building Detection Filter
Detects buildings from 2 SAR images.
Description
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 Information | Description |
|---|---|
| Block Type | Processing |
| Supported Input Data | Sentinel 1 L1C (GeoTIFF) |
| Input parameters | Set 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 Data | GeoTIFF |
| Resolution | identical to the input |
| Performance | Prediction 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. |
Capabilities
To know more please check the block capabilities specifications.
Terms & Conditions
View the End User License Agreement conditions.