Annotation: Deep Learning Labels for Satellite and Aerial Imagery

Maintained by the satellite-image-deep-learning organization, this repository provides annotations for deep learning models applied to satellite and aerial imagery. The resource was updated in February 2026 and focuses on the generation of labels for remote sensing datasets.

Use Cases

• Training object detection models using provided bounding boxes for satellite imagery
• Developing semantic segmentation masks for land cover classification
• Benchmarking annotation software for remote sensing dataset generation

Strengths

• Apache-2.0 permissive license allows for commercial and research use
• Maintained by a specialized remote sensing deep learning organization
• Focuses specifically on high-resolution aerial and satellite imagery

Limitations

• Unknown record count and specific label categories in the top-level metadata
• Lack of sample data or column definitions in the source repository description

Provenance

Source

satellite-image-deep-learning GitHub repository

Collection Method

annotated

Freshness

Updated as recently as February 2026.