Satellite and Aerial Imagery for Deep Learning and Earth Observation

Curated by the satellite-image-deep-learning organization, this resource aggregates satellite and aerial imagery for deep learning applications in Earth observation. The collection, updated in March 2026, includes remote sensing data and Sentinel imagery for various computer vision tasks.

Use Cases

• Training object detection models using Sentinel satellite imagery
• Semantic segmentation of Earth observation data for land cover mapping
• Change detection analysis using multi-temporal remote sensing data

Strengths

• Updated as of March 2026
• Includes Sentinel-specific imagery
• Curated by satellite-image-deep-learning

Limitations

• Missing specific record counts and file size metadata
• Individual dataset licenses are not aggregated

Provenance

Source

satellite-image-deep-learning GitHub repository

Collection Method

curated collection

Freshness

Updated March 2026

Geography

global