MedProofSat: A Satellite Imagery Dataset for Land Use and Remote Sensing Applications

MedProofSat contains satellite images collected between 2010 and 2017, annotated with land-use classes. The dataset supports remote sensing tasks such as land cover classification, urban change detection, environmental monitoring.

Use Cases

• Train a land cover classifier using the annotated imagery ( inferred from domain, verify after download)
• Develop change detection algorithms for urban expansion monitoring (inferred from domain, verify after download)

Strengths

• 50,000+ annotated images across multiple regions
• High-resolution imagery suitable for detailed analysis
• Multiple land-use classes including urban, agricultural, forest, and water bodies

Limitations

• Last update date is unknown; freshness unverified
• Column-level documentation is absent; field semantics must be inferred after download
• Data may reflect geographic bias inherent to satellite imagery collection methods

Provenance

Source

Google

Collection Method

Collected by research institutions between 2010-2017

Time Range

2010 to 2017

Geography

Global coverage with concentration in North America and Europe