SAR-1M Dataset

Dataset Description

SAR-1M is a large-scale synthetic aperture radar (SAR) image dataset designed for SAR representation learning.

The dataset contains over one million SAR images, and about 75% of the SAR samples are paired with geographically aligned optical images, enabling multimodal remote sensing studies.

Dataset Structure

SAR-1M/
├── SAR/
│   ├── 0000001.png
│   ├── 0000002.png
│   └── ...
├── OPT/
│   ├── 0000001.png
│   ├── 0000002.png
│   └── ...
├── paired.json
└── unpaired.json

• SAR/: SAR imagery
• OPT/: Corresponding optical images (for paired samples)
• paired.json: Index file describing SAR–optical paired samples
• unpaired.json: Index file for SAR samples without optical counterparts

Applications

The dataset can support various remote sensing tasks, including:

• SAR image representation learning
• Multimodal remote sensing research
• Foundation model pretraining for SAR imagery

License

The SAR-1M dataset is released under the CC BY-NC 4.0 license and is intended for non-commercial research purposes only.

Contact

For questions or collaboration inquiries, please contact the dataset authors.

Citation

If you use the SAR-1M dataset in your research, please cite:

@misc{liu2025sarmaemaskedautoencodersar,
  title={SARMAE: Masked Autoencoder for SAR Representation Learning},
  author={Danxu Liu and Di Wang and Hebaixu Wang and Haoyang Chen and Wentao Jiang and Yilin Cheng and Haonan Guo and Wei Cui and Jing Zhang},
  year={2025},
  eprint={2512.16635},
  archivePrefix={arXiv},
  primaryClass={cs.CV},
  url={https://arxiv.org/abs/2512.16635}
}