metadata
license: cc-by-nc-4.0
task_categories:
- image-feature-extraction
size_categories:
- 1M<n<10M
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}
}