| --- |
| 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} |
| } |
| ``` |
