PanScale / README.md
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---
pretty_name: PanScale
license: cc-by-4.0
task_categories:
- image-to-image
tags:
- remote-sensing
- pansharpening
- multispectral
- panchromatic
size_categories:
- 1K<n<10K
---
# PanScale
[![arXiv](https://img.shields.io/badge/arXiv-2603.00543-B31B1B?logo=arxiv&logoColor=white)](https://arxiv.org/abs/2603.00543)
[![GitHub](https://img.shields.io/badge/GitHub-ScaleFormer-181717?logo=github&logoColor=white)](https://github.com/caoke-963/ScaleFormer)
[![Hugging Face Dataset](https://img.shields.io/badge/HuggingFace-Dataset-FFD21E?logo=huggingface&logoColor=000)](https://huggingface.co/datasets/kecao/PanScale)
## Dataset Summary
PanScale is a remote-sensing pansharpening dataset with paired multispectral (ms) and panchromatic (pan) TIFF images for cross-scale evaluation.
- Total pairs: **7,559**
- Disk size: **~6.9 GB**
- Format: **8-bit TIFF**
## Supported Tasks
- Image Fusion (Cross-scale Pansharpening)
## Subsets at a Glance
| Subset | Splits | # Pairs | MS size | PAN size | PAN/MS scale |
|---|---|---:|---|---|---:|
| `jilin` | `train200`, `test200/400/800` | 1,157 | 200-800 | 200-800 | 1.0 |
| `landsat` | `train256`, `test200/400/800/1600` | 2,868 | 200-1600 | 200-1600 | 1.0 |
| `skysat` | `train200`, `test200/400/800/1600` | 2,722 | 200-1600 | 200-1600 | 1.0 |
| `fjilin` | `test800/1200/1600/2000` | 484 | 200-500 | 800-2000 | 4.0 |
| `flandsat` | `test800/1200/1600/2000` | 192 | 400-1000 | 800-2000 | 2.0 |
| `fskysat` | `test800/1200/1600/2000` | 136 | 320-800 | 800-2000 | 2.5 |
## Data Fields
- `ms`: 4-channel multispectral image (`.tif`)
- `pan`: 1-channel panchromatic image (`.tif`)
- `id`: filename stem (integer)
## Intended Use
- Pansharpening training and evaluation
- Cross-scale robustness analysis
## License
This dataset is released under **CC BY 4.0**.
## Citation
Citation information will be added after the paper is publicly available.
```bibtex
@article{cao2026cross,
title={Cross-Scale Pansharpening via ScaleFormer and the PanScale Benchmark},
author={Cao, Ke and He, Xuanhua and Li, Xueheng and Zhu, Lingting and Wang, Yingying and Ma, Ao and Zhang, Zhanjie and Zhou, Man and Xie, Chengjun and Zhang, Jie},
journal={arXiv preprint arXiv:2603.00543},
year={2026}
}
```