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---
task_categories:
- image-classification
---
# So2Sat
**So2Sat** is a local climate zone (LCZ) classification task consisting of images from Sentinel-1 and Sentinel-2. We only keep Sentinel-2 images which have 10 MSI bands in this dataset. In addition, we reserve 10% of the training set as the validation set, resulting in 31,713 training samples, 3,523 validation samples and 48,307 test samples.
## How to Use This Dataset
```python
from datasets import load_dataset
dataset = load_dataset("GFM-Bench/So2Sat")
```
Also, please see our [GFM-Bench](https://github.com/uiuctml/GFM-Bench) repository for more information about how to use the dataset! 🤗
## Dataset Metadata
The following metadata provides details about the Sentinel-2 imagery used in the dataset:
<!--- **Number of Sentinel-1 Bands**: 2-->
<!--- **Sentinel-1 Bands**: VV, VH-->
- **Number of Sentinel-2 Bands**: 10
- **Sentinel-2 Bands**: B02 (**Blue**), B03 (**Green**), B04 (**Red**), B05 (**Vegetation red edge**), B06 (**Vegetation red edge**), B07 (**Vegetation red edge**), B08 (**NIR**), B8A (**Narrow NIR**), B11 (**SWIR**), B12 (**SWIR**)
- **Image Resolution**: 32 x 32 pixels
- **Spatial Resolution**: 10 meters
- **Number of Classes**: 17
## Dataset Splits
The **So2Sat** dataset consists following splits:
- **train**: 31,713 samples
- **val**: 3,523 samples
- **test**: 48,307 samples
## Dataset Features:
The **So2Sat** dataset consists of following features:
<!--- **radar**: the Sentinel-1 image.-->
- **optical**: the Sentinel-2 image.
- **label**: the classification label.
<!--- **radar_channel_wv**: the central wavelength of each Sentinel-1 bands.-->
- **optical_channel_wv**: the central wavelength of each Sentinel-2 bands.
- **spatial_resolution**: the spatial resolution of images.
## Citation
If you use the So2Sat dataset in your work, please cite the original paper:
```
@article{zhu2019so2sat,
title={So2Sat LCZ42: A benchmark dataset for global local climate zones classification},
author={Zhu, Xiao Xiang and Hu, Jingliang and Qiu, Chunping and Shi, Yilei and Kang, Jian and Mou, Lichao and Bagheri, Hossein and H{\"a}berle, Matthias and Hua, Yuansheng and Huang, Rong and others},
journal={arXiv preprint arXiv:1912.12171},
year={2019}
}
``` |