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license: cc-by-nc-4.0
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# CloudSEN12
## A Benchmark Dataset for Cloud Semantic Understanding

![CloudSEN12 Images](https://cloudsen12.github.io/thumbnails/cloudsen12.gif)

CloudSEN12 is a **LARGE dataset** (~1 TB) for cloud semantic understanding that consists of 49,400 image patches (IP) that are
evenly spread throughout all continents except Antarctica. Each IP covers 5090 x 5090 meters and contains data from Sentinel-2 
levels 1C and 2A, hand-crafted annotations of thick and thin clouds and cloud shadows, Sentinel-1 Synthetic Aperture Radar (SAR), 
digital elevation model, surface water occurrence, land cover classes, and cloud mask results from six cutting-edge 
cloud detection algorithms.

CloudSEN12 is designed to support both weakly and self-/semi-supervised learning strategies by including three distinct forms of 
hand-crafted labeling data: high-quality, scribble and no-annotation. For more details on how we created the dataset see our 
paper.

Ready to start using [CloudSEN12](https://cloudsen12.github.io/)?

[Download Dataset](https://cloudsen12.github.io/download.html)

[Paper - Scientific Data](https://www.nature.com/articles/s41597-022-01878-2)

[Inference on a new S2 image](https://colab.research.google.com/github/cloudsen12/examples/blob/master/example02.ipynb)

[Enter to cloudApp](https://github.com/cloudsen12/CloudApp)

[CloudSEN12 in Google Earth Engine](https://gee-community-catalog.org/projects/cloudsen12/)

This work has been partially supported by the Spanish Ministry of Science and Innovation project PID2019-109026RB-I00 (MINECO-ERDF) and 
the Austrian Space Applications Programme within the [SemantiX project](https://austria-in-space.at/en/projects/2019/semantix.php).