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  license: cc-by-nc-4.0
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  license: cc-by-nc-4.0
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  ---
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+
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+ # **CloudSEN12 NOLABEL**
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+ ## **A Benchmark Dataset for Cloud Semantic Understanding**
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+
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+ ![CloudSEN12 Images](https://cloudsen12.github.io/thumbnails/cloudsen12.gif)
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+
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+ CloudSEN12 is a LARGE dataset (~1 TB) for cloud semantic understanding that consists of 49,400 image patches (IP) that are
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+ evenly spread throughout all continents except Antarctica. Each IP covers 5090 x 5090 meters and contains data from Sentinel-2
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+ levels 1C and 2A, hand-crafted annotations of thick and thin clouds and cloud shadows, Sentinel-1 Synthetic Aperture Radar (SAR),
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+ digital elevation model, surface water occurrence, land cover classes, and cloud mask results from six cutting-edge
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+ cloud detection algorithms.
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+
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+ CloudSEN12 is designed to support both weakly and self-/semi-supervised learning strategies by including three distinct forms of
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+ hand-crafted labeling data: high-quality, scribble and no-annotation. For more details on how we created the dataset see our
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+ paper.
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+
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+ Ready to start using **[CloudSEN12](https://cloudsen12.github.io/)**?
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+
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+ **[Download Dataset](https://cloudsen12.github.io/download.html)**
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+
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+ **[Paper - Scientific Data](https://www.nature.com/articles/s41597-022-01878-2)**
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+
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+ **[Inference on a new S2 image](https://colab.research.google.com/github/cloudsen12/examples/blob/master/example02.ipynb)**
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+
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+ **[Enter to cloudApp](https://github.com/cloudsen12/CloudApp)**
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+
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+ **[CloudSEN12 in Google Earth Engine](https://gee-community-catalog.org/projects/cloudsen12/)**
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+
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+
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+ <br>
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+
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+ ### **Description**
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+
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+ <br>
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+
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+ | File | Name | Scale | Wavelength | Description | Datatype |
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+ |---------------|-----------------|--------|------------------------------|------------------------------------------------------------------------------------------------------|----------|
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+ | L1C_ & L2A_ | B1 | 0.0001 | 443.9nm (S2A) / 442.3nm (S2B)| Aerosols. | np.int16 |
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+ | | B2 | 0.0001 | 496.6nm (S2A) / 492.1nm (S2B)| Blue. | np.int16 |
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+ | | B3 | 0.0001 | 560nm (S2A) / 559nm (S2B) | Green. | np.int16 |
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+ | | B4 | 0.0001 | 664.5nm (S2A) / 665nm (S2B) | Red. | np.int16 |
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+ | | B5 | 0.0001 | 703.9nm (S2A) / 703.8nm (S2B)| Red Edge 1. | np.int16 |
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+ | | B6 | 0.0001 | 740.2nm (S2A) / 739.1nm (S2B)| Red Edge 2. | np.int16 |
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+ | | B7 | 0.0001 | 782.5nm (S2A) / 779.7nm (S2B)| Red Edge 3. | np.int16 |
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+ | | B8 | 0.0001 | 835.1nm (S2A) / 833nm (S2B) | NIR. | np.int16 |
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+ | | B8A | 0.0001 | 864.8nm (S2A) / 864nm (S2B) | Red Edge 4. | np.int16 |
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+ | | B9 | 0.0001 | 945nm (S2A) / 943.2nm (S2B) | Water vapor. | np.int16 |
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+ | | B11 | 0.0001 | 1613.7nm (S2A) / 1610.4nm (S2B)| SWIR 1. | np.int16 |
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+ | | B12 | 0.0001 | 2202.4nm (S2A) / 2185.7nm (S2B)| SWIR 2. | np.int16 |
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+ | L1C_ | B10 | 0.0001 | 1373.5nm (S2A) / 1376.9nm (S2B)| Cirrus. | np.int16 |
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+ | L2A_ | AOT | 0.001 | - | Aerosol Optical Thickness. | np.int16 |
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+ | | WVP | 0.001 | - | Water Vapor Pressure. | np.int16 |
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+ | | TCI_R | 1 | - | True Color Image, Red. | np.int16 |
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+ | | TCI_G | 1 | - | True Color Image, Green. | np.int16 |
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+ | | TCI_B | 1 | - | True Color Image, Blue. | np.int16 |
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+ | S1_ | VV | 1 | 5.405GHz | Dual-band cross-polarization, vertical transmit/horizontal receive. |np.float32|
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+ | | VH | 1 | 5.405GHz | Single co-polarization, vertical transmit/vertical receive. |np.float32|
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+ | | angle | 1 | - | Incidence angle generated by interpolating the ‘incidenceAngle’ property. |np.float32|
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+ | EXTRA_ | CDI | 0.0001 | - | Cloud Displacement Index. | np.int16 |
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+ | | Shwdirection | 0.01 | - | Azimuth. Values range from 0°- 360°. | np.int16 |
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+ | | elevation | 1 | - | Elevation in meters. Obtained from MERIT Hydro datasets. | np.int16 |
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+ | | ocurrence | 1 | - | JRC Global Surface Water. The frequency with which water was present. | np.int16 |
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+ | | LC100 | 1 | - | Copernicus land cover product. CGLS-LC100 Collection 3. | np.int16 |
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+ | | LC10 | 1 | - | ESA WorldCover 10m v100 product. | np.int16 |
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+ | LABEL_ | fmask | 1 | - | Fmask4.0 cloud masking. | np.int16 |
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+ | | QA60 | 1 | - | SEN2 Level-1C cloud mask. | np.int8 |
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+ | | s2cloudless | 1 | - | sen2cloudless results. | np.int8 |
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+ | | sen2cor | 1 | - | Scene Classification band. Obtained from SEN2 level 2A. | np.int8 |
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+ | | cd_fcnn_rgbi | 1 | - | López-Puigdollers et al. results based on RGBI bands. | np.int8 |
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+ | |cd_fcnn_rgbi_swir| 1 | - | López-Puigdollers et al. results based on RGBISWIR bands. | np.int8 |
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+ | | kappamask_L1C | 1 | - | KappaMask results using SEN2 level L1C as input. | np.int8 |
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+ | | kappamask_L2A | 1 | - | KappaMask results using SEN2 level L2A as input. | np.int8 |
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+ | | manual_hq | 1 | | High-quality pixel-wise manual annotation. | np.int8 |
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+ | | manual_sc | 1 | | Scribble manual annotation. | np.int8 |
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+
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+ <br>
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+
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+
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+ ### **Label Description**
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+
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+
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+ | **CloudSEN12** | **KappaMask** | **Sen2Cor** | **Fmask** | **s2cloudless** | **CD-FCNN** | **QA60** |
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+ |------------------|------------------|-------------------------|-----------------|-----------------------|---------------------|--------------------|
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+ | 0 Clear | 1 Clear | 4 Vegetation | 0 Clear land | 0 Clear | 0 Clear | 0 Clear |
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+ | | | 2 Dark area pixels | 1 Clear water | | | |
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+ | | | 5 Bare Soils | 3 Snow | | | |
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+ | | | 6 Water | | | | |
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+ | | | 11 Snow | | | | |
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+ | 1 Thick cloud | 4 Cloud | 8 Cloud medium probability | 4 Cloud | 1 Cloud | 1 Cloud | 1024 Opaque cloud |
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+ | | | 9 Cloud high probability | | | | |
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+ | 2 Thin cloud | 3 Semi-transparent cloud | 10 Thin cirrus | | | | 2048 Cirrus cloud |
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+ | 3 Cloud shadow | 2 Cloud shadow | 3 Cloud shadows | 2 Cloud shadow | | | |
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+
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+
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+
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+ <br>
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+
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+
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+ ### **np.memmap shape information**
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+
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+ <br>
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+
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+ **cloudfree (0\%) shape: (5880, 512, 512)**
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+ <br>
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+ **almostclear (0-25 \%) shape: (5880, 512, 512)**
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+ <br>
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+ **lowcloudy (25-45 \%) shape: (5880, 512, 512)**
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+ <br>
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+ **midcloudy (45-65 \%) shape: (5880, 512, 512)**
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+ <br>
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+ **cloudy (65 > \%) shape: (5880, 512, 512)**
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+
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+ <br>
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+
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+ ### **Example**
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+
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+ <br>
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+
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+ ```py
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+ import numpy as np
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+
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+ # Read high-quality train
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+ cloudfree_shape = (5880, 512, 512)
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+ B4X = np.memmap('cloudfree/L1C_B04.dat', dtype='int16', mode='r', shape=cloudfree_shape)
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+ y = np.memmap('cloudfree/manual_hq.dat', dtype='int8', mode='r', shape=cloudfree_shape)
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+
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+ # Read high-quality val
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+ almostclear_shape = (5880, 512, 512)
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+ B4X = np.memmap('almostclear/L1C_B04.dat', dtype='int16', mode='r', shape=almostclear_shape)
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+ y = np.memmap('almostclear/kappamask_L1C.dat', dtype='int8', mode='r', shape=almostclear_shape)
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+
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+
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+ # Read high-quality test
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+ midcloudy_shape = (5880, 512, 512)
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+ B4X = np.memmap('midcloudy/L1C_B04.dat', dtype='int16', mode='r', shape=midcloudy_shape)
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+ y = np.memmap('midcloudy/kappamask_L1C.dat', dtype='int8', mode='r', shape=midcloudy_shape)
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+ ```
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+ <br>
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+
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+
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+ This work has been partially supported by the Spanish Ministry of Science and Innovation project
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+ PID2019-109026RB-I00 (MINECO-ERDF) and the Austrian Space Applications Programme within the
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+ **[SemantiX project](https://austria-in-space.at/en/projects/2019/semantix.php)**.