Sentinel Hub's cloud detector for Sentinel-2 imagery
The s2cloudless Python package provides automated cloud detection in Sentinel-2 imagery. The classification is based on a single-scene pixel-based cloud detector developed by Sentinel Hub's research team and is described in more details in this blog.
The package requires a Python version >= 3.6. The package is available on the PyPI package manager and can be installed with
$ pip install s2cloudless
To install the package manually, clone the repository and
$ pip install .
s2cloudless dependencies is
lightgbm package. If having problems during installation, please
check the LightGBM installation guide.
s2cloudless on Windows, it is recommended to install package
Unofficial Windows wheels repository
Input: Sentinel-2 scenes
The inputs to the cloud detector are Sentinel-2 images. In particular, the cloud detector requires the following 10
Sentinel-2 band reflectances: B01, B02, B04, B05, B08, B8A, B09, B10, B11, B12, which are obtained from raw
reflectance value in the following way:
Jupyter notebook on how to use the cloud detector to produce cloud mask or cloud probability map can be found in the examples folder.
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.