A Python library for producing cloud masks of SLSTR scenes using a neural network.
Also includes functions to produce a collocated training data set using either the CALIOP or CATS missions to provide cloud feature labels. In addition, functionality is provided to evaluate the model's performance in different situations using various metrics.
| False Colour Image | Neural Network Mask | Bayesian Mask |
|---|---|---|
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This library produces cloud masks which are an improvement over the current standard bayesian ESA masks.
After cloning this repository and navigating to its install directory, the dependencies can be installed with anaconda:
conda env create -f environment.yml
This will create a new anaconda environment 'cloud-id'. After activating the environment:
conda activate cloud-id
A toggleable matplotlib figure can be produced for an SLSTR S3A_SL_1_RBT folder at PATH with:
python MaskToggle.py PATH
Valid SLSTR files are available from https://scihub.copernicus.eu/s3/#/home
This program is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.
This program is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details.
You should have received a copy of the GNU General Public License along with this program. If not, see https://www.gnu.org/licenses/.