s3lst-ds provides pipelines for conveniently querying, downloading, filtering and downscaling Sentinel-3 LST data using either single or multi-timestamp scale-invariance-based models.
To be able to install and use the s3lst-ds package in your project, you would need:
-
Install the latest stable release from PyPI in the activated virtual environment using
uv:uv add s3lst-ds
-
Safely set your CDSE credentials as environment variables of the system:
uv run s3lst-ds-set-cdse
3. Install esa-snappy (optional)
-
Install
esa-snappyPython package usinguv:uv add s3lst-ds[snap]
-
Install the backend
SNAPJava package (if not already installed) and subsequently configure it usinguv:uv run s3lst-ds-install-snap
Note
CDSE credentials are required to download Sentinel-3 data. Script s3lst-ds-set-cdse
will prompt you to provide their CDSE mail and password. The script will subsequently
write them to file ~/.config/cdse_credentials.sh with user-only read and write
permissions and source it in ~/.bashrc file. You may check the created credentials
file using the command:
nano ~/.config/cdse_credentials.shNote that if you would like to remove the credentials from the file at a later time, you may run:
uv run s3lst-ds-unset-cdseThe default installation considers
rioxarray for georeferencing the
downloaded Sentinel-3 products. However,
esa-snappy has been found to produce
better results, and, because of that, it is herein availed as an optional tool. With
its installation, both tools can be used for georeferencing.
If the you would to like to uninstall SNAP at a later time, you may run:
uv run s3lst-ds-uninstall-snapIt is important to note that SNAP is configured with a limited amount of memory. To
increase SNAP's maximum heap memory to for instance 64 GB, you would need to open
file esa_snappy.ini nested in the installation directory of the virtual environment
(herein assumed to be VENV) by doing
nano VENV/lib/python3.12/site-packages/esa_snappy/esa_snappy.iniand writing in it:
[DEFAULT]
java_max_mem: 64GThe full documentation is available at GitHub Pages.
If you are a project developer, please read CONTRIBUTING.md to assimilate the development workflow, build Docker images from the project source code and locally run them.
If you are a project maintainer, please read RELEASING.md to know how to build and publish the package to PyPI, create GitHub releases and publish the documentation to GitHub Pages after successful merge pull requests.
If you use s3lst-ds in research or software, please cite the
companion paper. The respective citation
information is provided in
CITATION.cff and
may be download in APA or BibTeX formats through button Cite this repository in the
About section of the GitHub repo page.
s3lst-ds is licensed under the terms of the
MIT license.
