Satip provides the functionality necessary for

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Project description

Satip

All Contributors

PyPI version

codecov

Satip is a library for satellite image processing, and provides all of the functionality necessary for retrieving, and storing EUMETSAT data


Installation

To install the satip library please run:

pip install satip

Or if you're working in the development environment you can run the following from the directory root:

pip install -e .

Conda

Or, if you want to use conda from the a cloned Satip repository:

conda env create -f environment.yml
conda activate satip
pip install -e .

If you plan to work on the development of Satip then also consider installing these development tools:

conda install pytest flake8 jedi mypy black pre-commit
pre-commit install

Operation

Getting your own API key

In order to contribute to development or just test-run some scripts, you will need your own Eumetsat-API-key. Please follow these steps:

  1. Go to https://eoportal.eumetsat.int and register an account.
  2. You can log in and got to https://data.eumetsat.int/ to check available data services. From there go to your profile and choose the option "API key" or go to https://api.eumetsat.int/api-key/ directly.
  3. Please make sure that you added the key and secret to your user's environment variables.

Downloading EUMETSAT Data

The following command will download the last 2 hours of RSS imagery into NetCDF files at the specified location

python satip/app.py --api-key=<EUMETSAT API Key> --api-secret=<EUMETSAT API Secret> --save-dr="/path/to/saving/files/" --history="2 hours"

To download more historical data, the command below will download the native files, compress with bz2, and save into a subdirectory.

python satip/get_raw_eumetsat_data.py --user-key=<EUMETSAT API Key> --user-secret=<EUMETSAT API Secret>

Converting Native files to Zarr

scripts/convert_native_to_zarr.py converts EUMETSAT .nat files to Zarr datasets, using very mild lossy JPEG-XL compression. (JPEG-XL is the "new kid on the block" of image compression algorithms). JPEG-XL makes the files about a quarter the size of the equivalent bz2 compressed files, whilst the images are visually indistinguishable. JPEG-XL cannot represent NaNs so NaNs. JPEG-XL understands float32 values in the range [0, 1]. NaNs are encoded as the value 0.025. All "real" values are in the range [0.075, 1]. We leave a gap between "NaNs" and "real values" because there is very slight "ringing" around areas of constant value (see this comment for more details). Use satip.jpeg_xl_float_with_nans.JpegXlFloatWithNaNs to decode the satellite data. This class will reconstruct the NaNs and rescale the data to the range [0, 1].

Testing

To run tests, simply run pytest . from the root of the repository. To generate the test plots, run python scripts/generate_test_plots.py.

Contributors ✨

Thanks goes to these wonderful people (emoji key):


Jacob Bieker
💻
Jack Kelly
💻
Ayrton Bourn
💻
Laurence Watson
💻
Notger Heinz
📖
Peter Dudfield
📖

This project follows the all-contributors specification. Contributions of any kind welcome!

Project details

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