.. image:: https://enmap.git-pages.gfz-potsdam.de/sicor/doc/_static/sicor_logo_lr.png
:width: 300px
:alt: SICOR Logo
=================================================
SICOR - Sensor Independent Atmospheric Correction
=================================================
Sensor Independent Atmospheric Correction of optical Earth Observation (EO) data from both multispectral and
hyperspectral instruments. Currently, SICOR can be applied to Sentinel-2 and EnMAP data but the implementation of
additional space- and airborne sensors is under development. As unique features for the processing of hyperspectral
data, SICOR incorporates a coupled retrieval of the three phases of water and a snow and ice surface property
inversion based on a simultaneous optimization of atmosphere and surface state (Bohn et al., 2020; Bohn et al., 2021).
Both algorithms are based on Optimal Estimation (OE) including the calculation of several measures of retrieval
uncertainties. The atmospheric modeling in case of hyperspectral data is based on the MODTRAN® radiative transfer code
whereas the atmospheric correction of multispectral data relies on the MOMO code. The MODTRAN® trademark is being used
with the express permission of the owner, Spectral Sciences, Inc.
* Please check the documentation_ for installation and usage instructions and in depth information.
* Information on how to **cite the SICOR Python package** can be found in the
`CITATION <https://git.gfz-potsdam.de/EnMAP/sicor/-/blob/main/CITATION>`__ file.
Alternatively, you can cite the following publications when using specific features of SICOR:
Bohn, N., Guanter, L., Kuester, T., Preusker, R., Segl, K. (2020). Coupled retrieval of the three phases of water from
spaceborne imaging spectroscopy measurements. Remote Sens. Environ., 242, 111708,
https://doi.org/10.1016/j.rse.2020.111708.
Bohn, N., Painter, T. H., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. J., Helmlinger, M. C., Green, R. O.,
Cook, J. M., Guanter, L. (2021). Optimal estimation of snow and ice surface parameters from imaging spectroscopy
measurements. Remote Sens. Environ., 264, 112613, https://doi.org/10.1016/j.rse.2021.112613.
License
-------
Free software: GNU General Public License v3 or later (GPLv3+)
All images contained in any (sub-)directory of this repository are licensed under the CC0 license which can be found
`here <https://creativecommons.org/publicdomain/zero/1.0/legalcode.txt>`__.
Feature overview
----------------
* Sentinel-2 L1C to L2A processing
* EnMAP L1B to L2A processing
* generic atmospheric correction for hyperspectral airborne and spaceborne data
* retrieval of the three phases of water from hyperspectral data
* 'lazy Gaussian inversion' of snow and ice surface properties
* calculation of various retrieval uncertainties
(including a posteriori errors, averaging kernels, gain matrices, degrees of freedom, information content)
* atmospheric correction for Landsat-8: work in progress
* CH4 retrieval from hyperspectral data: work in progress
Status
------
|badge1| |badge2| |badge3| |badge4| |badge5| |badge6| |badge7| |badge8| |badge9|
.. |badge1| image:: https://git.gfz-potsdam.de/EnMAP/sicor/badges/main/pipeline.svg
:target: https://git.gfz-potsdam.de/EnMAP/sicor/pipelines
.. |badge2| image:: https://git.gfz-potsdam.de/EnMAP/sicor/badges/main/coverage.svg
:target: https://git.gfz-potsdam.de/EnMAP/sicor/coverage/
.. |badge3| image:: https://img.shields.io/static/v1?label=Documentation&message=GitLab%20Pages&color=orange
:target: https://enmap.git-pages.gfz-potsdam.de/sicor/doc/
.. |badge4| image:: https://img.shields.io/pypi/v/sicor.svg
:target: https://pypi.python.org/pypi/sicor
.. |badge5| image:: https://img.shields.io/conda/vn/conda-forge/sicor.svg
:target: https://anaconda.org/conda-forge/sicor
.. |badge6| image:: https://img.shields.io/pypi/l/sicor.svg
:target: https://git.gfz-potsdam.de/EnMAP/sicor/-/blob/main/LICENSE
.. |badge7| image:: https://img.shields.io/pypi/pyversions/sicor.svg
:target: https://img.shields.io/pypi/pyversions/sicor.svg
.. |badge8| image:: https://img.shields.io/pypi/dm/sicor.svg
:target: https://pypi.python.org/pypi/sicor
.. |badge9| image:: https://zenodo.org/badge/DOI/10.5281/zenodo.5535505.svg
:target: https://doi.org/10.5281/zenodo.5535505
See also the latest coverage_ report and the pytest_ HTML report.
History / Changelog
-------------------
You can find the protocol of recent changes in the SICOR package
`here <https://git.gfz-potsdam.de/EnMAP/sicor/-/blob/main/HISTORY.rst>`__.
Credits
-------
This software was developed within the context of the EnMAP project supported by the DLR Space Administration with
funds of the German Federal Ministry of Economic Affairs and Energy (on the basis of a decision by the German
Bundestag: 50 EE 1529) and contributions from DLR, GFZ and OHB System AG.
The MODTRAN® trademark is being used with the express permission of the owner, Spectral Sciences, Inc.
This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
.. _documentation: https://enmap.git-pages.gfz-potsdam.de/sicor/doc/
.. _coverage: https://enmap.git-pages.gfz-potsdam.de/sicor/coverage/
.. _pytest: https://enmap.git-pages.gfz-potsdam.de/sicor/test_reports/report.html
Raw data
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The atmospheric modeling in case of hyperspectral data is based on the MODTRAN\u00ae radiative transfer code\nwhereas the atmospheric correction of multispectral data relies on the MOMO code. The MODTRAN\u00ae trademark is being used\nwith the express permission of the owner, Spectral Sciences, Inc.\n\n* Please check the documentation_ for installation and usage instructions and in depth information.\n* Information on how to **cite the SICOR Python package** can be found in the\n `CITATION <https://git.gfz-potsdam.de/EnMAP/sicor/-/blob/main/CITATION>`__ file.\n\nAlternatively, you can cite the following publications when using specific features of SICOR:\n\nBohn, N., Guanter, L., Kuester, T., Preusker, R., Segl, K. (2020). Coupled retrieval of the three phases of water from\nspaceborne imaging spectroscopy measurements. Remote Sens. Environ., 242, 111708,\nhttps://doi.org/10.1016/j.rse.2020.111708.\n\nBohn, N., Painter, T. H., Thompson, D. R., Carmon, N., Susiluoto, J., Turmon, M. 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