Skip to main content

Sensor Independent Atmospheric Correction

Project description



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 a unique feature for the processing of hyperspectral data, SICOR incorporates a three phases of water retrieval based on Optimal Estimation (OE) including the calculation 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 usage, examples and in depth information.



Usage from python:

from sicor import AC
from sicor.sicor_enmap import sicor_ac_enmap
enmap_l2a_vnir, enmap_l2a_swir, res = sicor_ac_enmap(data_l1b, options, logger)

From command line (currently, only applicable to multispectral case): --help --help


  • 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
  • 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


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.

Project details

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for sicor, version 0.16.4
Filename, size File type Python version Upload date Hashes
Filename, size sicor-0.16.4.tar.gz (68.7 MB) File type Source Python version None Upload date Hashes View

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring DigiCert DigiCert EV certificate Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page