Processor: S2 L2A FORCE
The on-demand processor Sentinel-2: FORCE Atmospheric Correction/Cloud Mask generation is an established processor for the correction of atmospheric influences on Sentinel-2 data. FORCE is a Framework for Operational Radiometric Correction for Environmental monitoring offering a series of modules to generate analysis ready data out of radiometrically calibrated Sentinel-2 and Landsat data. In the Data Explorer the atmospheric correction module of FORCE is offered for the on-demand processing of Sentinel-2 data.
Sentinel-2:FORCE Atmospheric Correction/Cloud Mask generation is an alternative to the S2 L2A MAJA processor and can be applied to all Sentinel-2 L1C data.
Processor details
- Version: FORCE 3.0
- Input data: Sentinel-2 L1C
- Methodology: Detailed information can be found in the links below.
Access and use
Depending on the environment and intended use, there are the following possibilities to execute the processing:
- EO Browser: -
- Data Explorer:
- Data Catalog: CODE-DE or CREODIAS
- Search and select required Sentinel-2 L1C input data -> Add to Workspace.
- Go to Workspace - > Select required datasets and Add to processing center -> Go to Processing center.
- Select processor: Sentinel-2: FORCE Atmospheric Correction/Cloud Mask generation.
- Select required datasets and Create processing order.
- Progress of orders can be monitored in Processing status.
- The processed data is added to the CODE-DE data catalog in the Sentinel-2 L2A-FORCE collection.
Usage requirements
There are certain requirements that must be met for use. Some data or services require an individual application. For more information, please contact CODE-DE Support.
| Required? | Remark | |
| Registration on CODE-DE | Yes | --- |
| Cloud resources on CODE-DE | No | --- |
| Individual request | No | --- |
More information
Further information on this product can also be found on the following external pages:
References
- Frantz, D.; Röder, A.; Stellmes, M.; Hill, J. An Operational Radiometric Landsat Preprocessing Framework for Large-Area Time Series Applications. IEEE Trans. Geosci. Remote Sens. 2016, 54, 3928–3943. (https://ieeexplore.ieee.org/document/7426833)
- Frantz, D. FORCE—Landsat + Sentinel-2 Analysis Ready Data and Beyond. Remote Sens. 2019, 11, 1124. (http://doi.org/10.3390/rs11091124)
- Frantz,D.; Haß, E.; Uhl, A.; Stoffels, J.; Hill, J. Improvement of the Fmask algorithm for Sentinel-2 images: Separating clouds from bright surfaces based on parallax effects. Volume 215, 15 September 2018, Pages 471-481. (http://doi.org/10.1016/j.rse.2018.04.046)
Terms of use
Use of the product is subject to the following terms of use:
