Customer: Centre National d’Etudes Spatiales (CNES)

Programme: R&T

Supply Chain: CNES > CS Group SPACE

Context

CS Group responsabilities for Atmospheric correction of hyperspectral data are as follows:

• Specifications, development, validation

The features are as follows:

• State of the art of atmospheric correction methods
• CORATHYP specifications and design
• Code development in Python in the PERSEUS environment
• Generation of synthetic images with SOS-ABS for validation
• Validation on synthetic, real data and in-situ measurements
• Computer optimization (reduction of calculation time)
• Proposals for algorithmic improvements
• Creation of a spectral band selection tool to characterize the atmosphere

Project implementation

The project objectives are as follows:

• Develop an autonomous and modular atmospheric correction code for processing satellite hyperspectral images

The processes for carrying out the project are:

• Bibliography, Specifications, Development, Validation, Studies, Regular progress updates, Reports

Technical characteristics

The solution key points are as follows:

• Not applicable

The main technologies used in this project are:

Domain	Technology(ies)
Programming language(s)	Python, Dask, Pandas
Main COTS library(ies)	PERSEUS, SOS-ABS, GDALdem, Shareloc