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:

• Atmospheric correction method statement
• Corathyp specifications and design
• Development of the Python code in the Persian environment
• Generation of synthetic images with SOS-ABS for validation
• Validation on synthetic, real data, and in-situ measures
• IT optimization (decrease in calculation time)
• Algorithmic improvement proposals
• 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 the processing of satellite hyperspectral image

The processes for carrying out the project are:

• Bibliography, specifications, development, validation, Studies, points on regular advances, reports

Technical characteristics

The solution key points are as follows:

• Incommensurate

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