End-to-end simulations to optimize imaging spectroscopy mission requirements for seven scientific applications
Résumé
CNES is currently carrying out a Phase A study to assess the feasibility of a future hyperspectral imaging sensor
(10 m spatial resolution) combined with a panchromatic camera (2.5 m spatial resolution). This mission focuses
on both high spatial and spectral resolution requirements, as inherited from previous French studies such as
HYPEX, HYPXIM, and BIODIVERSITY. To meet user requirements, cost, and instrument compactness constraints,
CNES asked the French hyperspectral Mission Advisory Group (MAG), representing a broad French scientific
community, to provide recommendations on spectral sampling, particularly in the Short Wave InfraRed (SWIR)
for various applications.
This paper presents the tests carried out with the aim of defining the optimal spectral sampling and spectral
resolution in the SWIR domain for quantitative estimation of physical variables and classification purposes. The
targeted applications are geosciences (mineralogy, soil moisture content), forestry (tree species classification,
leaf functional traits), coastal and inland waters (bathymetry, water column, bottom classification in shallow
water, coastal habitat classification), urban areas (land cover), industrial plumes (aerosols, methane and carbon
dioxide), cryosphere (specific surface area, equivalent black carbon concentration), and atmosphere (water
vapor, carbon dioxide and aerosols). All the products simulated in this exercise used the same CNES end-to-end
processing chain, with realistic instrument parameters, enabling easy comparison between applications. 648 simulations were carried out with different spectral strategies, radiometric calibration performances and signal-
to-noise Ratios (SNR): 24 instrument configurations × 25 datasets (22 images + 3 spectral libraries).
The results show that spectral sampling up to 20 nm in the SWIR range is sufficient for most applications.
However, 10 nm spectral sampling is recommended for applications based on specific absorption bands such as
mineralogy, industrial plumes or atmospheric gases. In addition, a slight performance loss is generally observed
when radiometric calibration accuracy decreases, with a few exceptions in bathymetry and in the cryosphere for
which the observed performance is severely degraded. Finally, most applications can be achieved with a realistic
SNR, with the exception of bathymetry, shallow water classification, as well as carbon dioxide and methane
estimation, which require the optimistic SNR level tested. On the basis of these results, CNES is currently eval-
uating the best compromise for designing the future hyperspectral sensor to meet the objectives of priority
applications.
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