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 focuseson both high spatial and spectral resolution requirements, as inherited from previous French studies such asHYPEX, 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 scientificcommunity, 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 spectralresolution in the SWIR domain for quantitative estimation of physical variables and classification purposes. Thetargeted applications are geosciences (mineralogy, soil moisture content), forestry (tree species classification,leaf functional traits), coastal and inland waters (bathymetry, water column, bottom classification in shallowwater, coastal habitat classification), urban areas (land cover), industrial plumes (aerosols, methane and carbondioxide), cryosphere (specific surface area, equivalent black carbon concentration), and atmosphere (watervapor, carbon dioxide and aerosols). All the products simulated in this exercise used the same CNES end-to-endprocessing 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 asmineralogy, industrial plumes or atmospheric gases. In addition, a slight performance loss is generally observedwhen radiometric calibration accuracy decreases, with a few exceptions in bathymetry and in the cryosphere forwhich the observed performance is severely degraded. Finally, most applications can be achieved with a realisticSNR, with the exception of bathymetry, shallow water classification, as well as carbon dioxide and methaneestimation, 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 priorityapplications.
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