European Space Agency OSIP: Multi-Model synthetic S2-HS (Hyperspectral) data for marine/plastic debris characterization (MUSS-2)

For plastic identification and tracking, we need rich spectral info in hyperspectral (HS) data. Research based on full stretch (0.4 to 2.5 μm) HS for microplastic suggests SWIR ranges are most useful in detecting debris >300 μm (Karlsson et al, 2016). In Garaba and Dierssen (2018), an airborne HS study of synthetic hydrocarbon detection using SWIR absorption features successfully identified debris from marine harvested macro- (>5mm) and microplastics (<5mm). Image analysis on 7.1 m pixel also identified band depth using 1702, 1732 and 1742 nm calibrated at-sensor radiance are most useful. In Driedger et al (2015), the authors suggested it is possible to detect common plastic debris in beach sand using NIR reflectance spectrometry at the range 890–2500 nm. In terms of spatial resolution for identification and tracking, Moy et al (2016) used HD aerial photo (30cm) to track debris. In summary, we want HS data at SWIR (1000-2500 nm) around 0.5 m GSD. Both of these characteristics are non-existent in current EO missions, and will still be difficult to find in future EO missions. In this work, we propose (1) to use novel spectral enhancement method to generate simulated HS SWIR from Sentinel 2 MSI using dictionary learning and spectral response function modeling, (2) Image superresolution with multi-view S2 for spatial enhancement and (3) CNN based HSMS fusion with 2 branch feature extraction model for HD HS modelling. Simulated marine plastic spectra will be used to validate effectiveness of full exploitation of S2 mission using detailed feature in spatial and spectral domain for marine plastic debris identification.