Water quality exploiting PRISMA hyperspectral data: algorithm and first validation results

A prototype processor for water quality exploiting PRISMA satellite hyperspectral images has been developed in the framework of the ASI project "Sviluppo di Prodotti Iperspettrali Prototipali Evoluti" (Contract ASI N. 2021-7-I.0). The main objective of the project is the prototyping of a subset of Level 3 / Level 4 value-added products to be retrieved by means of hyperspectral data processing. The Water Quality Prototype is a combination of the state-of-the-art techniques for the retrieval of the following parameters, useful for the characterization of both inland and coastal waters: Phytoplankton, Total Suspended Matter (TSM) and Bottom Substrate. The prototype processor ingests at-surface reflectance product and implements both adaptive semi empirical, semi-analytical and analytical methods for parameters retrieval. An adaptive band ratio algorithm was developed for the retrieval of the concentration of phytoplankton primary photosynthetic pigment (Chlorophyll-a (Chl-a)) and the accessory pigments (e.g. phycocyanin). The processor exploits the diagnostic reflectance spectral feature of Chl-a and phycocyanin. Chl-a is correlated with both the height and position of the red-edge scattering signal near 700 nm, which shifts towards increasing wavelengths as biomass increases. Thanks to the spectral resolution of the PRISMA sensor, the relative maximum and minimum diagnostic features can be performed pixel-based and adaptively identified in the image scene. Moreover the prototype processor implements a dedicated algorithms to retrieve TSM concentration and water Turbidity exploiting different wavelengths in the visible or near-infrared range. A bio-Optical model inversion allows the retrieval of chlorophyll, coloured dissolved organic matter and non-algal particulate matter concentration for optical deep water, or bottom substrate coverage abundances (e.g. macrophytes, sand, rocks) for optically shallow waters. Model parameters consider the Inherent Optical Properties specific for the case studies and different bottom spectral properties. The developed approach assumes a relative linear mixed distribution of up to three different substrates and a relaxed constraint hypothesis for modelling the contribution of the substrates in bottom reflectance. The proposed techniques have been tested on PRISMA data, acquired over different Italian lakes (Lake Garda, Mantua, Varese and Trasimeno) and coastal areas (northern Adriatic Sea). The preliminary results of the prototype products validation show a good agreement respect to the in-situ data.