Development of an Advanced L2 Processor for PRISMA Second-Generation within the COOL Project: Application to Snow-Covered Terrain

The COOL project, funded by the Italian Space Agency (ASI), focuses on the development of an advanced, modular Level-2 (L2) processor for the PRISMA Second-Generation (PRISMA-SG) hyperspectral mission. The processor is designed to generate high-quality L2 products, including surface reflectance, water vapor content, and aerosol optical thickness, while addressing the unique challenges introduced by the off-nadir acquisition geometry of the PRISMA-SG sensor.

The processor builds upon state-of-the-art radiative transfer modeling and integrates physics-based atmospheric and topographic correction algorithms based on the MODTRAN6 model. The processing chain is derived and extended from previous work (Santini & Palombo, 2019; Palombo & Santini, 2020; Santini & Palombo, 2022), and incorporates second-order effects, such as adjacency corrections and topographic illumination variations. These algorithms are carefully adapted to the spectral, spatial, and viewing geometry characteristics of PRISMA-SG, aiming to achieve or exceed a Scientific Readiness Level (SRL) of 6.

Validation of the processor relies on both simulated datasets and in-situ measurements over dedicated calibration and validation (CAL/VAL) sites established within the COOL project. Top-of-atmosphere (TOA) radiance signals are simulated over these sites and compared with field measurements to quantify residual errors and assess the sensitivity of the inversion algorithms to off-nadir acquisition effects. These activities ensure the robustness and scientific usability of the derived L2 products in both nadir and off-nadir observation modes.

As a demonstration, the L2 processor was applied to PRISMA-SG images acquired over snow-covered areas in the Italian Alps. The results were compared with the standard L2 products provided by the image supplier. The comparison shows close general agreement in reflectance spectra while correcting artifacts present in the standard products, including topographic effects, adjacency effects, and off-nadir-induced reflectance overestimation. Notably, the corrected reflectance values remain physically consistent and do not exceed unity, a problem often observed in the standard products.

This work consolidates the L2 processing capabilities for PRISMA-SG, providing validated, reliable, and application-ready hyperspectral products. The approach demonstrates the importance of accounting for off-nadir geometry and second-order atmospheric and topographic effects, enabling robust use of PRISMA-SG data for environmental monitoring, snow cover studies, and other Earth observation applications.