Satellite monitoring of inland water bodies is an essential tool for assessing water quality, including the detection of water pollution, eutrophication and algal blooms. The success and accuracy of satellite measurements are highly dependent on rigorous calibration and validation (Cal/Val) processes using in situ reference data. The UFSAT-1 educational mission proposes to bring this monitoring capability to a more accessible scale, including a multispectral camera (Arrok) aimed at detecting algal blooms in coastal and inland waters. Validation of data from new sensors, especially those with specific spectral and spatial characteristics requires efficient methodologies. In this regard, previous studies have performed extensive Cal/Val work for hyperspectral sensors (PRISMA) over various water bodies, including Italian lakes such as Lake Garda and Lake Trasimeno, using validated in situ measurements. These lakes present varied optical characteristics and trophic states different from the eutrophic to hypereutrophic state of Lake San Roque, Argentina, which makes them valuable test sites to evaluate the potential of remote sensing in different aquatic environments.

Based on the importance of Cal/Val and the availability of validated datasets over Garda lake, this work proposes to evaluate the capability of the Arrok camera for water quality monitoring using a simulation approach and analysis of existing data. Validated PRISMA reference hyperspectral data will be used to simulate the spectral response that the UFSAT-1 multispectral camera bands would record over these water bodies. By analyzing how the UFSAT-1 bands would capture the characteristic spectral signatures of water quality indicators (such as Chlorophyll-a, Total Suspended Solids) in the various trophic and optical states present in Garda, we seek to validate the proposed monitoring methodology for UFSAT-1 and characterize its operational capabilities. This approach allows to evaluate the Arrok camera in aquatic environments with properties different from its initial area of focus (San Roque lake), taking advantage of robust validation frameworks and reference data collected in previous studies on this Italian lake. The results will contribute to optimize processing algorithms for UFSAT-1 data and guide its future applications in global water quality monitoring.