Oral Session 3

Multi-sensor analysis for estimating water quality parameters in a shallow and highly dynamic lake

Remote sensing is a valuable tool for conducting multi-spatial and multi-temporal analyses of inland waters. However, a single-sensor analysis can be limiting in highly dynamic settings, as in the case of Lake Trasimeno (Italy), where wind and temperature significantly affect the diurnal lake conditions. The dynamic of this environment was confirmed through continuous measurements from a fixed radiometer placed in the lake (WISPStation). In this context, this study aims to exploit hyperspectral and multispectral sensors to understand the intra- and inter-daily dynamics of Lake Trasimeno. The dataset includes 17 dates between 2019-2023, and a total of 105 remote sensed imagery from four hyperspectral sensors (PRISMA, DESIS, ENMAP, AVIRIS) and eight multispectral sensors (Landsat-8, Sentinel-2, Sentinel-3A/B, MODIS-Aqua/Terra, VIIRS-SNPP/JPSS). The Level-2 images are used as input into the BOMBER bio-optical model to generate maps of solid particulate matter and chlorophyll-a. Then, a comparison at both spectral and concentration levels was conducted between the remote sensed imagery and data obtained from the WISPStation. Spectral analysis showed a good agreement between the remote sensed imagery and the WISPStation data (MAPE=28.8%, SA=11.6°). The lowest agreement was found in the blue domain (R2=0.4), while a strong correlation emerged in the range between 600-705 nm (R2=0.8). In particular, PRISMA, Sentinel-3A/B, and MODIS-Aqua/Terra demonstrated the best performance. Preliminary results on water quality parameter concentrations confirmed that the multi-sensor analysis was crucial to detecting diurnal changes in the lake that would have been impossible to capture when performing a single-sensor analysis.

Nicola Ghirardi, National Research Council Institute of BioEconomy (CNR IBE), Italy, https://orcid.org/0000-0002-5006-9853

Alice Fabbretto, National Research Council Institute for the Electromagnetic Survey of the Atmosphere (CNR IREA), Italy, https://orcid.org/0009-0006-8025-9179

Andrea Pellegrino, National Research Council Institute for the Electromagnetic Survey of the Atmosphere (CNR IREA), Italy, https://orcid.org/0009-0002-4152-3409

Salvatore Mangano, National Research Council Institute for the Electromagnetic Survey of the Atmosphere (CNR IREA), Italy, https://orcid.org/0000-0002-1953-4825

Claudia Giardino, National Research Council Institute for the Electromagnetic Survey of the Atmosphere (CNR IREA), Italy, https://orcid.org/0000-0002-3937-4988

Mariano Bresciani, National Research Council Institute for the Electromagnetic Survey of the Atmosphere (CNR IREA), Italy, https://orcid.org/0000-0002-7185-8464

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