POSTER SESSION 4
10:30–12:30, Thursday, September 17
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
ABSTRACT 1329 | POSTER 40
HYPERESPECTRAL REFLECTANCE MODEL FOR ORGANIC AND INORGANIC PARTICULATE MATTER CHARACTERIZATION
Water optical quality is strongly influenced by suspended particulate matter (SPM) and its organic (POM) and inorganic (PIM) fractions, which have distinct optical properties. In optically complex waters, hyperspectral remote sensing offers new opportunities to quantify these fractions by capturing subtle variations in the spectral shape of remote sensing reflectance (Rrs). This study evaluated the potential of hyperspectral reflectance to estimate POM and PIM in the complex waters of Southern Brazil. Concentrations of SPM, POM, PIM, and chlorophyll-a were obtained from six field campaigns conducted between 2023 and 2025, together with synchronous above-water Rrs measurements. The spectra were decomposed using Empirical Orthogonal Functions (EOFs), and the resulting scores were applied in Generalized Linear Models to estimate particulate matter fractions. Results showed a predominance of PIM in most sampling areas, while selected stations along the Santa Catarina coast presented higher POM contributions, averaging 59% of SPM. This increase was not associated with higher chlorophyll-a concentrations, suggesting that POM variability was not mainly driven by active phytoplankton biomass, but likely by detrital, refractory, laterally transported, or resuspended organic material. The models performed better for POM and PIM than for total SPM, indicating that hyperspectral data may be more effective for discriminating particulate composition than for estimating total particulate concentration. The ongoing analyses aim to apply the developed equations to hyperspectral imagery from PACE, EnMAP, and PRISMA to assess their spatial applicability and consistency across different optical conditions. The results reinforce the potential of hyperspectral approaches for characterizing SPM composition in complex waters.
Catharina Cardoso*, Federal University of Rio Grande (FURG), [email protected]
Nikolas Heinz, Federal University of Rio Grande, [email protected]
Ana Paula Forgiarini, Federal University of Rio Grande, [email protected]
Maria Fernanda Giannini, Federal University of Rio Grande, [email protected]
Poster Session | 1 | 2 | 3 | 4 | Schedule at a Glance
