POSTER Session 4

COMPARISON OF ATMOSPHERIC CORRECTION METHODS FOR SENTINEL-2 AND LANDSAT 8 DATA PROCESSING: A CASE STUDY FOR THE ESTIMATION OF SUSPENDED PARTICULATE MATTER CONCENTRATION IN THE DANUBE DELTA

Understanding the dynamics of suspended particulate matter (SPM) in aquatic ecosystems is essential for assessing water quality and ecosystem health. Remote sensing offers a powerful tool for monitoring SPM concentrations over large spatial and temporal scales. However, accurate retrieval of water quality parameters from satellite images requires careful consideration of atmospheric effects. These corrections pose significant challenges in complex areas, where aerosol optical properties tend to vary considerably. Large ranges of biogeochemical variables contribute, as well, to the difficulty in finding the optimal processing scheme. This study aims to present the outcomes of a comparative analysis of atmospheric correction methods, with the final goal to retrieve SPM concentrations in the Danube Delta area. Data collected by the Sentinel-2 and Landsat 8 satellite missions were used. Specifically, two atmospheric correction techniques were compared: the dark spectrum fitting (DSF) (Vanhellemont and Ruddick, 2018) and the C2RCC neural network (Brockmann et al., 2016; Doerffer et al., 2007). The combination of these two, using a multi-conditional pixel-based switching method was also tested (Van der Zande et al., 2022). By evaluating the performance of each approach, using in-situ measurements as reference, this study contributes to enhance our understanding of SPM dynamics inside the river-delta-sea system formed by the Danube when entering the Black Sea, using high-resolution satellite imagery.

*Georgiana Anghelin, TERRASIGNA/University of Bucharest, Romania, [email protected]

Sorin Constantin, TERRASIGNA, Romania, [email protected]

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