Ocean color atmospheric correction methods in view of usability for different optical water types

Satellite remote sensing allows large-scale global observations of aquatic
ecosystems and matter fl uxes from the source through rivers and lakes to
coasts, marginal seas into the open ocean. Fuzzy logic classi fi cation of optical
water types (OWT) is increasingly used to optimally determine water properties
and enable seamless transitions between water types. However, effective
exploitation of this method requires a successful atmospheric correction (AC)
over the entire spectral range, i.e., the upstream AC is suitable for each water type
and always delivers classi fi able remote-sensing re fl ectances. In this study, we
compare fi ve different AC methods for Sentinel-3/OLCI ocean color imagery,
namely IPF, C2RCC, A4O, POLYMER, and ACOLITE-DSF (all in the 2022 current
version). We evaluate their results, i.e., remote-sensing re fl ectance, in terms of
spatial exploitability, individual fl agging, spectral plausibility compared to in situ
data, and OWT classi fi ability with four different classi fi cation schemes. Especially
the results of A4O show that it is bene fi cial if the performance spectrum of the
atmospheric correction is tailored to an OWT system and vice versa. The study
gives hints on how to improve AC performance, e.g., with respect to
homogeneity and fl agging, but also how an OWT classi fi cation system should
be designed for global deployment.

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