Atmospheric and sunglint correction for retrieving chlorophyll-a in a productive tropical estuarine-lagoon system using Sentinel-2 MSI imagery

Remote monitoring of chlorophyll-a (chla) has been widely used to evaluate the trophic state of inland and coastal waters, however, there is still much uncertainty in the algorithms applied in different optical water types. The influence of different atmospheric correction (AC) processors, which can also provide correction for sunglint and adjacency effects, on the retrieved chla is poorly understood. In this study, state-of-the-art atmospheric correction and chla algorithms are evaluated using Sentinel-2 MSI imagery in the Mundau-Manguaba Estuarine-Lagoon System (MMELS), a productive tropical system that consists of two turbid lagoons of different optical water types (OWT). We compared the performance of six AC processors, with the addition of sunglint correction for two of them, with field measured water reflectance. There was difficulty in correcting for the atmospheric effects, especially for bands 2, 3 and 8A. Overall, C2X showed the best performance over MMELS, but with sunglint correction, ACOLITE and GRS provided the most consistent water reflectance (rho(w)). Sunglint correction might be essential for retrieving accurate rho(w) in most low-latitude water bodies. We also found that in Mundau, the dense urban area surrounding it likely caused heavy adjacency effects in the satellite-retrieved reflectance, and thus correction for it is necessary. We also compared the performance of six chla algorithms recommended for the OWTs present in MMELS in addition to a widely applied and a global chla algorithm in retrieving this variable using both field and satellite reflectance, in this case corrected with the three best performing processors. For the in situ data, most algorithms performed well in Manguaba lagoon, while in Mundau lagoon the semi-analytical NIR-red ratio (2SAR) algorithm was the most consistent model, and in both cases the locally calibrated algorithms outperformed the global algorithm. When retrieving chla with the satellite-derived rho(w), considerably poorer results were produced, especially in Mundau lagoon. The global algorithm was found to be especially sensitive to the atmospheric effects. We also found that the quality of AC provided by the algorithms is not a general predictor of the performance of the chla models, even when analysing individual bands separately, while the relationship between chla concentration and the ratio of bands used by most algorithms can be. Despite containing distinct water characteristics, chla can be modelled using a single algorithm, 2SAR, calibrated for MMELS as a whole, with r(2) of 0.77 and nRMSE of 38.7%, and we consider that 2SAR has the potential to be a global algorithm for these OWTs, provided that it is recalibrated for a large dataset of satellite-derived BOA reflectance. We recommend that further studies explore the impacts of AC, sunglint and adjacency effects on the performance of chla algorithms, in order to delineate the most suitable combinations of AC + chla algorithms for the variable OWTs, in an effort to provide the basis for global-scale retrievals of this pigment using medium-resolution sensors such as MSI and OLI.

Automated summary

Remote monitoring of chlorophyll-a (chla) is widely used for assessing the trophic state of water bodies, but the algorithms applied in different optical water types still face uncertainties. The study evaluated state-of-the-art atmospheric correction and chla algorithms using Sentinel-2 MSI imagery in a tropical system, highlighting the importance of addressing atmospheric and adjacency effects. The research suggests the need to explore suitable combinations of AC + chla algorithms for different optical water types to enable global-scale retrievals of chlorophyll-a pigment using medium-resolution sensors.