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

•Validation of atmospheric correction algorithms for Sentinel-2 MSI images.•Importance of sunglint correction in tropical waters is highlighted.•Chlorophyll-a models are assessed in the two optical water types in the system.•Locally calibrated chlorophyll-a algorithms outperformed the global algorithms.•Remote monitoring of the system with a single consistent, calibrated model. 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 Mundaú-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 (ρw). Sunglint correction might be essential for retrieving accurate ρw in most low-latitude water bodies. We also found that in Mundaú, 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 Mundaú 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 ρw, considerably poorer results were produced, especially in Mundaú lagoon. The global algorithm was found to be especially sensitive to the at