@article{fdi:010081399,
  title = {{A}tmospheric and sunglint correction for retrieving chlorophyll-a in a productive tropical estuarine-lagoon system using {S}entinel-2 {MSI} imagery},
  author = {{T}avares, {M}. {H}. and {L}ins, {R}. {C}. and {H}armel, {T}. and {F}ragoso, {C}. {R}. and {M}artinez, {J}ean-{M}ichel and {M}otta-{M}arques, {D}.},
  editor = {},
  language = {{ENG}},
  abstract = {{R}emote 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. {T}he influence of different atmospheric correction ({AC}) processors, which can also provide correction for sunglint and adjacency effects, on the retrieved chla is poorly understood. {I}n this study, state-of-the-art atmospheric correction and chla algorithms are evaluated using {S}entinel-2 {MSI} imagery in the {M}undau-{M}anguaba {E}stuarine-{L}agoon {S}ystem ({MMELS}), a productive tropical system that consists of two turbid lagoons of different optical water types ({OWT}). {W}e compared the performance of six {AC} processors, with the addition of sunglint correction for two of them, with field measured water reflectance. {T}here was difficulty in correcting for the atmospheric effects, especially for bands 2, 3 and 8{A}. {O}verall, {C}2{X} showed the best performance over {MMELS}, but with sunglint correction, {ACOLITE} and {GRS} provided the most consistent water reflectance (rho(w)). {S}unglint correction might be essential for retrieving accurate rho(w) in most low-latitude water bodies. {W}e also found that in {M}undau, the dense urban area surrounding it likely caused heavy adjacency effects in the satellite-retrieved reflectance, and thus correction for it is necessary. {W}e also compared the performance of six chla algorithms recommended for the {OWT}s 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. {F}or the in situ data, most algorithms performed well in {M}anguaba lagoon, while in {M}undau lagoon the semi-analytical {NIR}-red ratio (2{SAR}) algorithm was the most consistent model, and in both cases the locally calibrated algorithms outperformed the global algorithm. {W}hen retrieving chla with the satellite-derived rho(w), considerably poorer results were produced, especially in {M}undau lagoon. {T}he global algorithm was found to be especially sensitive to the atmospheric effects. {W}e 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. {D}espite containing distinct water characteristics, chla can be modelled using a single algorithm, 2{SAR}, calibrated for {MMELS} as a whole, with r(2) of 0.77 and n{RMSE} of 38.7%, and we consider that 2{SAR} has the potential to be a global algorithm for these {OWT}s, provided that it is recalibrated for a large dataset of satellite-derived {BOA} reflectance. {W}e 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 {OWT}s, in an effort to provide the basis for global-scale retrievals of this pigment using medium-resolution sensors such as {MSI} and {OLI}.},
  keywords = {{C}hlorophyll-a (chl-a) ; {S}entinel-2 {MSI} ; {T}urbid productive waters ; {A}lgorithm validation ; {O}ptical water type ; {W}ater quality ; {BRESIL} ; {ZONE} {TROPICALE} ; {ALAGOAS} ; {MUNDAU} {LAGUNE} ; {MANGUABA} {LAGUNE}},
  booktitle = {},
  journal = {{ISPRS} {J}ournal of {P}hotogrammetry and {R}emote {S}ensing},
  volume = {174},
  numero = {},
  pages = {215--236},
  ISSN = {0924-2716},
  year = {2021},
  DOI = {10.1016/j.isprsjprs.2021.01.021},
  URL = {https://www.documentation.ird.fr/hor/fdi:010081399},
}