Assessment of Scattering Error Correction Techniques for AC-S Meter in a Tropical Eutrophic Reservoir

• Main Authors: Fernanda Watanabe, Thanan Rodrigues, Alisson do Carmo, Enner Alcântara, Milton Shimabukuro, Nilton Imai, Nariane Bernardo, Luiz Henrique Rotta
• Format: Article
• Language: English
• Published: MDPI AG 2018-05-01
• Series: Remote Sensing
• Subjects: absorption coefficient; bio-optical properties; Case 2 waters; ac-s meter
• Online Access: http://www.mdpi.com/2072-4292/10/5/740

Measurements of absorption coefficients (a(λ), in m−1) collected by spectrophotometers in situ are overestimated due to the scattering of the reflecting tube absorption meter. Accurate correction of these data is essential in order to characterize water bodies bio-optically, as well as retrieve the remote sensing reflectance (Rrs, in sr−1), when applying a forward model. There are various methods of scattering error correction; however, they were all developed for clear water. In this research, different techniques were attempted in order to define the most appropriate method for correcting a(λ) values acquired by an absorption and attenuation spectral (ac-s) meter (WET Labs Inc., Philomath, OR, USA) in a tropical eutrophic reservoir. Three methods recommended by the manufacturer of the ac-s meter were tested: “flat” or “baseline”, “constant fraction”, and “proportional”. These methods were applied to two datasets that were measured in May and October 2014. The flat technique exhibited the lowest errors, with an average normalized root mean square error (NRMSE) of 7.95%, and a mean absolute percentage error (MAPE) of 29.26% for May. Meanwhile, proportional was the most suitable technique for most of the samples in October, with a mean NRMSE of 11.19% and a MAPE of 31.03% for October. In addition, the proportional method maintained the shape of the a(λ) values better than the other methods. Despite that, both the flat and proportional methods gave a similar performance statistically. Moreover, the flat method produced the best estimations of chla content for both datasets. Therefore, this method is recommended to correct ac-s data in retrieving such phytoplankton pigments.