Effects of atmospheric correction of Landsat imagery on lake water clarity assessment. Issue 11 (1st December 2015)

• Record Type: Journal Article
• Authors: Bonansea, Matias; Ledesma, C.; Rodríguez, C.; Pinotti, L.; Antunes, M. Homem
• Is Part Of: Advances in space research. Volume 56:Issue 11(2015)
• Page Start: 2345
• Page End: 2355
• Publication Date: 2015-12-01
• Subjects: Atmospheric correction -- Landsat -- Reservoir -- 6S model -- Water clarity; Space sciences -- Periodicals; Astronautics -- Periodicals; Geophysics -- Periodicals; 500.505
• DOI: 10.1016/j.asr.2015.09.018
• Languages: English
• ISSNs: 0273-1177

Abstract

Highlights: Water clarity was estimated using Landsat ETM+ imagery. Atmospheric correction reduces the effects of scattering and absorption. Statistical analysis was used to select the ETM+ bands most correlated with SDT. Water clarity algorithms were improved correcting the atmospheric effects. The 6S code improved reliability for estimating water clarity. Abstract: Empirical relationships between Landsat data and water clarity expressed in terms of Secchi disk transparency (SDT) have been widely used for monitoring and assessment of water quality. The atmosphere affects differently sensor bands depending on the waveband, thus affecting the relationships obtained from top-of-atmosphere reflectance. The objective of this study was to evaluate whether the reliability of water clarity can be improved applying atmospheric correction of Landsat imagery. Further, a general predictive algorithm to determine water clarity in the reservoir was developed. Samples of SDT were taken from Río Tercero reservoir (Argentina). Landsat images were atmospheric corrected using the 6S code. Estimated values of SDT with and without atmospheric correction were compared for their differences. Results suggested that atmospheric corrected values of Landsat band 3 and the ratio 1/3 proved to be the best predictor of water clarity in the reservoir ( R 2 = 0.84). Using the 6S code we demonstrate the usefulness of atmospheric correction to Landsat data since water clarity algorithm using surface reflectance was more reliable than the top-of atmosphere reflectance model.