Atmospheric Correction of Airborne Hyperspectral CASI Data Using Polymer, 6S and FLAASH

Airborne hyperspectral data play an important role in remote sensing of coastal waters. However, before their application, atmospheric correction is required to remove or reduce the atmospheric effects caused by molecular and aerosol scattering and absorption. In this study, we first processed airborne hyperspectral CASI-1500 data acquired on 4 May 2019 over the Uljin coast of Korea with Polymer and then compared the performance with the other two widely used atmospheric correction approaches, i.e., 6S and FLAASH, to determine the most appropriate correction technique for CASI-1500 data in coastal waters. Our results show the superiority of Polymer over 6S and FLAASH in deriving the R-rs spectral shape and magnitude. The performance of Polymer was further evaluated by comparing CASI-1500 R-rs data with those obtained from the MODIS-Aqua sensor on 3 May 2019 and processed using Polymer. The spectral shapes of the derived R-rs from CASI-1500 and MODIS-Aqua matched well, but the magnitude of CASI-1500 R-rs was approximately 0.8 times lower than MODIS R-rs. The possible reasons for this difference were time difference (1 day) between CASI-1500 and MODIS data, higher land adjacency effect for MODIS-Aqua than for CASI-1500, and possible errors in MODIS R-rs from Polymer.