A revision of NASA SeaDAS atmospheric correction algorithm over turbid waters with artificial Neural Networks estimated remote-sensing reflectance in the near-infrared br

For atmospheric correction over turbid waters, due to non-negligible water-leaving radiance (Lw) in the near -infrared (NIR), measurements in the short-wave infrared (SWIR) are usually required to achieve reliable remote-sensing reflectance (Rrs). But several ocean color satellite sensors, such as the Sea-viewing Wide Field-of -view Sensor (SeaWiFS) and other small satellites, have no bands in the SWIR domain. We here present an at-mospheric correction algorithm (termed as ACANIR-NN) based on NASA SeaDAS (version 7.5.3), which can achieve atmospheric correction seamlessly over clear and turbid waters, even for sensors having no spectral bands in SWIR. Specifically, ACANIR-NN uses estimated Rrs(NIR) from available Rrs in the visible bands with a specifically designed artificial Neural Networks to carry out atmospheric correction, and the performance of ACANIR-NN is evaluated over eight coastal locations having ground measurements by the Aerosol Robotic Network-Ocean Color (AERONET-OC) system. It is found that the Mean Absolute Percent Difference (MAPD) of Rrs retrievals by ACANIR-NN for this dataset is smaller by a factor of two or more than that by the standard SeaDAS algorithm (termed as ACANIR-bio) for each band, especially for Rrs(412) and Rrs(443), which is 7.5% and 7.7%, respectively, from ACANIR-NN, but they are 44.0% and 27.5% from ACANIR-bio. We further demonstrated the applicability of ACANIR-NN to SeaWiFS measurements over turbid waters, where consistent Rrs products were also obtained compared to that generated from the same-day MODerate resolution Imaging Spectrometer (MODIS) measurements using SWIR bands. These results indicate that ACANIR-NN can generate reliable Rrs over turbid coastal areas, as well as clear ocean waters, for sensors having no SWIR bands.

Automated summary

In this study, an atmospheric correction algorithm named ACANIR-NN based on NASA SeaDAS was proposed to achieve reliable atmospheric correction without SWIR bands for sensors. The performance of ACANIR-NN was evaluated at eight coastal locations and compared with ground measurements, showing that ACANIR-NN retrieved Rrs with smaller Mean Absolute Percent Difference (MAPD) compared to the standard SeaDAS algorithm. The applicability of ACANIR-NN to turbid waters was also demonstrated using SeaWiFS measurements.