Spectral band adaptation of ocean color sensors for applicability of the multi-water biogeo-optical algorithm ONNS

Abstract

The ocean color algorithm ONNS (OLCI Neural Network Swarm) is designed to process remote-sensing reflectances at 11 Sentinel-3/OLCI bands in order to derive water quality parameters for most natural waters [Hieronymi et al., Front. Mar. Sci. 4, 140 (2017)]. The present work introduces a spectral band-shifting procedure, which allows exploitation of atmospherically corrected input from SeaWiFS, MODIS, MERIS, OCM-2, VIIRS, SGLI, GOCI-2, EnMAP, or PACE/OCI and corresponding utilization of ONNS or other ocean color algorithms. The performance of the band adapters is evaluated in view of diverse optical water types. In the spectral range between 400 and 600 nm, the mean percentage retrieval error is mostly <5%. The band adaptation is a tool for cross-mission Earth observation and uncertainty estimate, as well as for extended possibilities of algorithm validation.