Suitability of different in-water algorithms for eutrophic and absorbing waters applied to Sentinel-2 MSI and Sentinel-3 OLCI data - Ansper-Toomsalu, Ave; Uusõue, Mirjam; Kangro, Kersti; Hieronymi, Martin; Alikas, Krista (Frontiers in Remote Sensing, 2024)
Optically complex waters present significant challenges for remote sensing due to high concentrations of optically active substances (OAS) and their inherent optical properties (IOPs), as well as the adjacency effect. OAS and IOPs can be derived from atmospheric correction processors' in-water algorithms applied to data from Sentinel-2 MultiSpectral Instrument (S2 MSI) and Sentinel-3 Ocean and Land Colour Instrument (S3 OLCI). This study compared S3 OLCI Level-2 in-water products for Case-2 waters with alternative in-water algorithms derived from Acolite, Polymer, C2RCC and A4O. Fifty in-water algorithms were evaluated using an extensive match-up data set from lakes and coastal areas, focusing particularly on small lakes with high colored dissolved organic matter absorption at 442 nm (up to 48 m -1 ). The Chl a band ratio introduced by Gons (2002) applied to data processed by Acolite, performed best for S3 OLCI Chl a retrieval (dispersion = 23 %, bias = 10 %). The Gons (2002) band ratio also showed consistent agreement between S3 OLCI and S2 MSI resampled data (intercept of 6.27 and slope of 0.83, close to the 1:1 line); however, lower Chl a values (< 20 mg/m 3 ) were overestimated by S2 MSI. When estimating errors associated with proximity to land, S2 MSI Chl a inwater algorithms had higher errors close to the shore (on average 315 %) compared to S3 OLCI (on average 150 %). Chl a retrieved with Polymer had the lowest errors close to the shore for both S2 MSI and S3 OLCI data (on average 70 %). TSM retrieval with C2RCC performed well for S2 MSI (dispersion 24 %, bias -12 %). Total absorption was most accurately derived from C2RCC applied to S3 OLCI L1 data (dispersion < 43 %, bias < -39 %) and it was better estimated than its individual components: phytoplankton, mineral particles, and colored dissolved organic matter absorption. However, none of the colored dissolved organic matter absorption in-water algorithms performed well (dispersion > 59 %, bias < -29 %).