Validation of MERIS bio-optical products within situdata in the turbid Lithuanian Baltic Sea coastal waters

Abstract

In this study bio-optical water quality indicators, chlorophyll a, colored dissolved organic matter (CDOM), and total suspended matter (TSM) were derived from the Envisat-MERIS satellite data and were compared with in situ measurements collected in the Lithuanian optically Case 2 coastal waters of the Baltic Sea. Eight MERIS full-resolution Level 1b images, acquired during late spring and summer 2010, were processed using five, neural network-based processors for optically Case 2 or coastal and inland waters: FUB, C2R, Eutrophic, Boreal, and standard MERIS Level 2. Results showed that the FUB processor provided the most accurate estimates of the concentration of chlorophyll a [R 2 ¼ 69%; mean absolute errorðMAEÞ ¼ 7.76 mg∕m 3 ] and TSM (R 2 ¼ 89%; MAE ¼ 3.93 g∕m 3). In situ CDOM absorption was most accurately estimated using the Boreal processor (R 2 ¼ 69%; MAE ¼ 0.20 1∕m). We analyzed the factors that were most influential in explaining the differences in the accuracy and found that the Secchi depth and the sampling time were the most important factors. The greatest differences between satellite-derived and in situ values of water quality indicators were in correspondence with the lowest Secchi depth, suggesting that the plume zone created by freshwater coming from the hyper-eutrophic lagoon was the most sensitive region for the validation. The evident match between in situ measurements and satellite-based estimates was observed when field measurements were acquired 1-2 h before to approximately 2-4 h after the satellite overpass. Results of this validation work confirmed that remote sensing techniques are suitable for monitoring the changes of optical constituents in Lithuanian coastal waters.

Retrieval of suspended particulate matter from turbidity – model development, validation, and application to MERIS data over the Baltic Sea

“…The Klaipeda Strait provides a narrow connection with a large, freshwater, shallow water body, the Curonian Lagoon (total area 1584 km 2 , mean depth 3.8 m). The mixing of fresh and brackish water masses creates spatially and temporally unstable salinity gradients ranging from 0 PSU inside the lagoon to 7 PSU offshore (Dailidienė and Davulienė 2008;Vaičiūtė, Bresciani, and Bučas. 2012).…”

“…These methods are used to retrieve SPM concentration in optically complex waters, such as the Baltic Sea, where the optical signal of SPM does not necessarily co-vary with chlorophyll concentration. Previous studies in the NW and SE Baltic Sea (Kratzer and Vinterhav 2010;Beltrán-Abaunza, Kratzer, and Brockmann 2014;Vaičiūtė, Bresciani, and Bučas. 2012) have shown that the SPM products from the ocean colour multi-spectral spectrometer 'medium-resolution imaging spectrometer' (MERIS) over-or underestimate SPM concentration by about 8-16%, depending on the processor used.…”

Spatial and temporal distribution of coloured dissolved organic matter in a hypertrophic freshwater lagoon

“…The latter was validated by match-ups with in situ data and relatively good agreement (R 2 =0.69; MAE=0.20 m -1 ) between in situ and Boreal-derived CDOM absorption was found (Vaičiūtė et al 2012). We used the standard cloud mask tool (Cloud Probability Processor, version 1.5.203) available in the BEAM VISAT software to detect and eliminate cloud-contaminated pixels.…”

Using MERIS data to assess the spatial and temporal variability of phytoplankton in coastal areas

“…Previous research has shown that MERIS data can be used to monitor coastal areas in the Baltic Sea and that the concentration of chl-a can be derived reliably despite the high absorption by yellow substances (Kratzer, Brockmann, and Moore 2008;Vaičiūtė, Bresciani, and Bučas 2012;Attila et al 2013;Beltrán-Abaunza, Kratzer, and Brockmann 2014;Harvey, Kratzer, and Philipson 2015).…”