Validation of MERIS spectral inversion processors using reflectance, IOP and water quality measurements in boreal lakes

We evaluated MERIS spectral inversion processors in the estimation of chlorophyll a (Chl-a), total suspended matter (TSM), absorption of colored dissolved organic matter (a(CDOM) at 443 nm) and Secchi disk transparency (Z(SD)) in four lakes located in southern Finland. The lakes represent oligotrophic, mesotrophic and humic (high a(CDOM), low TSM) lake types. Our validation data was extensive, consisting of remote sensing reflectance (R-rs) measured in the field, detailed measurements of (specific) inherent optical properties ((S)IOP) and water quality measurements. Validation measurements were collected at stations and as spatially intensive transects. The tested processors were Boreal lakes (BOR) and Free University of Berlin WeW WATER processor (FUB). In the case of BOR we included two versions, the original one available in 2008 and the most recent version. The processing chains of these versions differed in terms of MERIS archive reprocessing (2nd reprocessing (RP2) and 3rd reprocessing (RP3) were used), version of adjacency effect correction (ICOL) and rectification method. However, all these had only minor effect on the estimated R-rs when compared to the effect caused by the differences in the atmospheric correction versions. The use of ICOL improved the estimation of R-rs and therefore all IOP and water quality validations were made with ICOL pre-processed data. R-rs was best estimated with RP2 BOR, although it somewhat overestimated R-rs in blue in the humic lake. RP3 BOR greatly overestimated the R-rs in blue. FUB was outside its aCDOM training range in most of the studied lakes. RP2 BOR estimated water quality with the best accuracy in mesotrophic lakes, but failed in humic and clear water lakes. BOR overestimated Chl-a, particularly with RP3. The best TSM correlation was for RP2 BOR. All processors underestimated a(CDOM). The SIOP measurements showed that overestimation of Chl-a was not due to incorrect conversion factors, and that underestimation of TSM was to some extent explained by lower average conversion factor than that measured in the validation lakes. The inaccuracies in Chl-a and a(CDOM)(443) estimation were related to the partition of a(tot) to phytoplankton and CDOM absorption, which emphasizes the importance of including IOP measurements in the validation studies. Z(SD) was best estimated on the basis of a(tot) and b(tot), which were separately calculated from BOR output and the bio-optical model assumed in the processor. For the needs of transparency estimation the processors should produce a(tot) and b(tot) for all MERIS bands as standard output. Atmospheric correction over humic lakes is another problem to be solved in future versions of the processors. The 2008 version of BOR provided better atmospheric correction results in humic lakes and is thus more applicable in the boreal zone where these lakes are common. This suggests that before a new processor version is published it should be validated with existing in situ data. (C) 2014 Elsevier Inc. All rights reserved.