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

Abstract

We evaluated MERIS spectral inversion processors in the estimation of chlorophyll a (Chl-a), total suspended matter (TSM), absorption of colored dissolved organic matter (aCDOM at 443nm) and Secchi disk transparency (ZSD) in four lakes located in southern Finland. The lakes represent oligotrophic, mesotrophic and humic (high aCDOM, low TSM) lake types. Our validation data was extensive, consisting of remote sensing reflectance (Rrs) 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 Rrs when compared to the effect caused by the differences in the atmospheric correction versions. The use of ICOL improved the estimation of Rrs and therefore all IOP and water quality validations were made with ICOL pre-processed data. Rrs was best estimated with RP2 BOR, although it somewhat overestimated Rrs in blue in the humic lake. RP3 BOR greatly overestimated the Rrs 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 aCDOM. 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 aCDOM(443) estimation were related to the partition of atot to phytoplankton and CDOM absorption, which emphasizes the importance of including IOP measurements in the validation studies. ZSD was best estimated on the basis of atot and btot, 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 atot and btot 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.