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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 a CDOM 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.

Over the past few years, the increased spectral and spatial resolution of remote sensing equipment has promoted the investigation of new techniques for inland and coastal water monitoring. The availability of new high-resolution data has allowed improvements in models based on the radiative transfer theory for assessing optical water quality parameters. In this study, we fine-tuned a physical model for the highly turbid Venice lagoon waters and developed an inversion technique based on a two-step optimization procedure appropriate for hyperspectral data processing to retrieve water constituent concentrations from remote data. In the first step, the solution of a linearized analytical formulation of the radiative transfer equations was found. In the second step, this solution was used to provide the initial values in a non-linear least squares-based method. This effort represents a first step in the construction of a feasible and timely methodology for Venice lagoon water quality monitoring by remote sensing, especially in view of the existing experimental hyperspectral satellite (Hyperion) and the future missions such as PRISMA, EnMap and HyspIRI. The optical properties of the water constituents were assessed on the basis of sea/lagoon campaigns and data from the literature. The water light field was shaped by an analytical formulation of radiative transfer equations and the application of numerical simulations (Hydrolight software). Once the optical properties of the Venice lagoon bio-optical model were validated, the inverse procedure was applied to local radiometric spectra to retrieve concentrations of chlorophyll, colored dissolved organic matter and tripton. The inverse procedure was validated by comparing these concentrations with those measured in the laboratory from in situ water samples, then it was applied to airborne (CASI and MIVIS) and satellite (Hyperion) sensors to derive water constituent concentration maps. The consistent results encourage the use of this procedure using future missions satellite (PRISMA, EnMap and HyspIRI).

As it can strongly influence the availability of light and thus primary production, coloured dissolved organic matter (CDOM) affects the function of lake ecosystems. Therefore reliable methods are required for the monitoring of CDOM concentration. A new method using downwelling irradiance was tested for applicability in four selected lakes of the Bavarian Osterseen Lake District, which consists of 19 naturally connected freshwater lakes of different trophic level. The method separates between the direct and diffuse part of the incident light in order to handle the strong variability of the underwater light field. It is implemented in the software WASI, which is capable to retrieve water constituents by inverse modeling. During field campaigns downwelling irradiance measurements using RAMSES sensors were made in different depths. Simultaneously, water samples were taken in three depths (0.5 m, 2 m and Secchi disk depth), from which the absorption coefficient of CDOM, a Y , was derived in the range from 190 to 900 nm using photometric absorption measurements. Concentration (defined as a Y at 440 nm) ranged from 0.33 to 1.55 m -1 with a mean of 0.71 m -1 ± 0.04 m -1 , the spectral slope at 440 nm from 0.0120 to 0.0184 nm-1 with a mean of 0.0145 ± 0.0008 nm -1 . These laboratory measurements from water samples were compared to CDOM concentration obtained by inverse modeling of downwelling irradiance measurements using WASI. For sensor depths lower than 1 to 1.5 m large uncertainties were observed. The measurements in 2 m depth and at Secchi disk depth yielded good correlation between water sample and WASI derived data (R 2 = 0.87) with a mean standard deviation of 0.06 m -1 for the determined CDOM concentrations. This new method is an alternative to laboratory analysis of water samples from in situ measurements of CDOM concentration.