Bio-Optical Model Specification
Details of the algorithm for the retrieval of water constituents are provided in an ATBD, which can be found at
http://www.brockmann-consult.de/beam-wiki/display/LAKES/Home
The following gives only a brief overview.
Input to the algorithms are the water leaving radiance reflectances of 8 MERIS bands. These data are the output of
the atmospheric correction (s. atmospheric correction ATBD). The algorithms derive data of the inherent optical
properties total scattering of particles (total suspended matter, tsm) b_tsm, the absorption coefficient of
phytoplankton pigments a_pig and the absorption of dissolved organic matter a_gelb (gelbstoff), all at 443 nm (MERIS
band 2). From these IOPs the concentrations of phytoplankton chlorophyll and of total suspended dry weight are
determined. Furthermore, the attenuation coefficient for the downwelling irradiance, k, at the wavelength with
maximum transparency is determined (k_min) as well as the z90 signal depth, which indicates the water depth from
which 90% of the reflected light comes from. The algorithm is based on a neural network (NN), which relates the
bi-directional water leaving radiance reflectances with these concentration variables. The network is trained with
simulated reflectances. The bio-optical model used for the simulations is based on a data set collected in different
lakes in Finland and Spain.
Two NN's are trained with simulated reflectances:
- invNN to emulate the inverse model
(reflectances, geometry) --> concentrations, and
- forwNN to emulate the forward model
(concentrations, geometry) --> reflectances.
The invNN is used to obtain an estimate of the concentrations which is used as a first guess to start a
minimization
procedure, which uses the forwNN iteratively to minimize the difference between the calculated reflectances and
the
measured ones. The procedure is fast as it takes advantage of the Jacobian, which is a byproduct of the NN
calculation.
