Mapping sea surface salinity from MODIS satellite data

The water salinity is the one of the important environmental marine factors and play important role in the Prediction of the surface ocean currents, spatial analysis of the fish aggregation, determination the density and studying its changes and also in ecological properties.
This parameter change greatly with time and space and proper recognition is need to short time intervals measuring (monthly) for Multiple points of the study area.
in the classic way, appraising one or more specific factors of water quality is expensive and spend great time and also is not good indicator for the whole area of a large region. But In recent years satellite technology and remote sensing are considered as appropriate tool for the assessment some of the water quality parameters, because due to the digital nature of this data, extensive availability, regular measurement, repeating data in the short time periods and spending less time and cost, can complete wide range of project .
the purpose of this study is mapping sea surface salinity of Persian Gulf in iran and Gulf of st Lawrence in the Canada,using MODIS satellite data. in this regard a software produced in IRAN for the first time that can create salinity, temperature and density maps of sea surface In three different models with proper accuracy
by entering the MODIS satellite data and field data.
High ability and flexibility of artificial Neural Network in approximation of nonlinear and linear continuous functions in hybrid space, led this study to provide a new method based on using this network in which salinity map determines by a multilayer perceptron network.