A simple Google search provides a lot of positive answers, for instance see http://www.salinityremotesensing.ifremer.fr/

Regards

Be advised, this is sea surface salinity that Vittorio is talking about. I do not know of a method to retrieve vertical profile of salinity, but I would like to know if there are attempts to do so, that would be interesting.   

What extent and resolution you would need? There's the Aquarius data set available at: http://oceancolor.gsfc.nasa.gov/cgi/l3. I guess there are ~4 years of data, it stopped working last year.

Best regards,

Vero 

you can mach salinity with the corresponding vegetation, the aerosol band (OLI, Sentinel ..) provide a best differenciation on sea water caracteristics. the problem is just the coatal areas (1-3 km far from the coast). the water became opac in large and deep areas. the salinity conrol the type of vegetatation and plankton with have different reflectances. you can test this in differents sea surface around the world (Oceans-enclosed  sea and very saline sea) and take some conclusions. good luck

This article contains both a NASA and the European Space Agency ocean water salinity monitoring satellite that could be helpful for your work.

http://earthobservatory.nasa.gov/blogs/fromthefield/2012/09/11/measuring-salinity-from-space/

As mentioned by the others, SMOS and Aquarius were designed to measure the sea surface salinity only, but it provides a nice global map on almost a daily basis. If you are after vertical profiles, you will need to look into the ARGO network (http://www.argo.ucsd.edu/). Those only provide you with point observations of the floats, but in combination with the satellites can be worked into a nice mutli-dimensional profile.

Thanks Christoph for your interested answer

Hi Osama,

according to my simple experience, we have three types of algorithms:

1- Empirical algorithm.

2- Semi-empirical algorithm.

3-  Analytical algorithm.

the third type is very useful for most of remote sensing studies generally and for you work especially, but this type requires. the second type that I used in my paper "A Modified Hopfield Neural Network Algorithm (MHNNA) Using ALOS Image for Water Quality Mapping". this type require to collect validation data from the study area then depend their information positions in the satellite image, so at the same time use the validation data to validate your method that you applied on the satellite image. the second type is good if your study area is limited.