Passive optical calibration, satellite derived bathymetry, water column correction
and bottom typing of shallow water areas using remote sensing imageries.

Use passive hyperspectral or multispectral satellite images 
to retrieve both SDB depth and spectral reflectance of shallow bottom, 
ready for bottom typing, ahead of any field work: no need for field data.

Self-calibrated Supervised Spectral Shallow-sea Modeler

Panchromatic   Pansharpened

And the winner is Uncertainty on depth  Empirical vs Analytical 

I am developing a 4SM_2K_Jerlov page

   4SM workstation     4SM flowchart   

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1 - NO NEED for field data, nor for atmospheric correction
2 - this is demonstrated in this website, using a variety of hyper/multi spectral data
Requirements are
1 - homogeneous water body and atmosphere
2 - some coverage of optically deep water
3 - some coverage of dry land
Problems are
1 - the precision on estimated depth is found wanting, because the noise-equivalent change in radiance  of accessible data is too high for shallow water column correction work 
2 - radiance data should be preprocessed by the provider at level 1 in order to improve S/N ratio
3 - exponential decay: the deeper/darker the bottom, the poorer the performances
I keep digging
until suitable data
become available
Two peer-revued articles:

October 2016
Two Landsat 8 time series in the Bahamas
No need for formal atmospheric correction
No use of field data for optical calibration
Water column corrected signatures calibrated into reflectance (0-1) for OLI and WV2
This also works with PAN-sharpenned images