Self-calibrated Supervised Spectral Shallow-sea Modeler
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.

And the winner is Uncertainty on depth  Empirical vs Analytical 

I am developing a 4SM_2K_Jerlov page
   4SM workstation  4SM flowchart   

  home page continued


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
July 2017
4SM: a Novel Self-calibrated Algebraic Ratio Method
for Satellite Derived Bathymetry 
and Water Column Correction
Sept 2017
4SM Method Tested in the Gulf of California 
Suggests Field Data are Not Needed  
to Derive Satellite Bathymetry

In conclusion, the findings suggest that 4SM 
is as accurate as the commonly used Stumpf’s method, 
the only difference being the independence of 4SM from previous field data, 
and the potential to deliver bottom spectral characteristics for further modeling. 
4SM thus represents a significant advance in coastal remote sensing potential 
to obtain bathymetry and optical properties of the marine bottom.

A time series of Landsat 8 at La Paz, Baja California
15 m GSD NO Smoothing required   RMSE~=1 m

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