the Self-calibrated Supervised Spectral Shallow-sea Modeler

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


Use passive hyperspectral or multispectral satellite images to retrieve both
depth and spectral reflectance of shallow bottom, ready for bottom typing, ahead of any field work.


   r   

   I am developing a 4SM_2K_Jerlov page: it is time you get updated!
 




 
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
 
So
I keep digging
until suitable data
become available
 

Optical calibration does not need any field data:
the image itself contains all the information that is needed for a "ratio method"

 

Users of Geomatica, ENVI, Erdas, TNTmips, ERmapper, Ilwis, Idrisi, etc,
 no sweat: I only use open source 

            
Leave difficult cases
to semi-analytical methods!


 
Further to Lyzenga et al's empirical ratio method: water volume reflectance is an important variable.
No need for atmospheric correction.
Uses Jerlov's data for optical calibration.
Landsat 8

See work may2016
at LaParguera, Puerto Rico


See work July2016
at Caicos Bank, Bahamas
Just use a X86 or AMD64 laptop
running Linux.
From importing raw data to formating deliverables in one single 4SM executable code.
Uses a bash command line, focussed on productivity.
Users of Lyzenga's
or Stumpf et al's methods,

please be advised

on the cost of dispensing
with water volume reflectance.
index continued


 
4SM demonstration:

40 times faster than best ALLUT process on the same CASI image.