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lyzenga maritorena water column correction pasive, multispectral hyperspectral shallow bathymetry optical bathymetry shallow depth satellite image marine remote sensing bottom typing habitat reflectance  glint correction  coastal managment  diffuse attenuation coefficient  empirical casi  landsat  etm  tm  world view 2  wv2, ikonos  hyperion  ali panchromatic 
takapoto tarawa marakei manihi kauehi sanaa kanehoe 
  tanzania sabah davies reef 
Optical calibration, bathymetry,
water column correction
and bottom typing of shallow marine areas
using passive remote sensing imageries

the Self-calibrated Supervised Spectral Shallow-sea Modeler
for shallow water column correction and bottom typing.

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


Breaking news May 2nd 2014:
4SM demonstration
40 times faster than best ALUT process
on the same image

dubai kauai seychelles poivre island saint lucia mahone bay janvrin tracady bay agay porquerolles menton cap martin
  PANCHROMATIC   
lee stocking  bahmas  heron island  gbr  great barrier reef  caicos bank scott reef   greenland  clipperton  hawaii ohau jamaica negril french polynesia  tuamotu usvi buck island reef  new caledonia cockburn  marmion geraldton abrolhos princess cays eleuthera florida keys bahrain gezirat siyul red sea la parguera dry tortugas whitsunday andros shark bay marawaah rangiroa tikehau tarawa alacranes chinchorro gubal bora bora moorea zirku ras hatibah
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.

Ron/Yann


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
   and  

On the cost of dispensing with water volume reflectance

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.

 
 


 
Panchromatic  CASI
WV2  OLI  HYPERION
4SM vs ALUT
4SM vs DigitalGlobe

From raw data to bottom typing:
it works
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