La Parguera, Puerto Rico
a time series of images, couryesy of US Geological Survey, and of OSU
with LIDAR DTM from NOAA


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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
 
So
I keep digging
until suitable data
become available
 
Please refer to
"Deriving Bathymetry from Multispectral Remote Sensing Data",
William J. Hernandez and Roy A. Armstrong , J. Mar. Sci. Eng. 2016, 4(1)
Habitat composition and coverage mapping in La Parguera, Puerto Rico, using AVIRIS and IKONOS imagery,  Ramon Lopez Rosado
  "REMOTE SENSING OF BENTHIC HABITATS IN SOUTHWESTERN PUERTO RICO"
JEANNETTE ARCE ARCE, UNIVERSITY OF PUERTO RICO, MAYAGUEZ CAMPUS, 2005



 
LIDAR data reveals that this is a success for 4SM,
although vast expanses are affected by turbid waters
  • it demonstrates that
    • no need for field data, although the LIDAR data helped me a lot in deciphering this case
    • the generic optical calibration of the PAN band works fine
  • good depth retrievals down to 25 m,
    • subject to minor adjustment of the deep water radiance
    • using Kblue/Kgreen with wavelengths WLblue and WLgreen at mid-waveband
    • so that: no need for field data:   CoefZ=1.0
With a DTM at hand, 
I can decide which operational practices in 4SM should be ruled out, 
and which are confirmed
These scenes are NOT worthy of shallow water work, apart from isolated  ROIs
Another nice case for "semi-analytical" methods to show their superiority: see DigitalGlobe and EOMAP
But I note that Hernandez's 2016 PhD work
  • was done in 2014-2016 at UPRM, home of Prof. Roy Armstrong and Dr James Goodman
  • resorted to not so "analytical" or physical ways, in favor of mathematical ways
  • required a select/suitable formal atmospheric correction
  • required/used an existing LIDAR coverage for its calibration
    • using a simple Blue/Green band ratio (not using Coastal?)
  • focused precisely, and commented only, on the very area where 4SM obtained its best results: ROI5 
  • produced a "depth-invariant" index of bottom brightness in place of a real spectral water column correction
  • and finaly did not use the Panchromatic band of WV2 imagery
  • HYPERION....................... ....August..............15th......2002   work feb  2014
  • HYPERION...........................January............13th......2003   work feb  2014
  • LANDSAT 8...........................June.................18th......2013   work feb  2014
  • LANDSAT 8...**....................December....27th 2013   work may 2016
  • LANDSAT 8...****.................October........30th 2015   work may 2016
  • HICO.................****.............September.... .26th..2013  work april 2016



 
With a DTM at hand, I can decide 
which operational practices in 4SM should be ruled out
and which are worth investigating further

I've done my best to try and make sense of these images under 4SM,
using Landsat 8 and Hyperion images: NO WAY!
Looks like there is a curse on La Parguera!


with NOAA's LIDAR seatruth dataset    PR_BATHY_4M_Mean_NNresample

 


 
This scene is marred by heterogeneous waters, under the dual influence of
coastal pollution from lands masses, rivers and cities
 and west-bound flow of very clear oceanic waters from the Sargasso Sea.
See original image



From "Geologic maps of the southwestern Puerto Rico Parguera to Guanica insular shelf"
Jack Morelock, Elizabeth A. Winget, and Carlos Goenaga