Optical calibration, bathymetry, water column correction and bottom typing of shallow marine areas, using passive remote sensing imageries
Bathymetry and water column correction
at Caicos Bank, Bahamas
4018*4149, 30 m pixel size, UTM zone 18, downloaded from USGS
Using the Panchromatic band for water column correction
to derive water depth and spectral bottom signature:

Landsat 8 OLIP bandset used for this work

Purple_1Blue_2Green_3PAN_4Red_5NIR_6 and SWIR1_7

Please refer to Bora Bora and Sanaa
for use of the PANchromatic band for water column correction

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
scene LC80090452013133LGN01   May 13th 2013
Work done august 2013
The data
Optical calibration
Calibration of the Panchromatic band
Modeling: breaking new ground
Retrieved depth
DTM seatruth RMSE=0.74m

Bottom reflectance

DTM sea truth: 
RMSE=0.52 m for the whole image
No need for field data
Tide height 0.9 m 
2K is correct for the Blue and Green bands
This DTM gives me a valuable opportunituy

Seatruth regression
Z4SM vs ZDTM+0.9m
RMSE=0.52 m
Tide correction applied: 0.9 m

Difference ZDTM+0.9 - Z4SM
Tide correction applied: 0.9 m

see legend

4SM retrieved depth

see legend

DTM by Harris-Ellis
resampled to 30 m GSD and scaled to centimeters

see legend


The data
Seven bands are used: Purple, Blue, Green, PAN, Red, NIR and SWIR1

Panchromatic band, sum-aggregated to 30 m,
exhibits excellent radiometric quality

Landsat OLI exhibits excellent radiometric quality



Glint regression based on SWIR1 band
SWIR1 is quite convenient for deglinting

Glint regression based on NIR band

Deglinted TCC
Deglinting is far from perfect:

I need to dig harder:
  • lots of clouds,
  • lots of surface glitter
Deglinting along Profile Red

Bottom detection by OLI's red band
Deglinted Red band


Red band at 655 nm
in this image exhibits bottom detection
in excess of 10 m,
as evidenced using BILKO's field dataset
  • This means that operational Kred for remote sensing radiance is distinctly lower in this scene than diffuse attenuation coefficient for downwelling irradiance Kdred of Jerlov.
  • Either we need to shift WLred at an operational wavelength much shorter than mid-waveband, which would only reach down to ~6 m over very bright bottoms.
    • I suppose sensor designers would object loudly!
  • Or , as I realized using HYPERION in 2014, operational  2Kred  for remote sensing radiance is affected by viewing geometrical conditions and/or atmospheric optical properties.
    • I suppose HYDROLIGHT designers would agree loudly!
  • See comment by Jerlov.


 Optical calibration
is under tight control, thank to the optimization process:
Water type OIB+0.7 of Jerlov
Spectral reflectance of the brightest bottoms:
0.272 0.343 0.439 0.462 0.548 0.678 0.634
on the scale 0-1, as calibrated using the _MTL.txt textfile

Calibration diagram
for bands Blue, Green, Red and NIR
[2] vs [3]: excellent fit
of GREEN against BLUE

Calibration diagram
for bands Coastal, Blue, PAN and Red
[1&2] vs [4]: excellent fit 
of  COASTAL and BLUE against PAN

Calibration diagram
for bands Blue, PAN, Red and NIR
[2] vs [4]: excellent fit
of PAN band against the BLUE

Calibration diagram
2K for Coastal band must be increased
for bands Coastal, Blue, Green and Red
[1&2] vs [3]: excellent fit
of  COASTAL and BLUE against GREEN
Rw: water volume reflectance
    0.018 0.017 0.003 0.001 0.000 0.000 0.000
Ra: path radiance
0.106 0.076 0.042 0.037 0.023 0.011 0.003

Spectral operational 2K
  • This calibration yields the following:
2Kblue  =0.104 m-1
2Kgreen=0.190 m-1
2Kred    =0.637 m-1 well below pure water at 655 nm!
2Knir ~=0.45 m-1 is a customary for NIR
  • Final_Z = CoefZ*Z -Tide_to_chart_datum
    • I hope that CoefZ=1.00!
  • The effective diffuse attenuation coefficient of the PAN band decreases  progressively
  • from very high values at shallow depths
  • to much lower values at depth
  • It is necessary to account for it in the optical calibration of the PAN band in a very precise way, based on the Landsat 8 PAN response curve


Modeling: breaking new ground
Using the PAN band is a great step forward for water column correction.

Yellow: modeling by bands 1, 2 and 3 against 4
Green:  modeling by bands 1     and 2 against 3
For a comparison, we also show the more general case,
which takes advantage of the whole visible range.

Yellow: modeling by bands 1, 2  and 3 against 4
Green:  modeling by bands 1      and 2 against 3


Water column correction

Performance of the PAN band reaches ~20 m over bright bottoms in this OIB water type of Jerlov

4SM retrieved depth

see legend

of water column corrected bottom reflectance
rosy hues: possibly some "whiting"

PAN solution and RED solution

This plot compares Z4 vs Z5
along Profile Red
  • Z4 uses Purple, Blue, Green against PAN
  • Z5 uses Purple, Blue, Green, and PAN against RED
Deglinting and Smart-Smoothing applied

GREEN solution and PAN solution

This plot compares Z3 vs Z4
along Profile Red
  • Z4 uses Purple, Blue, Green against PAN
  • Z3 uses Purple, Blue against Green
Deglinting and Smart-Smoothing applied
  • Waypoints A1 and B1: the RED solution underestimates the retrieved depth where some "whiting" or suspended particle load comes into play
    • at waypoints A1 and B1
  • Waypoint A2: the PAN solution appears to underestimate retrieved depth over very dark bottoms
    • see waypoint A2
  • Waypoint A2:   the GREEN solution appears to underestimate even more badly the retrieved depth over very dark bottoms
    • see waypoint A2


Bottom typing

As of august 2016, 4SM operates a generic bottom typing protocol,
based on the spectral angle mapping.

SAM classified image
Now that water column corrected radiances
are converted to BOA spectral reflectances,
bottom typing is performed in a generic way,
which is applicable in 4SM 
to any Landsat 8 or WV2 image

Then BOA bottom type signatures
can be extracted using the SA-classified image

SAM classified image zoom
TCC BOA deglinted zoom

The calibration is optimized
so as to achieve a "flat" bottom type signature
for the brightest bottom type in this scene.
This involves a very fine-tuning
of the -LsM... parameter