Bathymetry and water column correction
at Andros Bank, Bahamas
7671*7841, 30 m pixel size, UTM zone 18
scene LC80120442013202LGN00, July 21rst 2013. Image courtesy of the U.S. Geological Survey
Work done november 2013
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

This is end spring in the Bahamas: lots of greeneries.
Sun light is plentyfull.

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
The data
Optical calibration

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
The atmosphere in this image
is very thick


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

Glint regression based on NIR band
Deglinted TCC
  • Please note the distinct negative bopttom contrast  between waypoints 2 and 3 along Red Profile
  • With Laswir1 =Lswswir1 at ~10 under the cloud shadows, it is seen that the atmosphere in this scene exhibits a lot of aerosols
Deglinting of
PURPLE and SWIR1 bands
  along Profile Red
  • Please note the pronounced and steady increase of the signal in the SWIR1 band from West to East: "deglinting"  removes it efficiently
  • The atmospheric path radiance is set at 17 in the SWIR1 band: this is observed under could shadows, while the lowest sea-surface signal under sun illumination is 10 DNs stronger.
    • this must be accomodated in the optical calibration!
  • The negative bottom contrast in the Purple band is quite pronounced between waypoints 2 and 3 along Red Profile

Optical calibration
Water type OIB of Jerlov
Spectral reflectance of the brightest bottoms:
0.390 0.470 0.527 0.541 0.589 0.690 0.290
on the scale 0-1, as calibrated using the _MTL.txt textfile

Calibration diagram
for bands Blue, Green, Red and NIR

Calibration diagram
for bands Blue, Green, Pan and Red
Operational wavelengths
Here again
  • the wavelength for the Red band must be set at a very low value: WLred=600 nm
  • the wavelength for the Purple band must be set at a very high value: WLpurple=470 nm
  • the wavelength for the Blue and Green bands are set at mid-waveband
The use of Hydrolight code should provide an insight into this question.
                 Operational wavelengths
  • I suspect that this is all-important aspect  (for a "NoNeed or field data" method) very much depends on the bi-directional properties of the light field
    • because stuffy atmospheres deliver very high levels of very diffuse illumination
    • this is most often the case in the Gulf of Arabs (Emirates)
  • As a result, very low diffuse attenuation coefficients are observed under very high levels of very diffuse illumination (whitish skyes),  while Jerlov's diffuse attenuation data assume clear dep-blue skies
  • As a consequence, under such illumination conditions, record shallow water penetrations are observed, which exceed by large the perfomance we can expect from using Jerlov's data.