Landsat 8 at La Paz, Mexico
HICO at LSI, Bahamas
4SM vs ALUT
4SM vs DigitalGlobe
From raw data to bottom typing:
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
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
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
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.
|4SM demonstration: |
40 times faster than best ALLUT process on the same CASI image.
|Albert & Mobley's analytical model (2003) is used commercially by EOMAP and PROTEUS. |
For operational purpose, we need a way out:
the simplified shallow water Radiative Transfer Equation.
These BOA models require formal atmospheric correction.
Following Lyzenga, Maritorena, Jerlov and Kirk,
passive optical bathymetry is operational and practical
| "operates" the simplified shallow water RTE. |
Being a "ratio method", it works for TOA radiance as well.
| 4SM only uses the satellite image: no atmospheric correction or field data required. |
Yields both retrieved depth and water column corrected spectral radiance,
ready for bottom typing.
This is a TOA simplified RTE:
it uses DNs, does not require formal atmospheric correction.
No need for field data to retrieve depth in meters
just determine Ki/Kj for wavelengths i and j (Lyzenga),
then derive spectral K in m-1 for all visible bands (Kirk).
|Oct 2016: a time series of Landsat 8 MULTI+PAN scenes at SanLorenzoChannel, Baja California||read more|
|Oct 2016: a time series of Landsat 8 MULTI+PAN scenes at LSI, Bahamas||read more|
|Jul 2016: a time series of Landsat 8 MULTI+PAN scenes at Caicos, Bahamas||read more|
|May 2016: a Landsat 8 MULTI+PAN scene at La Parguera, Puerto Rico||read more|
|Feb 2016: a WV2 MULTI+PAN scene at Gulf of Laganas, Greece||read more|
|Mar 2015: a PAN-sharpened QB scene at Shiraho Reef, Japan||read more|
|Jan 2015: HICO data||read more|
|Sep 2014: generic optical calibration of the Panchromatic band||read more|
|May 2014: 4SM demonstration using CASI data at Heron Island||read more|
|May 2014: ETM over Florida Bay: water types from Coastal4 to OIB||read more|
|Feb 2014: HYPERION data at La Parguera Nature Reserve, Puerto Rico||read more|
|Feb 2014: further to Lyzenga's method, and how 4SM adds to it||read more|
|Jan 2014: Landsat 8 MULTI+PAN at Dry Tortugas National Park, Florida keys, USA, with seatruth LIDAR DTM||read more|
|Dec 2013: CASI data at Heron Island, GBR, Australia, with seatruth DTM||read more|
Nov 2013: the "PANchromatic solution" for shallow water column correction using 4SM
|Nov 2013: water volume reflectance and reflectance of the brightest shallow substrates in coral reeef||read more|