Self-calibrated Supervised Spectral Shallow-sea ModelerPassive optical calibration, satellite derived bathymetry, water column correction
and bottom typing of shallow water areas using remote sensing imageries.
Use passive hyperspectral or multispectral satellite images
to retrieve both SDB depth and spectral reflectance of shallow bottom,
ready for bottom typing, ahead of any field work.
And the winner is Uncertainty on depth Empirical vs Analytical
I am developing a 4SM_2K_Jerlov page
4SM workstation 4SM flowchart
home page continued
|July 2017 |
4SM: a Novel Self-calibrated Algebraic Ratio Method
for Satellite Derived Bathymetry and Water Column Correction
|Sept 2017 |
4SM Method Tested in the Gulf of California
Suggests Field Data are Not Needed
to Derive Satellite Bathymetry
In conclusion, the findings suggest that 4SM
is as accurate as the commonly used Stumpf’s method,
the only difference being the independence of 4SM from previous field data,
and the potential to deliver bottom spectral characteristics for further modeling.
4SM thus represents a significant advance in coastal remote sensing potential
to obtain bathymetry and optical properties of the marine bottom.
|A time series of Landsat 8 at La Paz, Baja California |
15 m GSD NO Smoothing required RMSE~=1 m
|Two Landsat 8 time series in the Bahamas |
No need for formal atmospheric correction
No use of field data for optical calibration
Water column corrected signatures calibrated into reflectance (0-1) for OLI and WV2
This also works with PAN-sharpenned images