Automated Derivation of Bathymetric Information from Multi-Spectral Satellite Imagery Using a Non-Linear Inversion Model

Abstract

Most previous studies utilized a log-linear regression model to invert multi-spectral images into bathymetric data. Based on the Levenberg-Marquardt optimization algorithm, we developed an automated method for calibrating the parameters for a non-linear inversion model. Our method has been successfully applied to an IKONOS multispectral image. We compared depth data derived from our model to those estimated using a conventional log-linear inversion model. Bathymetric data derived from the non-linear inversion model are slightly more accurate and stable, particularly for deeper benthic habitats, than those derived from a conventional log-linear model although their overall performances are very similar.

Keywords:

• Water depth
• inversion
• IKONOS
• optimization
• Levenberg-Marquardt method

Acknowledgements

This research is funded by the NOAA Sea Grant Program #NA16RG1078 and Norman Hackerman Advanced Research Program 010366-0017-2007.