Bathymetric maps produced from remotely sensed imagery are increasingly
common. However, when this method is applied to fluvial environments,
changing scenes and illumination variations severely hinder the
application of well established empirical calibration methods used to
obtain predictive depth-colour relationships. In this paper,
illumination variations are corrected with feature based image
processing, which is used to identify areas in an image with a
near-zero water depth. This information can then be included in the
depth-colour calibration process, which results in an improved
prediction quality. The end product is an automated bathymetric mapping
method capable of a 4 m(2) spatial resolution with a precision of 15
cm, which allows for a more widespread application of bathymetric
mapping.