Feature based image processing methods applied to bathymetric measurements from airborne remote sensing in fluvial environments

TLDR

Bathymetric maps from remotely sensed imagery are common, yet in fluvial settings scene changes and illumination variations undermine empirical depth–colour calibration. The authors correct illumination with feature‑based image processing to identify near‑zero depth areas, which are then incorporated into depth–colour calibration to improve predictions. The automated method yields 4 m² spatial resolution with ±15 cm precision, enabling broader bathymetric mapping. © 2006 John Wiley & Sons, Ltd.

Abstract

Abstract 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. Copyright © 2006 John Wiley & Sons, Ltd.