Depth is an essential characteristic of flood inundation in hydro-ecological research. Several studies have tried to estimate inundation depth from remotely sensed image and digital elevation model (DEM) data by applying a series of cross section profiles along the centerline of a river reach. This method requires a large amount of manual work in order to identify the centerlines and cross sections, which makes them both unsuitable for automation and inefficient for mapping.
This study presents a methodology of rapidly generating flood inundation depth maps automatically using a combination of remotely sensed inundation extent and a high resolution DEM. The proposed approach is tested in a study area located in the Murray-Darling Basin in Australia, and has been proved to be feasible and reliable.