Remote sensing of river bathymetry for use in hydraulic model prediction of flood inundation

Many studies have been carried out for bathymetry mapping based on remotely sensed imagery coupled with ancillary datasets. Most of the techniques that have been developed are mainly used for shallow and clear water rivers, while deep, turbulent and highly suspended sediment rivers have received little attention in terms of developing new techniques. The aims of this study were (i) to predict a bathymetry map by remote sensing and (ii) to map flood extent for the River Kelantan, Malaysia using a hydraulic model based on the bathymetry map. Firstly, a regression model was fitted to the relation between river depth and a SPOT satellite sensor image. The results showed a large correlation between river depth and the green band. Secondly, an image processing technique (i.e. density slicing) was applied to the SPOT image to classify river water depth and thus produce a map of bathymetry. A hydraulic model (HECRAS) was then used to predict flood inundation extent and the result compared to flood extent predicted from a RADARSAT image. The accuracy assessment was applied to identify spatial variation in the error between three areas (i.e. upstream, midstream and downstream).