Passive optical remote sensing of Congo River bathymetry using Landsat
Abstract:
Methods of estimating bathymetry using remotely sensed datasets have been used extensively for coastal regions and now more recently have been demonstrated as feasible for optically shallow rivers. Previous river bathymetry studies have focused on shallow rivers and have generally used aerial imagery with a finer spatial resolution than Landsat. While the Congo River has relatively low suspended sediment concentration values the application of passive bathymetry estimation to a river of this scale has not been attempted before.
Three different analysis methods are tested in this study: 1) a single band algorithm; 2) a log ratio method; and 3) a linear transform method. All three methods require depth data for calibration and in this study area bathymetry measurements are available for three cross-sections resulting in approximately 300 in-situ measurements of depth, which are used in the calibration and validation.
The performance of each method is assessed, allowing the feasibility of passive depth measurement in the Congo River to be determined. Considering the scarcity of in-situ bathymetry measurements on the Congo River, even an approximate estimate of depths from these methods will be of considerable value in its hydraulic characterisation.
