Confidence Measure of the Shallow-Water Bathymetry Map Obtained through the Fusion of Lidar and Multiband Image Data

Abstract

With the advancement of Lidar technology, bottom depth (H) of optically shallow waters (OSW) can be measured accurately with an airborne or space-borne Lidar system (HLidar hereafter), but this data product consists of a line format, rather than the desired charts or maps, particularly when the Lidar system is on a satellite. Meanwhile, radiometric measurements from multiband imagers can also be used to infer H (Himager hereafter) of OSW with variable accuracy, though a map of bottom depth can be obtained. It is logical and advantageous to use the two data sources from collocated measurements to generate a more accurate bathymetry map of OSW, where usually image-specific empirical algorithms are developed and applied. Here, after an overview of both the empirical and semianalytical algorithms for the estimation of H from multiband imagers, we emphasize that the uncertainty of Himager varies spatially, although it is straightforward to draw regressions between HLidar and radiometric data for the generation of Himager. Further, we present a prototype system to map the confidence of Himager pixel-wise, which has been lacking until today in the practices of passive remote sensing of bathymetry. We advocate the generation of a confidence measure in parallel with Himager, which is important and urgent for broad user communities.