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We used airborne hyperspectral images to generate a dense survey of bathymetric data in the Bahía Blanca estuary (Buenos Aires Province, Argentina). This estuarine area is characterized by intense sediment transport turning the water muddy, and thus optical bathymetric estimations are difficult. We used 24 spectral bands in a range of 500-900 nm acquired with a hyperspectral camera aboard an unmanned aerial vehicle, together with 100 bathymetry data points surveyed with a sonar sensor aboard an unmanned surface vehicle, covering an area of about 800 m2. Random-forest and support-vector-machine regressors were trained with this data set. The resulting model yielded a determination coefficient of 0.815 with unseen data, a root-mean-square error of 0.166 m, and an absolute average error less than 2%. These results allow dense and accurate reconstructions of the underwater profile in wide, muddy, shallow regions of the Bahía Blanca estuary, showing the feasibility of hyperspectral imagery combined with sonar data in turbid shallow waters. [ABSTRACT FROM AUTHOR]

Detailed knowledge of nearshore topography and bathymetry is required for a wide variety of purposes, including ecosystem protection, coastal management, and flood and erosion monitoring and research, among others. Both topography and bathymetry are usually studied separately; however, many scientific questions and challenges require an integrated approach. LiDAR technology is often the preferred data source for the generation of topobathymetric models, but because of its high cost, it is necessary to exploit other data sources. In this regard, the main goal of this study was to present a methodological proposal to generate a topobathymetric model, using low-cost unmanned platforms (unmanned aerial vehicle and unmanned surface vessel) in a very shallow/shallow and turbid tidal environment (Bahía Blanca estuary, Argentina). Moreover, a cross-analysis of the topobathymetric and the tide level data was conducted, to provide a classification of hydrogeomorphic zones. As a main result, a continuous terrain model was built, with a spatial resolution of approximately 0.08 m (topography) and 0.50 m (bathymetry). Concerning the structure from motion-derived topography, the accuracy gave a root mean square error of 0.09 m for the vertical plane. The best interpolated bathymetry (inverse distance weighting method), which was aligned to the topography (as reference), showed a root mean square error of 0.18 m (in average) and a mean absolute error of 0.05 m. The final topobathymetric model showed an adequate representation of the terrain, making it well suited for examining many landforms. This study helps to confirm the potential for remote sensing of shallow tidal environments by demonstrating how the data source heterogeneity can be exploited. [ABSTRACT FROM AUTHOR]