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Open AccessArticle

Mapping Topobathymetry in a Shallow Tidal Environment Using Low-Cost Technology

Departamento de Geografía y Turismo, Universidad Nacional del Sur (UNS), Bahía Blanca B8000, Argentina
Instituto Argentino de Oceanografía (UNS-CONICET), Bahía Blanca B8000, Argentina
Departamento de Ingeniería Eléctrica y de Computadoras, UNS, Bahía Blanca B8000, Argentina
Departamento Geología, UNS, Bahía Blanca B8000, Argentina
Author to whom correspondence should be addressed.
Remote Sens. 2020, 12(9), 1394;
Received: 30 March 2020 / Revised: 19 April 2020 / Accepted: 22 April 2020 / Published: 28 April 2020
(This article belongs to the Special Issue Remote Sensing of Estuarine, Lagoon and Delta Environments)
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. View Full-Text
Keywords: topobathymetry; shallow tidal environment; unmanned platforms; hydrogeomorphic zones topobathymetry; shallow tidal environment; unmanned platforms; hydrogeomorphic zones
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MDPI and ACS Style

Genchi, S.A.; Vitale, A.J.; Perillo, G.M.E.; Seitz, C.; Delrieux, C.A. Mapping Topobathymetry in a Shallow Tidal Environment Using Low-Cost Technology. Remote Sens. 2020, 12, 1394.

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