Remote sensing for shallow bathymetry: A systematic review

Abstract

Shallow bathymetric mapping is important for navigation safety and geomorphologic, hydrologic and oceanographic research. However, field measurements and shipborne sonar are inefficient and dangerous to operate in shallow-water areas. In recent years, owing to its high efficiency, non-contact, and repeated observation benefits, remotely sensed bathymetry has grown quickly and is now being explored in depth. Spectral, photo, laser, and wave-derived bathymetry are among the common methods, which use platforms such as satellites, aircraft, and drones, and sensors such as optical cameras, lasers, and radars. These techniques provide bathymetry for shallow seas, rivers, lakes, and reservoirs. However, existing reviews are either outdated or cover just one aspect of bathymetry; a systematic review is needed. In this study, a bibliometric analysis of peer-reviewed research papers retrieved from the Scopus database was conducted. Based on this analysis, we further summarize the current methods, platforms, sensors, and applications in remote sensing bathymetry, and present our perspectives. Our results indicate that satellite-derived bathymetry is the current focus of this subject, while emerging drones generate higher-resolution bathymetric data. In addition, spectrally derived bathymetry is widely implemented in shallow waters, and laser bathymetry is highly accurate, while wave-derived bathymetry is an effective supplement for existing optical methods in coastal waters. Meanwhile, water penetrating radar, tethered sonar, and satellite altimetry are widely used for inland water bathymetry. However, single bathymetric approaches have their own limitations and typical physical/empirical models are often unable to accurately retrieve water depths in complicated situations. Therefore, remote sensing-based shallow-water bathymetry is moving towards data-driven modeling and multi-source coupling.