Airborne Lidar bathymetry (ALB) is a modern measurement technology for obtaining rapid depth measurements in shallow underwater environments. The technique allows recording of the depth below the Secchi disk. ALB datasets are suitable for nearshore coastal mapping purposes, including the determination of submerged morphological bedforms and coastal protection structures. This article presents a novel methodological approach to understand and assess the suitability of ALB for the automatic classification and mapping of the seabed.

Human expansion into coastal areas and their intensive use for economic and recreational purposes require information on their state, evolution and functioning. Effective management of the coastal zone, making full use of its resources while ensuring the safety of people living in it, makes it crucial to monitor and map this zone, which is challenging from a technical and logistical point of view.

Shallow coastal mapping

Coastal mapping is one of the fundamental tools supporting coastal engineering. It is an important element in monitoring and assessing the condition of the shore and the coast and makes it possible to identify the areas that are most sensitive to erosion. Therefore, it enables the effective and economical management of coastal protection. In the case of protected shores, surveying makes it possible to verify the functionality and efficiency of the reinforcement applied, which further contributes to the improvement of engineering practice.

Bathymetric Lidar measurements can provide capability for the measurement of shallow coastal areas. Compared to acoustic systems, they allow for much faster surveys in shallow areas at a lower cost. A bathymetric laser scanner uses a green (532nm) beam to register the depth below the water surface. Compared to topographic scanners, this is characterized by higher power and lower laser pulse frequencies, due to the longer return time of the reflected echo beam.

Figure 1: The study site and its location in Europe. Location of particular research areas N1–N4 (natural polygons) and A1–A2 (areas modified by anthropogenic pressure). Basemap: OpenStreetMap.

The identification and classification of seabed geomorphology from remote sensing datasets can be performed manually, automatically or semi-automatically. Manual mapping is laborious and time-consuming and requires expertise by preferably one interpreter. Therefore, this study proposes a method for automatic mapping of the shallow seafloor based on ALB datasets for the Southern Baltic.