In this paper, the state-of-the-art concerning new methodologies for surveying in coastal areas in order to obtain an efficient quantification of submerged and emerged environments is described and evaluated. This work integrates an interdisciplinary approach involving both geomatics and robotics and focuses on definition, implementation, and development of a methodology to execute integrated aerial and underwater survey campaigns in shallow water areas. A preliminary test was performed at Gorzente Lakes near Genoa (Italy), to develop and integrate different survey techniques, enabling working in a smarter way, reducing costs and increasing safety for the operators. In this context, Remote Sensing techniques were integrated with a UAV (Unmanned Aerial Vehicle) carrying an aerial optical sensor for photogrammetry and with an ASV (Autonomous Surface Vehicle) expressly addressed to work in extremely shallow water with underwater acoustic sensors (single echo sounder). The obtained continuous seamless DSM (Digital Surface Model) for the entire environment was reconstructed by the combination of different sensing systems by limiting reliance on the GNSS (Global Navigation Satellite System) support. The obtained DSM was displayed in a 3D model leading to the evaluation of the water flow volume and rendering of 3D visualization.

Conventional methodologies often struggle in accurately positioning underwater habitats and elucidating the complex interactions between terrestrial and aquatic environments. This study proposes an innovative methodology to bridge the gap between these domains, enabling integrated 3D mapping and underwater positioning. The method integrates UAV (Uncrewed Aerial Vehicles) photogrammetry for terrestrial areas with underwater photogrammetry performed by a snorkeler. The innovative aspect of the proposed approach relies on detecting the snorkeler positions on orthorectified images as an alternative to the use of GNSS (Global Navigation Satellite System) positioning, thanks to an image processing tool. Underwater camera positions are estimated through precise time synchronization with the UAV frames, producing a georeferenced 3D model that seamlessly joins terrestrial and submerged landscapes. This facilitates the understanding of the spatial context of objects on the seabed and presents a cost-effective and comprehensive tool for 3D coastal mapping, useful for coastal management to support coastal resilience.