Maritime infrastructure such as quay walls, bridges, locks, and waterfront structures is essential for transportation and logistics. Many of these assets are several decades old and require regular condition assessments to ensure their safety, functionality, and long-term availability. A major challenge is that a significant portion of these structures is located below the waterline, making comprehensive inspections difficult using conventional methods. As a result, infrastructure managers often lack complete and consistent information about the actual condition of their assets.

This presentation introduces an integrated surveying workflow that combines hydrographic and engineering surveying techniques to create a seamless digital representation of infrastructure above and below the waterline. Underwater geometry is captured using high-resolution multibeam echosounder technology, while kinematic laser scanning and photogrammetry provide detailed 3D information and photorealistic surface models of the exposed structure. The fusion of these complementary datasets results in a georeferenced digital twin covering the entire asset.

Beyond data acquisition, the presentation demonstrates how modern data processing and artificial intelligence transform raw survey data into actionable information. Machine-learning algorithms are applied to sonar point clouds to detect geometric anomalies such as deformations or displaced structural elements, while deep-learning approaches identify surface defects including cracks, spalling, and corrosion from high-resolution imagery. By combining geometric and semantic information, detected defects can be accurately localized and evaluated within the three-dimensional model.

The resulting datasets are managed within a cloud-based platform that integrates point clouds, textured meshes, panoramic imagery, inspection findings, and historical information into a single environment. This digital workflow enables efficient collaboration between surveyors, engineers, infrastructure owners, and asset managers while providing a reliable basis for maintenance planning, condition monitoring, and long-term asset management.

Using practical examples from maritime infrastructure projects, the presentation illustrates how integrated surveying above and below the waterline bridges the gap between hydrography, engineering surveying, and digital asset management. The presented workflow demonstrates how high-resolution 3D reality capture, AI-supported analysis, and cloud-based data management contribute to more objective inspections, improved decision-making, and sustainable lifecycle management of critical infrastructure.

Der Mittelrhein ist ein besonders anspruchsvoller Abschnitt der Bundeswasserstraße Rhein. Zur Sicherung der Leichtigkeit und Sicherheit der Binnenschifffahrt sowie zur Untersuchung möglicher Engstellenbeseitigungen wird ein Digitales Geländemodell des Wasserlaufs (DGM-W) erstellt. Der Vortrag zeigt, wie Daten aus bathymetrischem und konventionellem Airborne Laserscanning, terrestrischem Laserscanning sowie hydroakustischer Erfassung zu einem einheitlichen Geländemodell zusammengeführt werden.