Welcome to the first issue of the 31th volume of The International Hydrographic Review (IHR).

In order to deploy the first layers of S-100 based navigation products in the Baltic Sea, and do so in a regionally harmonized manner, the Hydrographic Offices involved are partnering with academia and industry in the Baltic Sea e-Nav project. To unlock the full potential of the S-100 paradigm shift towards e-navigation, there is a need for transnational collaboration to build capacity and ensure seamless, harmonized products. In addition, the project will test S-100 products from an end-user perspective to ensure the most relevant and useable navigation data possible. The recently started project will continue until 2026 and is co-financed by the EU Interreg Baltic Sea Region programme.

Welcome to the first issue of the 30th volume of The International Hydrographic Review (IHR).

Welcome to the second issue of the 30th volume of The International Hydrographic Review (IHR).

The detection of boulders in hydroacoustic data is essential for a range of environmental, economic and marine planning applications. The manual interpretation of hydroacoustic data for object detection is a non-trivial, tedious and subjective task. Using the conventional means accessible to hydrographic professionals, it is nearly impossible to locate all boulders or rule out their presence for extended areas of interest. Although it has been shown that AI can do the job quickly and reproducibly, earlier work has not progressed beyond scientific experiments. As a result, AI software have not been routinely integrated into the workflows of institutions involved in hydrographic data acquisition and processing, or oceanographic analysis. This paper presents a workflow for fully automated boulder detection in hydroacoustic data. A graphical user interface enables training and evaluation of detection models, boulder detection model execution, and post-processing of detection results without programming. The workflow is demonstrated on data from the southern Baltic Sea. Validation results of the detection for various data inputs include a mAP-50 of 77.83 % for raster images of backscatter intensities based on side-scan sonar, a mAP-50 of 70.46 % for raster images of slope angles based on multibeam echosounder and a mAP-50 of 44.02 % for backscatter and bathymetric data given as 3D point clouds.

A unified Chart Datum for the whole Baltic Sea is required for the use of global navigation satellite systems (GNSS) in accurate 3-D bathymetric surveying and navigation, enabling for automated shipping with increased efficiency and improved maritime safety. So far, the zero levels of nautical maps were derived from the mean sea level (MSL) of different local tide gauges. The inherent height datum differences between neighboring map sheets are a fundamental infrastructural obstacle for implementing and using new cross-border navigation services based on electronic nautical maps. The Baltic Sea Hydrographic Commission, with its Chart Datum, Water Level and Currents Working Group (CDWCWG), has therefore decided to implement a harmonized vertical reference in the Baltic Sea (BSHC18 conference, 2013; Schwabe et al., 2020) called the Baltic Sea Chart Datum 2000 (BSCD2000). The first milestone was the agreement between the Baltic Sea countries on the fundamental standards of the BSCD2000, the general features of its practical realization, and the roadmap for the transition and implementation of the new chart datum (CDWG8, 2016).

As a result of natural processes and human activities, water bodies and in particular the seabed are in a constant state of change. Collecting data on the topography of the seabed for monitoring tasks, coastal protection or to ensure safe navigation is a major challenge. Airborne LiDAR bathymetry is an efficient area-wide method for acquiring seabed topography. However, this measurement method is limited in water depth penetration due to the attenuation of the measurement signal in the water column and water turbidity. Therefore, it is only suitable for bottom detection in shallow water areas. However, recent developments in full-waveform processing techniques allow an increase in the usable portion of the signal waveform, resulting in an improved representation of the seabed. In this contribution, two novel full-waveform processing techniques are evaluated for the first time on a dataset from the German Wadden Sea National Park. In addition, an enhanced water surface correction method is introduced, which accounts for the local sea surface topography with the goal of improving the accuracy potential of the full-waveform stacking processing. The study demonstrates an increase in the analyzable water depth on the order of 26 %. This results in an improved coverage of the seabed in terms of point density and area covered (+ 14.6 %). A comprehensive analysis of the results shows that the additional seabed points represent the seabed well.

Airborne LiDAR bathymetry allows an efficient and area-wide measurement of the water bottom topography in shallow waters. However, the maximum water depth range of this method is mainly limited by water turbidity, resulting in a reduced coverage of the water bottom topography in deeper waters. Water turbidity causes attenuation effects and hampers the reliable detection of water bottom echoes in the digitized full-waveform signal, and consequently, greater water depths are not analyzable by using standard processing methods. To increase the analyzable water depth, an extended full-waveform processing method was developed with the goal of enhancing the reliable extraction and detection of bottom points in deeper waters. This volumetric nonlinear ortho full-waveform stacking approach is based on the combined analysis of information from closely adjacent measurements under the assumption that the water depth is locally steady. Such an approach has the advantage that the influence of sensor noise and erratic non-bottom object echoes is significantly reduced so that weak water bottom echoes are better detectable. The results of the combined analysis were finally applied for water bottom echo detection in individual measurements, thus avoiding smoothing effects. For evaluation purposes, the detected water bottom points were compared with points derived from the standard processing method and with echo sounder measurements. The results of a pilot study in a river with high turbidity showed that the application of the extended full-waveform processing indicate an increase of the analyzable water depth from approximately 1.65 m to approximately 2.20 m, leading to an approximately 210 % increase in the number of detected water bottom points (related to the number of standard processing) and an improved coverage of the water bottom by newly processed points.

Welcome to the second issue of the 29th volume of The International Hydrographic Review (IHR). This year is a jubilee year – not only does it mark the centenary of our publication, celebrated with a special Jubilee issue1 and a presentation at the 3rd Assembly of the International Hydrographic Organization (IHO) in Monaco in May 2023, but it also signifies a remarkable milestone for the General Bathymetric Chart of the Oceans (GEBCO) program. This year, we celebrate GEBCO’s 120 years of ocean discovery!

<p>Sublittoral hard substrates, for example formed by blocks and boulders, are hotspots for marine biodiversity, especially for benthic communities. Knowledge on boulder occurrence is also important for marine and coastal management, including offshore wind parks and safety of navigation. The occurrence of boulders have to be reported by member states to the European Union. Typically, boulders are located by acoustic surveys with multibeam echo sounders and side scan sonars. The manual interpretation of these data is subjective and time consuming. This presentation reports on recent work concerned with the detection of boulders in different acoustic datasets by convolutional neural networks, highlighting current approaches, challenges and future opportunities.</p>

Multibeam bathymetry surveys conducted in highly stratified environments are routinely affected by sound speed errors. The approach proposed here aims to combine measured with synthetic sound speed profiles in order to minimize sound speed errors. The adequacy of synthetic profiles derived from a regional hydrodynamic model and spatiotemporal interpolation is therefore investigated. Ray-tracing comparisons at the 65° launch angle between measured and synthetic profiles demonstrates that the expected depth bias for modeled profiles will be in excess of 1% of water depth. Spatiotemporally interpolating hourly sampled profiles decreases the depth bias up to a factor of three for higher beam angles. Residual sounding depth biases are observed and ascribed to a residual surface sound speed error.

In a two-year research and development project, the prototype of a GNSS (Global Navigation Satellite System) based real-time service using a SSR-RTK (State Space Representation-Real Time Kinematic) approach was developed for the German exclusive economic zone in the North Sea. Because the survey area of the North Sea can only be represented with a heterogeneous distribution of GNSS Continuously Operating Reference Stations, the calculation algorithm and the modelling of the GNSS correction data are particularly important. Maritime measurements in the survey area have confirmed the basic functionality of the prototype through an almost 90% availability of the RTK status fix with initialisation times of less than two minutes. Sea and land measurements as well as a permanent monitoring station were used to demonstrate the quality targets.

Accurate information on turbidity in water bodies is relevant to numerous limnological and oceanological issues. However, the collection of turbidity parameters using conventional in-situ measurement methods is time-consuming and cost-intensive and therefore usually limited to very small study areas. The use of airborne LiDAR bathymetry data is a promising alternative. However, existing methods for deriving turbidity parameters from airborne LiDAR bathymetry data are limited to the determination of one single turbidity parameter per water column element. The paper presents a novel approach that overcomes the existing limitations enables the determination of 3D water turbidity fields. By volumetric data analysis, the vertical turbidity stratification in the water body can be determined. For validation purposes, the approach was applied to synthetic measurement data generated in a simulation as well as a real measurement data set of a shallow coastal water.

Surveying and navigation became much easier, more accurate and operational thanks to the Global Positioning System. The use of this technology in height determination, bathymetry and 3-D navigation is not only limited by the reduced accuracy compared to the horizontal component. It supposes additional information about the geodetic height reference surface in order to leverage the full potential of this technology. The corresponding models, measurements and activities which are necessary to improve this part of the geodetic infrastructure are usually behind the curtain. This article emphasizes the need of a common cross-border geodetic infrastructure and the relevance of precise models of the height reference surface for GNSS-aided height determinations. The need of gravimetric surveys for the determination and improvement of these models is explained. Finally, it gives an overview about the gravimetric surveys which were carried out in the German Exclusive Zone of the North and Baltic Sea over more than one decade and provides some insight into practical aspects and challenges of this kind of surveys.

Airborne LiDAR bathymetry is an efficient technique for surveying the bottom of shallow waters. In addition, the measurement data contain valuable information about the local turbidity conditions in the water body. The extraction of this information requires appropriate evaluation methods examining the decay of the recorded waveform signal. Existing approaches are based on several assumptions concerning the influence of the ALB system on the waveform signal, the extraction of the volume backscatter, and the directional independence of turbidity. The paper presents a novel approach that overcomes the existing limitations using two alternative turbidity estimation methods as well as different variants of further processed full-waveform data. For validation purposes, the approach was applied to a data set of a shallow inland water. The results of the quantitative evaluation show, which method and which data basis is best suited for the derivation of area wide water turbidity information.

Airborne LiDAR bathymetry is an efficient measurement method for area-wide acquisition of water bottom topography in shallow water areas. However, the method has a limited penetration depth into water bodies due to water turbidity. This affects the accuracy and reliability of the determination of water bottom points in waters with high turbidity or larger water depths. Furthermore, the coverage of the water bottom topography is also limited. In this contribution, advanced processing methods are presented with the goal of increasing the evaluable water depth, resulting in an improved coverage of the water bottom by measurement points. The methodology moves away from isolated evaluation of individual signals to a determination of water bottom echoes, taking into account information from closely adjacent measurements, assuming that these have similar or correlated characteristics. The basic idea of the new processing approach is the combination of closely adjacent full-waveform data using full-waveform stacking techniques. In contrast to established waveform stacking techniques, we do not apply averaging, which entails low-pass filtering effects, but a modified majority voting technique. This has the effect of amplification of repeating weak characteristics and an improvement of the signal-noise-ratio. As a consequence, it is possible to detect water bottom points that cannot be detected by standard methods. The results confirm an increased penetration water depth by about 27% with a high reliability of the additionally extracted water bottom points along with a larger coverage of the water bottom topography.

To achieve a geometrically accurate representation of the water bottom, airborne LiDAR bathymetry (ALB) requires the correction of the raw 3D point coordinates due to refraction at the air–water interface, different signal velocity in air and water, and further propagation induced effects. The processing of bathymetric LiDAR data is based on a geometric model of the laser bathymetry pulse propagation describing the complex interactions of laser radiation with the water medium and the water bottom. The model comprises the geometric description of laser ray, water surface, refraction, scattering in the water column, and diffuse bottom reflection. Conventional geometric modeling approaches introduce certain simplifications concerning the water surface, the laser ray, and the bottom reflection. Usually, the local curvature of the water surface and the beam divergence are neglected and the travel path of the outgoing and the returned pulse is assumed to be identical. The deviations between the applied geometric model and the actual laser beam path cause a coordinate offset at the water bottom, which affects the accuracy potential of the measuring method. The paper presents enhanced approaches to geometric modeling which are based on a more accurate representation of water surface geometry and laser ray geometry and take into account the diffuse reflection at the water bottom. The refined geometric modeling results in an improved coordinate accuracy at the water bottom. The impact of the geometric modeling methods on the accuracy of the water bottom points is analyzed in a controlled manner using a laser bathymetry simulator. The findings will contribute to increase the accuracy potential of modern ALB systems.

Airborne Lidar Bathymetry is a laser scanning technique to measure waterbody bottom topography in shallow waterbodies with limited turbidity. The topic has recently gained relevance due to the advent of new sensor technologies allowing for much higher spatial resolution in bathymetry data capture and due to guidelines demanding regular monitoring of waterbodies. In our contribution, we focus on three important aspects of lidar bathymetry: In the first part, systematic effects of wave patterns will be analysed in order to derive waterbody coordinate correction terms. In the second part, we will apply waveform-stacking techniques to enhance the detectability of water bottom points in lidar bathymetry full waveform signals. In the third part, a dedicated full waveform analysis procedure is shown, which allows for deriving turbidity information from the decay of the signal intensity in the waterbody.