Multibeam Echo Research Articles

Source and propagation modelling scenarios for environmental impact assessment: Model verificationa).

Evaluation of possible effects of underwater sound on aquatic life requires quantification of the sound field. A marine sound source and propagation modelling workshop took place in June 2022, whose objectives were to facilitate the evaluation of source and propagation models and to identify relevant metrics for environmental impact assessment. The scope of the workshop included model verification (model-model comparison) and model validation (model-measurement comparison) for multiple sources, including airguns, a low-frequency multi-beam echo sounder, and a surface vessel. Several verification scenarios were specified for the workshop; these are described herein.

Underwater Mapping and Optimization Based on Multibeam Echo Sounders

Multibeam echo sounders (MBESs) enable extensive underwater environment exploration. However, due to weak correlation between adjacent multibeam sonar data and difficulties in inter-frame feature matching, the resulting underwater mapping accuracy frequently falls short of the desired level. To address this issue, this study presents the development of a multibeam data processing system, which includes functionalities for sonar parameter configuration, data storage, and point cloud conversion. Subsequently, an Iterative Extended Kalman Filter (iEKF) algorithm is employed for odometry estimation, facilitating the initial construction of the point cloud map. To further enhance mapping accuracy, we utilize the Generalized Iterative Closest Point (GICP) algorithm for point cloud registration, effectively merging point cloud data collected at different times from the same location. Finally, real-world lake experiments demonstrate that our method achieves an Absolute Trajectory Error (ATE) of 15.10 m and an average local point cloud registration error of 0.97 m. Furthermore, we conduct measurements on various types of artificial targets. The experimental results indicate that the average location error of the targets calculated by our method is 4.62 m, which meets the accuracy requirements for underwater target exploration.

Long-term geomorphic effects of longitudinal training walls in the Grand River, Michigan (USA)

The Grand River is the longest river in Michigan, flowing from northwest Hillsdale County to Lake Michigan, and draining an area over 14,400 km2. Bathymetric surveys of a ~ 38 km reach of the river from Grand Rapids to the confluence with Bass River, performed in 1906, were uncovered in the Grand Rapids Community Archives and Research Center in 2014. These maps show depth recordings across the channel along cross sections spaced ~90 m apart. The maps also show the location of numerous training walls that were built in the river in the 1890's as an effort to maintain navigation. The 1906 maps were georeferenced, and the bathymetric data were digitized, converted to bed elevation, and interpolated into an elevation model of the channel bed. High-resolution multibeam echo sounding surveys were conducted in June 2019 and 2020 over the same reach and provided a means to assess over 100-years of geomorphic changes. The results from these analyses showed substantial changes to the average channel width and width variability, with some locations narrowing by up to 50 % (~90 m). Volumetric difference maps between 1906 and 2020 revealed a streamwise spatial variation in the net erosion and deposition, with upstream reaches being predominantly erosional and downstream reaches exhibiting net deposition, with the transition occurring close to the extent of backwater influence from Lake Michigan. The presence of the training walls also resulted in the development of many mid-channel islands and narrowing of the channel through floodplain accretion. Findings from this study have implications for river management projects that have been proposed for the Grand River, as well as other rivers where these structures might be implemented.

Geohazard features of the Northern Sardinia

ABSTRACT The maps of the geohazard-related features of the North Sardinia continental margin produced by the Magic project (MArine Geohazard along Italian Coasts) are here presented. The maps were created on the base of morphobathymetric data obtained by with multibeam echo sounders. ThreCoNISMa, DSCG Università degli studi di Cagliari, Cittadella Universitaria Monserrato - S.P. Monserrato-Sestu, Monserrato (CA), Italye wide canyon systems, Castelsardo to the west, Lavezzi and Caprera to the east, originate from the continental shelf between the islands of Sardinia and Corsica and run toward the Sardinia Sea and the Tyrrhenian Sea, respectively. The canyons feature very wide and articulated heads, meandered sections of the main axis. The continental shelfhosts several coastal lithotomies, genetically related to late Quaternary sea-level oscillation and coastline migration. Furthermore, in the Bonifacio Strait, several bedform fields testify to the present-day activity of strong bottom currents. The main geohazard potential from the North Sardinia is related to the retreating of Castelsardo canyon heads, in offshore of Castelsardo and Asinara, which cuts the continental shelf reaching a few kilometers from the coast.

Enhanced Multi-Beam Echo Sounder Simulation through Distance-Aided and Height-Aided Sound Ray Marching Algorithms

The study proposes two innovative algorithms in the field of multi-beam echo sounder (MBES) simulation: distance-aided sound ray marching (DASRM) and height-aided sound ray marching (HASRM). These algorithms aim to enhance the efficiency and accuracy of MBES simulations, particularly when dealing with long-distance propagation and real-time processing limitations. DASRM addresses issues related to simulation accuracy by efficiently utilizing the KD-tree for spatial indexing and intersection detection instead of the signed distance field (SDF). Building upon the further analysis of DASRM, HASRM is proposed, which improves the search strategy for ray intersections and utilizes a height field pyramid for sampling and retrieval, thereby reducing memory usage while enhancing indexing efficiency. The experimental results demonstrate that both algorithms significantly outperform traditional methods in terms of simulation time, with HASRM exhibiting particular advantages in parallel computing due to its data structure and improved strategies. Additionally, DASRM is well suited for applications requiring complex scene construction, while HASRM proves especially effective in simulating MBES with a focus on underwater terrain due to its effectiveness in handling large incident angles and long-distance propagation.

Geohazard features of the western Sardinia

ABSTRACT The Maps of Geohazard features of the Western Sardinia produced by the Magic project (MArine Geohazard along Italian Coasts) were presented. The maps were created using morphobathymetric data obtained by surveying with a multi-beam echo sounder. The main potential geo-hazards on the western Sardinian margin are related with the presence of three pockmark fields which include hundreds of elements from few meters to several hundred meters in diameter. The pockmark fields are located ∼25–35 km off the coastline and at more than 400 m depth.

Exploration of hydrothermal venting sites using deep-towed multibeam echosounder data

The Federal Institute for Geosciences and Natural Resources (BGR) obtained a contract for the exploration of polymetallic sulphides from the International Seabed Authority (ISA) in an area of 10,000 km2 located in the southwestern Indian Ocean. Since obtaining this contract of exploration in 2015, BGR has conducted annual research cruises to this area and continuously improves the exploration methods for seafloor sulphides deposits. One of the main instruments is HOMESIDE, a deep-towed multibeam echo sounder (MBES) sled. Its water column data allows to visualize and therefore locate discharge sites of hydrothermal fluid – active hydrothermal venting sites (or commonly also referred to as “black smokers”). Additionally, its bathymetric data is used for geological mapping and therefore greater analysis of the seafloor geomorphology. HOMESIDE is typically towed at an altitude of about 100 m above the seabed in a water depth of approximately 3,000 m, allowing a resolution of the derived digital terrain model (DTM) of 2 m. Due to malfunction of individual positioning sensors or operational errors, the navigation data might need to be further corrected in post-processing. Navigation offsets between adjacent lines are mostly apparent in overlapping swath data. The tool mbnavadjust of the open-source software MB-System showed to be a valuable tool to improve the data quality subsequently in areas with data overlap and systematic navigation offsets. Data mismatches of more than 10 m are processed with this tool and can, therefore, be reduced significantly. In this paper, firstly, the role of deep-towed MBES as exploration tool for hydrothermal sites is presented. Secondly, the importance of post-processing MBES navigation based on the swath data especially for this project is highlighted. The workflow as well as the results are presented and show significant improvement.

Unlock insights from hydrographic data with GeoAI

Hydrographic offices are collecting hundreds of terabytes of data every day. This information not only comes from bathymetry data sensors, but also from weather stations, radar, ships, satellites, aerial and drone imagery, and other sensors. With all this data pouring in, hydrographic offices need to be able to automate time consuming processes and adopt modern technologies. One such technology is GeoAI, the intersection of spatial data and artificial intelligence. GeoAI can be considered an enabling technology, in that it allows you collect the data once and apply different algorithms to the data for it to be for multiple purposes. Data collected from multibeam echo sounders can be analyzed to update ENCs by finding new obstructions such as rocks and shipwrecks. Using that same point cloud, GeoAI can then be used to understand marine animal habitat by identifying underwater structures and seafloor patterns that lead to increased biodiversity. GeoAI can be used to aid in coastal resilience projects by analyzing aerial imagery from drones captured in multiple seasons and years for change detection, highlight the areas that need the most attention. Machine Learning, a part of the GeoAI portfolio, can additionally use that same imagery data set to run predictive analytics, highlighting areas that are susceptible to erosion, flooding, and landslides. Many of the same GeoAI algorithms can be used to help maximize investments in the blue economy by bringing location intelligence to the decision-making process. Models can predict the best locations to establish aquaculture, Marine Protected Areas, and offshore energy production. In addition to its applications in coastal resilience projects and maximizing investments in the blue economy, GeoAI offers a wide array of benefits in the domain of hydrospatial data management. The integration of GeoAI in hydrographic offices revolutionizes the way hydrographic data is processed and utilized. Traditionally, processing and interpreting vast amounts of hydrospatial data, including bathymetry, weather, radar, and imagery, required extensive human resources and time-consuming manual efforts. However, with GeoAI, these offices can automate complex tasks and streamline data analysis, significantly improving efficiency and accuracy.

REVIEW OF MODERN BATHYMETRIC SURVEY TECHNIQUES AND THEIR IMPACT ON OFFSHORE ENERGY DEVELOPMENT

This paper presents a comprehensive review of modern bathymetric survey techniques and their impact on offshore energy development. Bathymetric surveys play a crucial role in mapping the seafloor and are essential for various offshore activities, including oil and gas exploration, renewable energy development, and submarine cable installation. The review synthesizes recent advancements in bathymetric surveying technologies, focusing on their role in improving the exploration and monitoring of offshore energy resources. The first section of the paper provides an overview of traditional bathymetric survey methods, such as single-beam and multi-beam echo sounders, which have been widely used for mapping the seafloor. The limitations of these methods, including limited coverage and resolution, are discussed, highlighting the need for more advanced techniques. The second section of the paper discusses the recent advancements in bathymetric survey technologies, such as airborne lidar, satellite-derived bathymetry, and unmanned surface vehicles (USVs). These technologies offer significant improvements in terms of coverage, resolution, and efficiency compared to traditional methods. For example, airborne lidar can provide high-resolution bathymetric data over large areas, making it ideal for rapid seafloor mapping in offshore energy exploration. The third section of the paper examines the impact of these advancements on offshore energy development. Improved bathymetric surveying techniques enable more accurate mapping of the seafloor, which is crucial for identifying suitable locations for offshore energy infrastructure, such as oil and gas platforms, wind farms, and wave energy converters. Furthermore, these techniques facilitate the monitoring of underwater structures and environmental changes, helping to ensure the safe and sustainable operation of offshore energy facilities. In conclusion, modern bathymetric survey techniques have revolutionized offshore energy development by providing more accurate, efficient, and cost-effective methods for mapping the seafloor. These advancements are essential for meeting the growing demand for offshore energy resources while minimizing environmental impact and ensuring operational safety.
 Keywords: Modern Bathymetric, Survey Techniques, Impact, Offshore Energy, Development.

Monitoring and risk assessment of Taoyuan ponds using an unmanned surface vehicle with multibeam echo sounder, ground-penetrating radar, and electrical resistivity tomography

Ponds are a unique agricultural irrigation method with a long history in the Taoyuan area. However, most of them lack accurate spatial information, such as water depth, water surface area, and effective water storage capacity. In this study, the water depth of pond was measured using an unmanned surface vehicle, which has the advantage of being able to operate in shallow waters and in areas that are inaccessible to manned boats. The results show that it can rapidly provide 3D point cloud and an underwater 50 cm gridded digital elevation model with an accuracy of 6.7 cm, which can be used to identify structural defects at the pond bed and the embankment and to accurately estimate the water surface area and effective water storage capacity. The nests with diameters of 30 to 70 cm dug by male tilapia to attract female tilapia for spawning can also be found. In addition, the ground-penetrating radar and electrical resistivity tomography were carried out to successfully investigate the electricity-related properties of the internal structure of the embankment and the leakage locations of pond. In conjunction with the maintenance experience of the Taoyuan Management Office, a risk reference index was proposed for the safety management.

Implementation of the split-beam function to Mills cross multibeam echo sounder for target strength measurements

Abstract Modern challenges in the increasing exploitation of aquatic ecosystems require efficient, reliable, and noninvasive technologies to acquire biomass information on a large scale. For the past 40 years, hydroacoustics has been an essential tool to analyse fish populations and their relationship with the environment. Currently, split-beam echo sounders are standard tools used to reliably and accurately record data in oceans, estuaries, and lakes. To maximize the coverage volume and to increase target detection, and therefore data quality, the use of multi-beam echo sounders is a real asset. We propose here an innovative method for target strength (TS) calculation based on the signal from a reversible Mills cross multi-beam sonar, SeapiX (Exail), which also includes the analytical capability of a split-beam echo sounder. This innovative approach provides new original information when using a multi-beam sonar. The case study in Lake Bourget was based on a comparison of the simultaneous recordings of SeapiX and EK80 (SIMRAD) to prove the validity of this multi split-beam processing, as well as to estimate the in situ TS of fish.

Application of Polynomial Interpolation for Iterative Complementation of the Missing Nodes in a Regular Network of Squares Used for the Construction of a Digital Terrain Model

Due to the continuous increase in the volume of spatially located information, the current requirements imposed on the Spatial Information System (SIS) concern increasing data mining capabilities. Modern measurement systems, based on devices which enable the automatic recording of observation results on a mass scale (LiDAR—Light Detection and Ranging, MBES—Multi Beam Echo Sounder, etc.), allow for a very large volume of information on the surface to be measured and acquired in a relatively short time. One of the methods to reduce the volume of data enabling the generation of a model surface is to convert unevenly distributed measurement points into a regular network of squares (GRID). However, the generation of a complete grid is not always possible. In the measurement spectrum, there may be areas where measurement points have not been recorded. Measurement points can also be eliminated by either filtering the erroneously recorded data or eliminating the measured vegetation or the utilities in the area. To address these problems, the current article proposes a method for complementing the missing internal nodes in a regular network of squares using polynomial interpolation algorithms. Moreover, the paper demonstrates the possibilities of using the presented method for adding additional points between the already existing nodes of the network of squares. The application of the methodology presented in this article enables the effective elimination of (or a reduction in) the gaps in the GRID structure, which, in turn, allows such a network of squares to be used to generate a more accurate Digital Terrain Model.

A Dual Robust Strategy for Removing Outliers in Multi-Beam Sounding to Improve Seabed Terrain Quality Estimation.

During the process of seabed terrain exploration using a multi-beam echo system, it is inevitable to obtain a sounding set containing anomalous points. Conventional methods for eliminating outliers are unable to reduce the disruption caused by outliers over the whole dataset. Furthermore, incomplete consideration is given to the terrain complexity, error magnitude, and outlier distribution. In order to achieve both a high-precision terrain quality estimate and quick detection of depth anomalies, this study suggests a dual robust technique. Firstly, a robust polyhedral function is utilized to solve anomaly detection for large errors. Secondly, the robust kriging algorithm is used for refined outlier removal. Ultimately, the process of dual detection and anomaly removal is achieved. The experimental results demonstrate that DRS technology has the most favorable mean square error and error fluctuation range in the test set, with values of 0.8321 and [-2.0582, 1.9209], respectively, when compared to RPF, WT, GF, and WLS-SVM schemes. Furthermore, DRS is able to adjust to various terrain complexities, discrete distribution features, and cluster outlier detection, as shown by objective indicators and visual outcome maps, guaranteeing a high-quality seabed terrain estimate.

Benthic habitat sediments mapping in coral reef area using amalgamation of multi-source and multi-modal remote sensing data

Scientific management of coral reefs is a global research topic due to their latent economic value and ecological significance. This research benefits from optical and acoustic remote sensing technology with high spatial resolution, sufficient coverage, and stable repeatability. However, each sensor with its own set of limitations, such as insufficient penetration ability, limited sensor resolution and range, which often hinder their applications in the precise classification of coral reef habitats. To address these issues, a novel scheme integrating airborne laser bathymetry (ALB), multibeam echo sounder (MBES) and the multispectral image is designed to serve large-scale and high-precision coral reef habitat sediments research. This scheme focuses on valuable attribute mining, inconsistent coverage, feature default, and redundancy according to multi-source data used in engineering demands. After per-system pretreating, numerous properties, including band, waveform, intensity, terrain, and derivative characteristics, are extracted and quantitatively analyzed to be responsible for habitat description. Subsequently, a complete seabed terrain is generated using the LightGBM regression model to establish the conversion relationship between satellite images and depth. Eventually, a new benthic habitat sediments classification method called RF-SAPSO-LightGBM is introduced with a powerful generalization ability. The unique functions of automatic default feature completion and optimal parameter search improve the discrimination ability of complex sediments. The results indicate that the new method outperforms five other approaches in sediment classification accuracy, and the combination of multi-source data provides more extensive coverage and higher accuracy with an overall of 87. 9%. In comparison, the accuracy values for multispectral image and terrain data alone are 74.5% and 54.7% respectively.

Subsidence of Artificial Reefs with Bamboo Foundations on a Soft Seabed

The design of artificial reefs must be based on the criteria of both durability and serviceability. In this respect, the seabed subsidence rate related to the weight of the reefs and of their foundation system should be limited. The horizontal drift of the reefs during their life should be small too. In this study, pertaining to the behavior of artificial reefs made of microsilica concrete and realized with foundations in bamboo near the international airport of Hong Kong, 1-year monitoring data and calculations of reef foundation settlements are shown and discussed to assess the performance of the adopted mixed foundation and to deduce the nature of the long-term subsidence. The subsidence related to the settlements of the foundations was monitored using a Multibeam Echo Sounder System. It was found that the observed subsidence rate cannot be justified by the primary consolidation of the soils forming the seabed. Indeed, secondary consolidation seems to play an important role. Overall, after one year of service, the artificial reefs are considered to be effective in terms of limitation of both subsidence and drift.

Active Pose - Autonomous Hole-Filling Techniques for 3D Surface Reconstruction in Underwater Exploration

Underwater exploration and related research face significant challenges, including incomplete data collections and the high cost of operations. An underwater robot's capacity to independently identify, target, and address gaps in 3D surface data, termed as ‘holes’, during a mission has the potential to significantly lower the expenses associated with research endeavors, such as those in underwater archaeology or subsea monitoring, and to improve sea surface mapping for autonomous robots. This study introduces a novel approach that combines the boundary-edge of a triangle mesh with Principal Component Analysis (PCA) to actively gather incomplete data. We propose two distinct techniques for active hole-filling, as well as a method to determine the most appropriate strategy. We introduce the flying-over and following-rail approaches to automatically determine new sensor positions for collecting additional point cloud data, which are then used to reconstruct the surface and fill the gaps. Experiments were conducted using both simulated underwater images with ORB-SLAM3 (Campos et al. (2021)) and real-world Multibeam Echo Sounder data.

Dense Neural Network for Classification of Seafloor Sediment using Backscatter Mosaic Feature

Water transportation plays a vital role in global economic activities, facilitating more than 85% of international trade and serving as a cost-effective and essential means to fulfill the demand for goods and services. Similarly, the Benoa Port, situated in the southern part of Denpasar City, operates in the same manner. By utilizing Multibeam Echo Sounder (MBES) backscatter data, backscatter mosaics can be generated to identify various seafloor sediment types, which consist of rock fragments, minerals, and organic materials. The characteristics of these sediments, such as grain size, density, composition, and others, can be observed. To improve the classification of sediments, the integration of backscatter data and backscatter features, such as ASM (Angular Second Moment), Energy, Contrast, and Correlation, can be employed. Supervised classification models like Dense Neural Network (DNN) can be utilized to accurately determine the types of seafloor sediments. The application of DNN modeling resulted in a training accuracy rate of 88% and a testing accuracy rate of 100%. The accuracy results delineated six distinct sediment types. Notably, sandy silt exhibited the highest distribution, accounting for 49.30%, whereas soft clayey silt registered the lowest distribution at 0.53%, as determined by their respective spatial prevalence.

Results of the multibeam echo sounder observations on the GB21-2,3 cruises (around Tokara Islands)

Results of the multibeam echo sounder observations on the GB21-2,3 cruises (around Tokara Islands)

Detailed Bathymetry and Seafloor Backscatter Image Dataset for Monitoring Ecosystem Environment: Southern Ulleungdo

We obtained a detailed bathymetry dataset using multi-beam echo sounder around Neunggeol located at Southern part in Ulleungdo. The survey period was from September 1, 2019 and the bathymetry survey was carried out by RV Jangmok No2 of Korea Institute of Ocean Science and Technology. The instrument equipment used for the survey were Kongsbergs’s EM2040 (multi-beam echo sounder). The detailed bathymetry of the study area shows gradually depth change from about 4 to 190 m. The study area has relatively gentle slopes from the coast to 25 m and below about 125 m in depth, but a steep slope from about 25 to 125 m. The rocky bottom zones identified from detailed bathymetry and backscattered seafloor images are distributed in the northeastern sea of the coastal area, the central sea, and around Neunggeol. In particular, Neunggeol and the near large outcropping rock are tumulus-like submarine landforms, forming big vertical walls. The submarine cable buried between Ulleungdo and the Korean mainland appears in the northern seafloor of the survey area. Stopper stones and gravels sediment are distributed around it. The rocky bottom zone has a strong and irregular reflection intensity in the seafloor backscattered image and the sandy sediment zone has a relatively weak reflection intensity and a uniform pattern, so the two zones are well divided. We classified the sediment zones into fine-grained sediments, sandy sediments, and gravel-like sediments by using the different reflection intensities due to differences in sediment particle size in the seafloor image. Detailed bathymetry and seafloor backscattered image dataset around Neunggeol can be used as a basic data for habitat environment mapping.

Archaeological Exploration, Excavation, and Analysis for a Richer Interpretation of the Past Chola Heritage City- Poompuhar

The article deals with the process of collecting underwater data from the historical area in South India and explicitly showcasing its ancient civilization. Various methods are used to investigate the environmental and structural variables that regulate the coastal structures. Geostatistical interpolation is a technique to predict the values of a spatially continuous bathymetry or depth of a submerged shoreline from a few sample data measurements. The bathymetric investigation of the submerged region surrounding the ancient port of Poompuhar consists of numerous processes conducted in stages. The survey was carried out with the use of an integrated measuring system developed by the National Institute of Technology, Chennai, which included various levels of Multi Beam Echo Sounder (MBES), GPS, sonar, and ROV. To discover continuous surfaces required for analyzing the morphology of the bottom of submerged Poompuhar, a suitable interpolation technique must be used to get estimated values in regions that were not physically surveyed. Bathymetric and topographic data, which typically are gathered independently for various purposes, were included in the spatial data used for elevation surface modeling. Data is gathered in multiple forms with varying resolutions and accuracy; as a result, a standard surface model that will allow for quick and accurate analysis is currently lacking. The major purpose of this study was to create a high-accuracy model of a coastal area's surface using input data from numerous sources. ArcGIS is a popular software platform for analyzing and visualizing geographic data, and it contains several geostatistical interpolation techniques. The research involves the erosion of the shoreline as well as the rise in water level. The study uncovered new scientific and methodological information on Poompuhar's bathymetric properties and submerged surface.