Multibeam Echosounder Systems Research Articles

Enhancing Marine Topography Mapping: A Geometrically Optimized Algorithm for Multibeam Echosounder Survey Efficiency and Accuracy

This research introduces a new multibeam survey line model that optimizes geometric relationships to improve the efficiency and accuracy of surveys over complex seabed topographies. Since existing multibeam echosounder systems have limitations in handling complex terrains, this study presents an advanced model to enhance data quality and operational efficiency. By strategically designing survey lines and optimizing coverage strategies, this paper achieves the optimal configuration of survey lines for secondary measurements in marine areas, ensuring high precision and reliability of measurement data. Experimental results show that the new model significantly outperforms existing technologies in terms of effective coverage area and measurement accuracy, with an average coverage rate of over 95%, higher than existing models, and a weighted average overlap rate of 3.18%, greatly improving the economic efficiency of measurements by reducing redundant coverage and minimizing operational costs. These findings confirm the advantages of the new model in practical applications and offer valuable technical support for advancing seabed mapping technology.

Robust algorithm for automatic surface-based outlier detection in MBES point clouds

Bathymetric multibeam echosounder systems (MBES) provide high-resolution mapping of underwater topography but are highly susceptible to errors due to harsh environmental conditions and the measurement process. Traditionally, manual post-processing is required to ensure data quality, a time-consuming, expensive, and subjective task. To address this issue, we propose a surface-based algorithm for pre-processing and cleaning MBES data that reduces manual intervention and improves consistency. A surface-based algorithm models the underwater topography as a surface instead of processing individual points. By assuming a continuous surface for underwater geometry, the algorithm easily identifies observations that deviate significantly from this model. The method combines a hierarchical B-spline surface with iterative robust estimation to automate data cleaning. Preliminary results on example datasets show a balanced outlier detection accuracy of 0.99, with manual processing time reduced from 2 days to just 30 min.

An Interpretable Multi-Model Machine Learning Approach for Spatial Mapping of Deep-Sea Polymetallic Nodule Occurrences

AbstractHigh-resolution mapping of deep-sea polymetallic nodules is needed (a) to understand the reasons behind their patchy distribution, (b) to associate nodule coverage with benthic fauna occurrences, and (c) to enable an accurate resource estimation and mining path planning. This study used an autonomous underwater vehicle to map 37 km2 of a geomorphologically complex site in the Eastern Clarion–Clipperton Fracture Zone. A multibeam echosounder system (MBES) at 400 kHz and a side scan sonar at 230 kHz were used to investigate the nodule backscatter response. More than 30,000 seafloor images were analyzed to obtain the nodule coverage and train five machine learning (ML) algorithms: generalized linear models, generalized additive models, support vector machines, random forests (RFs) and neural networks (NNs). All models ML yielded similar maps of nodule coverage with differences occurring in the range of predicted values, particularly at parts with irregular topography. RFs had the best fit and NNs had the worst spatial transferability. Attention was given to the interpretability of model outputs using variable importance ranking across all models, partial dependence plots and domain knowledge. The nodule coverage is higher on relatively flat seafloor ( < 3°) with eastward-facing slopes. The most important predictor was the MBES backscatter, particularly from incident angles between 25 and 55°. Bathymetry, slope, and slope orientation were important geomorphological predictors. For the first time, at a water depth of 4500 m, orthophoto-mosaics and image-derived digital elevation models with 2-mm and 5-mm spatial resolutions supported the geomorphological analysis, interpretation of polymetallic nodules occurrences, and backscatter response.

Deep-sea benthic structures and substrate types influence the distribution of functional groups in the Wallaby-Zenith Fracture Zone (East Indian Ocean)

Three-dimensional deep-sea structures enhance substrate complexity and can shape numerous ecological hotspots that play critical roles in the diversity and distribution of benthic faunal assemblages. The characteristics of these features are not fully understood due to the logistical challenges of exploring at great depths and remote locations. One such deep-sea feature, the Wallaby-Zenith Fracture Zone (WZFZ) located in the East Indian Ocean, was mapped using a full-ocean depth multibeam echosounder system. Additionally, twelve baited landers and five crewed submersible dives were conducted in water depths between 4709 and 6591 m. We use seafloor bathymetry, bathymetric derivatives and video footage from the submersible dives to characterise the benthic structures, substrate types, habitat diversity, and the distribution of associated functional groups of megafauna for the WZFZ. The Benthic Terrain Modeler toolbox was used as an initial semi-automated step to generate benthic structural classes, which were further characterized through the inclusion of bottom salinity and temperature data collected by the scientific landers and integrated with the observations of seafloor substrate from the submersible video footage. This resulted in identification of nine benthic habitat classes characterised by unique seafloor morphological structure and substrate texture. A polymetallic nodule field, a possible extension of the previously reported Cape Leeuwen nodule field, was also observed along submersible transects conducted on the slopes of the WZFZ. The distribution and diversity of the functional megafauna groups observed are influenced by the deep-sea benthic habitats, defined by seafloor structures and substrate heterogeneity, especially the presence of hard substrates such as outcropping bedrock and polymetallic nodules within the WZFZ.

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.

A study on the prediction model of water column sound absorption coefficients considering the characteristics of the East Sea of South Korea

East Sea of Korea has the deepest water depth among Korean seas, and the water column changes are distinct in space and time, resulting in a wide range of water column sound absorption coefficients. In this study, we calculate and analysis the spatiotemporal variation of water column sound absorption coefficient in the East Sea of Korea, which has unique oceanographic characteristics. Using extensive CTD data from the Korea Oceanographic Data Centre (KODC) from 1991 to 2021, we calculate the sound absorption coefficient using the widely applied Francois–Garrison model and reveal the unique absorption characteristics of the East Sea. The derived coefficients are then used to calibrate and improve past multibeam echosounder system (MBES) data, which suffered from incomplete water column information and arbitrary mean values. To facilitate the calculation and development of sound absorption coefficient, a MATLAB-based graphical user interface (GUI) was developed. The results of this study contribute to the calculation and inference of sound absorption coefficients along spatial and temporal dimensions of the water column in the East Sea and to the extraction of more accurate seafloor information from MBES data. This study developed the way for future research focusing on algorithmic advances and new methodologies for the calculation of sound absorption coefficients in the West and South Seas of Korea.

Method of Time Estimation for the Bathymetric Surveys Conducted with a Multi-Beam Echosounder System

Exact and complete preparation of a hydrographic survey project allows for the avoidance or reduction of additional costs and unexpected delays and, at the same time, increases the efficiency of the survey. One of the essential requirements at the survey planning stage is a calculation of time necessary for performing bathymetric measurements with a multi-beam echosounder. Based on these calculations, many decisions related to the costs and methodology are made. The article presents the method of time estimation for the hydrographic surveys and takes into account many variables that directly affect the final duration of the project. The paper demonstrates the influence of water depth, multi-beam echosounder swath angle, and other planning parameters related to the scheme of survey lines on the total time of stay at sea. The main findings are based on the author’s over twenty years of experience aboard the Polish Navy hydrographic ship Arctowski and include thorough analysis of specialist literature, publications, manuals, and international standards.

Echo grid integration: A novel method for preprocessing multibeam water column data to quantify underwater gas bubble emissions

AbstractWater column imaging multibeam echo sounder systems (MBESs) are a promising technology for quantitative estimates of the gas bubble volume flow within large gas seepage areas. Considerable progress has been made in recent years toward applicable calibration methods for MBESs as well as developing inversion models to convert acoustically measured backscattering cross sections to gas bubble volume flow. However, MBESs are still not commonly used for quantitative gas flow assessments. A reason for this is the absence of published processing methods that demonstrate how MBES data can be processed to quantitatively represent bubble streams. Here, we present a novel method (echo grid integration) that allows for assessing the aggregated backscattering cross section of targets within horizontal water layers. This derived value enables quantifying bubble stream gas flow rates using existing acoustic inversion methods. The presented method is based on averaging geo‐referenced volume backscattering coefficients onto a high‐resolution 3D voxel‐grid. The results are multiplied with the voxel volume to represent measurements of the total backscattering cross‐section within each voxel cell. Individual gridded values cannot be trusted because the beam pattern effects cause the values of individual targets to “smear” over multiple grid‐cells. The true aggregated backscattering cross‐section is thus estimated as the integral over the grid‐cells affected by this smearing. Numerical simulation of MBES data acquisition over known targets assesses the method's validity and quantify it's uncertainty for different, realistic scenarios. The found low measurement bias (< 1%), and dispersion (< 5%) are promising for application in gas flow quantification methods.

Distribution of boulders in coastal waters of Western Pomerania, German Baltic Sea

This study contributes to a better understanding of geogenic reef distribution in the southern Baltic Sea and highlights the implications of survey-related factors on automated boulder classification when utilizing data from multiple surveys. The distribution of hard grounds and reefs is needed as a baseline for geological and biological studies, but also for offshore construction, navigation and coastal management. In this study we provide maps of the distribution of geogenic reefs for about 750 km2 in the southern Baltic Sea, at the sites Wismar Bay, Darss Sill and Plantagenet Ground. The maps are based on full-coverage backscatter surveys with different side scan sonar and multibeam echo sounder systems. The distribution and number of boulders in the backscatter maps was determined using a convolutional neural network combined with quality control by human experts. The extent of the geogenic reefs was calculated on the basis of the number of boulders in 50 m x 50 m grid cells. We compare the results with previous reef maps based on point sampling, which show reefs of either biogenic or geogenic origin. According to the earlier maps, 11% of the Plantagenet Ground seabed was classified as reef habitat type. This is similar to the result of our study (12%), although we only considered reefs of geogenic origin. In the Darss Sill, geogenic reefs are larger in this study than in previous maps (30% versus 23%). In both regions, the spatial distribution of reefs differs significantly between old and new maps. For Wismar Bay, previous maps classify 3% of the seafloor as habitat type reef, whereas this study classifies 35% as geogenic reef. The use of automated classification during seafloor mapping allowed large areas to be interpreted in a few days. It also provided more information on the distribution of boulders within the geogenic reef. However, the boulder distribution maps show the negative effects of survey geometry, frequency and environmental conditions on automated boulder classification when data from different surveys are combined.

Subaqueous Topographic Deformation in Abandoned Delta Lobes—A Case Study in the Yellow River Delta, China

Reduction in river discharge and sediment load has left deltaic lobes in the world’s many river deltas starving, but knowledge of how the subaqueous topography of these abandoned subdeltas responds to environmental changes is limited. In this study, we aimed to determine the long-term dynamics of the subaqueous seabed of abandoned delta lobes to advance current knowledge. As a case study, we selected an abandoned subdelta on the Yellow River Delta of the Bohai Sea, China, for which three-decade long (1984–2017) bathymetric data and long-term river discharge and sediment load records are available. We analyzed the seafloor surface change and quantified the void space from the sea water surface to the seafloor. In addition, we surveyed the seafloor surface with an M80 unmanned surface vehicle carrying a multibeam echo sounder system (MBES) in 2019 to obtain high-resolution microtopography information. We found that a net volume of 5.3 × 108 m3 of sediment was eroded from the study seabed within an area of 3.6 × 108 m2 during 1984–2017. This volumetric quantity is equivalent to 6.89 billion metric tons of sediment, assuming a bulk density of 1.3 t/m3 for the seabed sediment. The seabed erosion from 0 to −5 m, from −5 to −10 m, and below −10 m has showed a similar increasing trend over the past 33 years. These findings suggest that seabed erosion in this abandoned subdelta will very likely continue, and that other abandoned delta lobes in the world may have been experiencing similar seabed erosion due to the interruption of the sediment supply and sea level rise. It is not clear if the seabed erosion of abandoned delta lobes would have any effect on the stability of the coastal shoreline and continental shelf.

Measurement of Scattering Properties of Water Body by Using a Multibeam Echosounder System

We propose a backscattering compensation based procedure to enhance the performance of multibeam echosounder systems (MBESs). High resolution in a wide field of view is the main benefit of MBESs, and this property makes them increasingly important for measuring scattering in water body. The performance of these systems is vulnerable to the anisotropic characteristics of scatterers, and thus, the results provided by MBESs can be inaccurate. To enhance the performance of MBESs, we compensate for the echo data on the basis of backscattering strength. The compensation considers the reflected sound energy by introducing interlayer coefficients calculated from the amounts of energy that penetrate into and are reflected from each layer. To demonstrate the effectiveness of the proposed method, we perform numerical simulations with randomly positioned scatters having anisotropic properties. Furthermore, anechoic pool experiments are conducted using bubbles generated by air compressors and propellers. The after-compensation results reveal richer details, thereby confirming the effectiveness of the proposed method.

Seagrass Habitat Suitability Models using Multibeam Echosounder Data and Multiple Machine Learning Techniques

Seagrass beds are important habitats in the marine environment by providing food and shelter to dugongs and sea turtles. Protection and conservation plans require detail spatial distribution of these habitats such as habitat suitability maps. In this study, machine learning techniques were tested by using Multibeam Echo Sounder System (MBES) and ground truth datasets to produce seagrass habitat suitability models at Redang Marine Park. Five bathymetric predictors and seven backscatter predictors from MBES data were used to representing topography features and sediment types in the study area. Three machine learning algorithms; Maximum Entropy (MaxEnt), Random Forests (RF), and Support Vector Machine (SVM) were tested. The results revealed that MaxEnt and RF models achieved the highest accuracy (93% and 91%, respectively) with SVM produced the lowest (67%). Depth was identified as the most significant predictor for all three models. The contributions of backscatter predictors were more central for SVM model. High accuracy models showed that suitable habitat for seagrass is distributed around shallow water areas (<20 m) and between fringing reef habitats. The findings highlight that acoustic data and machine learning are capable to predict how seagrass beds are spatially distributed which provide important information for managing marine resources.

Habitat variability and faunal zonation at the Ægir Ridge, a canyon-like structure in the deep Norwegian Sea.

The Ægir Ridge System (ARS) is an ancient extinct spreading axis in the Nordic seas extending from the upper slope east of Iceland (∼550 m depth), as part of its Exclusive Economic Zone (EEZ), to a depth of ∼3,800 m in the Norwegian basin. Geomorphologically a rift valley, the ARS has a canyon-like structure that may promote increased diversity and faunal density. The main objective of this study was to characterize benthic habitats and related macro- and megabenthic communities along the ARS, and the influence of water mass variables and depth on them. During the IceAGE3 expedition (Icelandic marine Animals: Genetics and Ecology) on RV Sonne in June 2020, benthic communities of the ARS were surveyed by means of a remotely-operated vehicle (ROV) and epibenthic sledge (EBS). For this purpose, two working areas were selected, including abyssal stations in the northeast and bathyal stations in the southwest of the ARS. Video and still images of the seabed were usedtoqualitatively describebenthic habitats based on the presence of habitat-forming taxa and the physical environment. Patterns of diversity and community composition of the soft-sediment macrofauna, retrieved from the EBS, were analyzed in a semiquantitative manner. These biological data were complemented by producing high-resolution bathymetric maps using the vessel’s multi-beam echosounder system. As suspected, we were able to identify differences in species composition and number of macro- and megafaunal communities associated with a depth gradient. A biological canyon effect became evident in dense aggregates of megafaunal filter feeders and elevated macrofaunal densities. Analysis of videos and still images from the ROV transects also led to the discovery of a number ofVulnerable Marine Ecosystems (VMEs) dominated by sponges and soft corals characteristic of the Arctic region. Directions for future research encompass a more detailed, quantitative study of the megafauna and more coherent sampling over the entire depth range in order to fully capture the diversity of the habitats and biota of the region. The presence of sensitive biogenic habitats, alongside seemingly high biodiversity and naturalness are supportive of ongoing considerations of designating part of the ARS as an “Ecologically and Biologically Significant Area” (EBSA).

AUV Navigation Correction Based on Automated Multibeam Tile Matching.

Ocean science and hydroacoustic seafloor mapping rely on accurate navigation underwater. By exploiting terrain information provided by a multibeam echosounder system, it is possible to significantly improve map quality. This article presents an algorithm capable of improving map quality and accuracy by aligning consecutive pings to tiles that are matched pairwise. A globally consistent solution is calculated from these matches. The proposed method has the potential to be used online in addition to other navigation solutions, but is mainly targeted for post processing. The algorithm was tested using different parameter settings on an AUV and a ship-based dataset. The ship-based dataset is publicly available as a benchmark. The original accurate navigation serving as a ground truth, alongside trajectories that include an artificial drift, are available. This allows quantitative comparisons between algorithms and parameter settings.

Morphodynamic changes in the Yangtze Estuary under the impact of the Three Gorges Dam, estuarine engineering interventions and climate-induced sea level rise

The estuarine turbidity maximum (ETM) in the Yangtze Estuary Delta (YED) is muddy by definition and lacks bottom undulations. However, since 2013, a remarkable change has occurred in the YED. Recent images detected by a multibeam echosounder system, SeaBat 7125, for the first time have confirmed widespread regions of subaqueous dunes in the Yangtze ETM channel. This abnormal change is the result of morphodynamic transformation from the combination of an abrupt decline in sediment supply resulting from the construction of the Three Gorges Dam (TGD) and hydrodynamic changes caused by sea level rise. The latter includes anthropogenic-induced sea level rises (from land subsidence and coastal engineering) of 7–37 cm and a climate-induced sea level rise of 8 cm during the past four decades. Obvious evidence of hydrodynamic changes includes tidal amplification, i.e., a 10–28 cm rise in the tidal range, 42–65 cm rise in the lowest tidal level in the dry season, 45–67 cm rise in the highest tidal level in the flood season and 10–30% increase in the amplitude of the major tidal component. These findings will likely have global implications in formulating strategies to combat the superimposed effects of human interventions and climate change on upstream river and downstream coastal developments.

An Intelligent Detection Method for Different Types of Outliers in Multibeam Bathymetric Point Cloud

Bathymetric Multibeam echo sounder systems (MBESs) are the most effective and reliable way to survey the earth’s seafloor. However, multibeam bathymetric data inevitably contain different types of outliers due to measurement characteristics and complex underwater environments. The traditional automatic approach to eliminate outliers may lead to more than one of the questions of reliability, limitation, and efficiency, respectively. This paper offers an algorithm aiming to detect different types of outliers by considering their characteristic of distribution and distance of them, rapidly. First, a coding octree based on Morton code is built to guarantee perfect efficiency and space division. Second, coarse outlier removal is performed by octree-based voxelized representation of the bathymetric data, and outliers far away from the seafloor will be detected and eliminated by connected component labeling. Third, fine outlier removal is employed to delete outliers connected closely to the seafloor by the improved morphological method based on the combination of the k-d tree and octree. Experimental results show that the proposed algorithm can achieve promising results. The percent of outliers that are detected by the hand-edit method that is regarded as a reference result is 5.06%. 4.70% of points in a total number of 3645541 points are detected in our method. Compared with other classical filtering methods, the intelligent method for detecting different types of the outlier from coarse to fine attains favorable performance in a reasonable time, avoiding over-filtering, and demonstrates high reliability for multibeam bathymetric point cloud.

A Precise Method to Calibrate Dynamic Integration Errors in Shallow- and Deep-Water Multibeam Bathymetric Data

Acoustic remote sensing with multibeam echo-sounder systems (MBESs) has been extensively used for coastal and ocean survey works. The imperfect integration of multibeam echo sounder and motion sensor can introduce integration errors, which manifest as high-frequency wobbles in swaths and hinder the accurate expression of high-resolution seabed topographic maps. To address this issue, a precise method is developed to calibrate these integration errors based on a simplified georeferenced model. First, an equivalent attitude coordinate (EAC) system is defined to represent mutual transformation between equivalent attitudes and the beam launch vector; then, with the help of equivalent attitudes, a simplified footprint georeferenced model is deduced that considers the effect of the parameterized integration errors (including time delay, motion scale, yaw misalignment, and lever arm errors); finally, in a selected flat region, integration errors are inverted by regressing the bathymetric data to the corresponding fitted plane via the differential evolution (DE) algorithm. The results indicate that the proposed method can effectively eliminate wobbles in multibeam bathymetries caused by single or multiple integration errors in both shallow- and deep-water areas. By comparing the data before and after calibration with the <i>in situ</i> measurements, the accuracy of the calibrated shallow- and deep-water data is controlled within approximately 0.15&#x0025; and 0.06&#x0025; of the water depth, respectively.

Testing the Improvement of Coral Reef Associated Fish Distribution Models Based on Multibeam Bathymetry by Adding Seafloor Backscatter Data

Demersal fishes constitute an essential component of the continental shelf ecosystem, and a significant element of fisheries catch around the world. However, collecting distribution and abundance data of demersal fish, necessary for their conservation and management, is usually expensive and logistically complex. The increasing availability of seafloor mapping technologies has led to the opportunity to exploit the strong relationship demersal fish exhibit with seafloor morphology to model their distribution. Multibeam echo-sounder (MBES) systems are a standard method to map seafloor morphology. The amount of acoustic energy reflected by the seafloor (backscatter) is used to estimate specific characteristics of the seafloor, including acoustic hardness and roughness. MBES data including bathymetry and depth derivatives were used to model the distribution of Abalistes stellatus, Gymnocranius grandoculis, Lagocephalus sceleratus, Lethrinus miniatus, Loxodon macrorhinus, Lutjanus sebae, and Scomberomorus queenslandicus. The possible improvement of model accuracy by adding the seafloor backscatter was tested in three different areas of the Ningaloo Marine Park off the west coast of Australia. For the majority of species, depth was a primary variable explaining their distribution in the three study sites. Backscatter was identified to be an important variable in the models, but did not necessarily lead to a significant improvement in the demersal fish distribution models’ accuracy. Possible reasons for this include: the depth and derivatives were capturing the significant changes in the habitat, or the acoustic data collected with a high-frequency MBES were not capturing accurately relevant seafloor characteristics associated with the species distribution. The improvement in the accuracy of the models for certain species using data already available is an encouraging result, which can have a direct impact in our ability to monitor these species.

Effects of nonlinear internal gravity waves on normal-incident reflection measurements of marine sediments

Sonar data acquired by sub-bottom profilers and multi-beam echosounder systems are widely used to estimate geoacoustic properties of marine sediments. However, the uncertainty of the seabed property estimates caused by water column variability may limit the application. In this study, we focus on the acoustic focusing and defocusing effects of nonlinear internal waves on normal-incident reflection measurements in the South China Sea. The field experiment was conducted using a transceiver mooring consisted of a sound source and a four channel vertical hydrophone array. The variation of acoustic signal reflections from sub-bottom layers during three days at the same site is observed. The effects of the nonlinear internal waves passing through the transceiver mooring are identified. The impact on the sub-bottom property estimates is investigated. [Work supported by the Office of Naval Research.]

Characterizing Geomorphology of Mesophotic Coral Reef Ecosystems in the Southwestern Gulf of Mexico: Implications for Conservation and Management

Coral reefs are the most biodiverse ecosystems on earth and are presently experiencing severe declines globally. Shallow coral reef ecosystems (&amp;lt;30 m) have been studied extensively while mesophotic coral ecosystems (MCE) are poorly studied. As a result, MCE are rarely included in marine reserve design and management, despite their ecological importance and connectivity to shallow reefs. In this study, we assessed the fine-scale topographic complexity, a proxy for structural complexity, for a group of coastal coral reefs in a marine park in the southwestern Gulf of Mexico, in depths between 2 and 49 m. We conducted hydrographic surveys using a semi-portable multibeam echosounder system to produce 3D bathymetry digital terrain models (DTM) with a 2.5 m spatial resolution for three submerged bank reefs and two emerging reefs. From these models, descriptive terrain parameters were calculated for each reef, including slope, aspect, curvature, rugosity and ruggedness. Results show that all reefs are predominantly northeast-southwest oriented, with well-defined leeward and windward sides. For the three submerged bank reefs, structural complexity increased with depth. Estimated mean ruggedness and rugosity were highest at 20–40 m depth range on windward side slopes. Emerging reefs showed high structural complexity, particularly at the 25–40 m depth range. We identified a spur and groove zone with maximum ruggedness (0.26) and rugosity (3.17) values, and four channels with steep slopes (68°) and dispersed mounds. We found that at mesophotic depths (&amp;gt;30 m), southern reefs basements from two distinct reefs merge to form a continuous complex. This has important management implications since presently, only 28.7% of this reef complex (mostly shallow areas) are within the existing limits of the marine park’s core zone. Considering the newly recognized importance of MCE, we propose expanding and reshaping the core zone to include the entire reef complex which mostly encompasses MCE with high structural complexity. Our study illustrates the value of semi-portable MBES for marine planning in developing countries and remote poorly studied areas.