Klasifikasi Jenis dan Sebaran Sedimen Menggunakan Data Multibeam Echosounder Multi-Temporal di Alur Pelayaran Barat dan Timur Surabaya

Pelabuhan Tanjung Perak Surabaya merupakan salah satu pelabuhan utama di Indonesia yang memiliki peran penting dalam transportasi laut Indonesia. Survei batimetri rutin diperlukan untuk mengidentifikasi kedalaman alur akses pelabuhan dan kondisi sedimentasi yang terjadi. Kondisi sedimen dapat dikarakterisasi berdasarkan sifat alaminya: ukuran butir, berat jenis, kecepatan jatuh, komposisi, porositas, bentuk, dll. Kondisi sedimen juga dapat dikarakterisasi berdasarkan nilai hamburan balik sonar, menggunakan instrumen Multibeam Echosounder (MBES) . Data mentah nilai hamburan balik kemudian dikoreksi dengan mengadopsi persamaan regangan kontras linier ke kisaran tertentu. Data masukan penelitian ini diukur menggunakan ODOM MB2 dengan instrumen Applanix oleh The Surabaya Navigational District (DISNAV) pada bulan Februari 2019 (Lokasi 2) dan Oktober 2018 (Lokasi 1) untuk alur akses barat Surabaya (APBS) dan Agustus 2017 ( Lokasi 3) untuk jalur akses timur Surabaya (APTS). Uji kualitas data batimetri dilakukan dengan mengikuti IHO S-44 2008 untuk spesifikasi pesanan khusus. Hasil penelitian menunjukkan bahwa data batimetri memiliki akurasi yang baik pada lokasi 1, 2, dan 3 dengan nilai 0,0862; 0,1317; dan 0,1072. Hubungan antara tipe sedimen dan hamburan balik menunjukkan bahwa tipe sedimen pasir memberikan hamburan balik yang kuat. Semakin kecil nilai hamburan balik maka jenis sedimennya semakin lunak. Klasifikasi di APBS dan APTS menunjukkan bahwa di APBS terdiri dari empat jenis sedimen (lempung, lanau lempung, lanau berpasir, dan pasir) sedangkan di APTS hanya terdapat tiga jenis sedimen (lanau lempung, lanau berpasir, dan pasir).

Determination of the relevant multibeam echosounder frequency to estimate the suspended sediment concentrations for environmental damage monitoring of mass movement

The problem of environmental damages in the river area can transform the morphology and threaten the ecosystem in it with one of the causes being natural factors such as suspended sediment. Retracing the medium form is fluid, the common instrument to determine the condition of the area is a sound wave-based instrument such as a multibeam echosounder. Considering the improvement of multibeam echosounder which can acquire areas using many frequencies at one time, noted as multi-frequency multibeam echosounder, now its application can reach various fields including environmental monitoring. Factors that can be considered in its practice include time efficiency, cost, and notably the accuracy of the data result. By converting the results of the acquisition into an estimate of the concentration of suspended sediment and integrating the results from several frequencies, it will be established the applicable frequency usage. It was concluded that a multibeam echosounder with a frequency of 450 kHz was recommended in a case study to determine the concentration of suspended sediment. This is supported by a correlation value of 89.18% or a very high correlation.

Seagrass habitat suitability model for Redang Marine Park using multibeam echosounder data: Testing different spatial resolutions and analysis window sizes

Integrating Multibeam Echosounder (MBES) data (bathymetry and backscatter) and underwater video technology allows scientists to study marine habitats. However, use of such data in modeling suitable seagrass habitats in Malaysian coastal waters is still limited. This study tested multiple spatial resolutions (1 and 50 m) and analysis window sizes (3 × 3, 9 × 9, and 21 × 21 cells) probably suitable for seagrass-habitat relationships in Redang Marine Park, Terengganu, Malaysia. A maximum entropy algorithm was applied, using 12 bathymetric and backscatter predictors to develop a total of 6 seagrass habitat suitability models. The results indicated that both fine and coarse spatial resolution datasets could produce models with high accuracy (>90%). However, the models derived from the coarser resolution dataset displayed inconsistent habitat suitability maps for different analysis window sizes. In contrast, habitat models derived from the fine resolution dataset exhibited similar habitat distribution patterns for three different analysis window sizes. Bathymetry was found to be the most influential predictor in all the models. The backscatter predictors, such as angular range analysis inversion parameters (characterization and grain size), gray-level co-occurrence texture predictors, and backscatter intensity levels, were more important for coarse resolution models. Areas of highest habitat suitability for seagrass were predicted to be in shallower (<20 m) waters and scattered between fringing reefs (east to south). Some fragmented, highly suitable habitats were also identified in the shallower (<20 m) areas in the northwest of the prediction models and scattered between fringing reefs. This study highlighted the importance of investigating the suitable spatial resolution and analysis window size of predictors from MBES for modeling suitable seagrass habitats. The findings provide important insight on the use of remote acoustic sonar data to study and map seagrass distribution in Malaysia coastal water.

Physics-Based Modelling and Simulation of Multibeam Echosounder Perception for Autonomous Underwater Manipulation

One of the key distinguishing aspects of underwater manipulation tasks is the perception challenges of the ocean environment, including turbidity, backscatter, and lighting effects. Consequently, underwater perception often relies on sonar-based measurements to estimate the vehicle’s state and surroundings, either standalone or in concert with other sensing modalities, to support the perception necessary to plan and control manipulation tasks. Simulation of the multibeam echosounder, while not a substitute for in-water testing, is a critical capability for developing manipulation strategies in the complex and variable ocean environment. Although several approaches exist in the literature to simulate synthetic sonar images, the methods in the robotics community typically use image processing and video rendering software to comply with real-time execution requirements. In addition to a lack of physics-based interaction model between sound and the scene of interest, several basic properties are absent in these rendered sonar images–notably the coherent imaging system and coherent speckle that cause distortion of the object geometry in the sonar image. To address this deficiency, we present a physics-based multibeam echosounder simulation method to capture these fundamental aspects of sonar perception. A point-based scattering model is implemented to calculate the acoustic interaction between the target and the environment. This is a simplified representation of target scattering but can produce realistic coherent image speckle and the correct point spread function. The results demonstrate that this multibeam echosounder simulator generates qualitatively realistic images with high efficiency to provide the sonar image and the physical time series signal data. This synthetic sonar data is a key enabler for developing, testing, and evaluating autonomous underwater manipulation strategies that use sonar as a component of perception.

Spatial Analysis of Beaked Whale Foraging During Two 12 kHz Multibeam Echosounder Surveys

To add to the growing information about the effect of multibeam echosounder (MBES) operation on marine mammals, a study was conducted to assess the spatial foraging effort of Cuvier’s beaked whales during two MBES surveys conducted in January of 2017 and 2019 off of San Clemente Island, California. The MBES surveys took place on the Southern California Antisubmarine Warfare Range (SOAR), which contains an array of 89 hydrophones covering an area of approximately 1800 km2 over which foraging beaked whales were detected. A spatial autocorrelation analysis of foraging effort was conducted using the Moran’s I (global) and the Getis-Ord Gi∗ (local) statistics, to understand the animals’ spatial use of the entire SOAR, as well as smaller areas, respectively, within the SOAR Before, During, and After the two MBES surveys. In both years, the global Moran’s I statistic suggested significant spatial clustering of foraging events on the SOAR during all analysis periods (Before, During, and After). In addition, a Kruskal-Wallis (comparison) test of both years revealed that the number of foraging events across analysis periods were similar within a given year. In 2017, the local Getis-Ord Gi∗ analysis identified hot spots of foraging activity in the same general area of the SOAR during all analysis periods. This local result, in combination with the global and comparison results of 2017, suggest there was no obvious period-related change detected in foraging effort associated with the 2017 MBES survey at the resolution measurable with the hydrophone array. In 2019, the foraging hot spot area shifted from the southernmost corner of the SOAR Before, to the center During, and was split between the two locations After the MBES survey. Due to the pattern of period-related spatial change identified in 2019, and the lack of change detected in 2017, it was unclear whether the change detected in 2019 was a result of MBES activity or some other environmental factor. Nonetheless, the results strongly suggest that the level of detected foraging during either MBES survey did not change, and most of the foraging effort remained in the historically well-utilized foraging locations of Cuvier’s beaked whales on the SOAR.

The Importance of Under-Keel Sound Velocity Sensor in Measuring Water Depth with Multibeam Echosounder

The basic and most commonly used application of modern multibeam echosounders (MBES) is the bathymetric survey. Surface sound velocity errors introduce errors on beam steering angles and consequently errors in depth and position values. Due to systematic malfunction and troubleshooting of the sound velocity sensor (SVS) on board Polish Navy hydrographic ship Arctowski, attempts to solve the problem were made. All the inspections and cleaning of the sensor were performed with the use of divers or while staying in the shipyard. Diving work did not always bring the expected results and periodic ship docking was quite expensive. The article shows the importance of the SVS sensor in bathymetric measurements using multibeam echosounder. Selected problems of the sensor operation and temporary solutions were presented. The paper provides a description of practical solutions implemented aboard the navy ship Arctowski. The idea and implementation were the result of the author’s experience gained during 18 years of service on board that ship.

Automatic Identification of Internal Wave Characteristics Affecting Bathymetric Measurement Based on Multibeam Echosounder Water Column Data Analysis

The accuracy of multibeam echosounder bathymetric measurement depends on the accuracy of the data of the sound speed layers within the water column. This is necessary for the correct modeling of ray bending. It is assumed that the sound speed layers are horizontal and static, according to the sound speed profile traditionally used in the depth calculation. In fact, the boundaries between varying water masses can be curved and oscillate. It is difficult to assess the parameters of these movements based on the sparse sampling of sound velocity profiles (SVP) collected through a survey; thus, alternative or augmented methods are needed to obtain information about water mass stratification for the time of a particular ping or a series of pings. The process of water column data collection and analysis is presented in this paper. The proposed method updates the sound speed profile by the automated detection of varying water mass boundaries, giving the option to adjust the SVP for each beam separately. This can increase the overall accuracy of a bathymetric survey and provide additional oceanographic data about the study area.