Single Beam Echosounder Research Articles

Analyzing Depth Uncertainty of Near-Shore Bathymetric Survey Conducted by Single-Beam Echo Sounder

Single-beam echo sounders have gained popularity for various applications due to their compact dimensions, ease of use, and cost-effectiveness. The question that often arises among the users is whether these devices can fulfill the necessary accuracy requirements. This paper concentrates on assessing the accuracy that can be achieved using a single-beam echo sounder. An accuracy assessment was performed by comparing the depths derived from the 3D model created from the single-beam echo sounder data to those obtained through more accurate and independent method (tacheometric surveying) in the test area. Accurate depth determination was achieved through trigonometric leveling, employing a specific methodology that allows for precise depth measurements up to 4.5 meters. The assessment results were compared to the vertical accuracy requirements for surveying and mapping in shallow waters, recommended by the International Hydrographic Organization. The results indicate that, with a 95% probability, the depths determined by the single-beam echo sounder meet the total vertical uncertainty (TVU) requirements specified by the S-44 standard for Order 1a survey.

A Novel Platform and Workflow for Underwater Photogrammetry Surveys

Abstract. Underwater photogrammetry has gained popularity for creating three-dimensional (3D) maps and ortho-images of marine environments as compared to traditional echosounder surveys, they can be more cost-effective at creating high-resolution 3D models, and orthoimages are usually more informative than acoustic backscatter maps. This paper builds on previous work by the authors that developed an underwater image-capturing platform with several additional sensors, including GNSS, IMU, pressure depth sensor and single beam echosounder. This study aims to analyse the impact of calibration and sensor data integration into the photogrammetric processing workflow. The tests were performed using two underwater sites. The low-cost device's pressure sensor and tide station data outperform GNSS PPK-derived heights. Furthermore, it was observed that incorporating IMU motion sensor data did not improve the processing results. Additionally, utilising the echosounder point cloud proves valuable for enhancing the overall quality of the survey. Despite its lower density, it serves a dual purpose by validating the photogrammetry dataset and, more importantly, can be employed for correcting DSM height. This study further underlined the importance of reliable camera calibration for accurate 3D reconstruction.

Seabed classification in Bahía de Navidad in the Mexican Central Pacific using a single-beam echosounder

This study proposes a methodology for characterizing subtidal habitats along rocky coastlines and adjacent seabeds in the epipelagic zone using a 120 kHz single-beam echo sounder (SBES). The data collected at depths of 15 to 80 m in Bahía de Navidad on the Mexican Central Pacific coast were postprocessed and classified using QTC Impact™ software to obtain three acoustic classes.Using the classified data and ArcMap™ software, a bathymetric map was built for the selection of 19 sampling points for ground truthing and granulometric analysis to create a matrix further subjected to two ordination analyses: principal component analysis (PCA) and nonmetric multivariate scaling analysis (MDS). Additionally, the matrix was adapted into a dummy matrix, which was subsequently used to conduct a Pearson correlation coefficient test.The analyses revealed a strong correlation between the medium-deep-zone acoustic class (20 m to 50 m) and the medium-grain-size sand substrate, as well as a high correlation between the deep-zone acoustic class (50 to 80 m) and finer sand substrates. This study demonstrated the potential of using affordable echosounders as a reliable and feasible alternative for characterizing marine habitats, especially for research institutions in developing countries with limited financial resources.

Acquisition of Bathymetry for Inland Shallow and Ultra-Shallow Water Bodies Using PlanetScope Satellite Imagery

This study is structured to address the problem of mapping the bottom of shallow and ultra-shallow inland water bodies using high-resolution satellite imagery. These environments, with their diverse distribution of optically relevant components, pose a challenge to traditional mapping methods. The study was conducted on several research issues, each focusing on a specific aspect of the SDB, related to the selection of spectral bands and regression models, regression models creation, evaluation of the influence of the number and spatial distribution of reference soundings, and assessment of the quality of the bathymetric surface, with a focus on microtopography. The study utilized basic empirical techniques, incorporating high-precision reference data acquired via an unmanned surface vessel (USV) integrated with a single-beam echosounder (SBES), and Global Navigation Satellite System (GNSS) receiver measurements. The performed investigation allowed the optimization of a methodology for bathymetry acquisition of such areas by identifying the impact of individual processing components. The first results indicated the usefulness of the proposed approach, which can be confirmed by the values of the obtained RMS errors of elaborated bathymetric surfaces in the range of up to several centimeters in some study cases. The work also points to the problematic nature of this type of study, which can contribute to further research into the application of remote sensing techniques for bathymetry, especially during acquisition in optically complex waters.

Seabed Geoacoustic Analysis Using Scientific Single Beam Echosounder

Graphical Abstract Highlight Research Geoacoustic quantification. Sediment identification. Sediment classification. Geoacoustic characteristic. Sediment type spatial distribution in Lancang Island. AbstractHydroacoustic technology was able to quantify the seabed substrate and can be estimated accurately and near real time on the acoustic characters of each substrate. The purpose of the research was to identify the geoacoustic characteristics and spatial mapping of the seabed substrate in Lancang Island. Acoustic data was acquired using a Simrad EK-15 Single Beam Echosounder instrument operating at 200 kHz. Sediment samples were taken using an Ekman grab, which will be used to validate the acoustic data. The results of this study indicated that the acoustic backscatter values of the seabed substrate based on the surface backscattering strength value and sediment particle size at fourteen sampling stations are -28.03 decibels to -20.02 decibels divided into 9 sediment type groups, namely medium and very coarse sand mixture; medium sand; medium, fine and coarse sand mixture; medium and fine sand mixture; fine and medium sand mixture; medium and very fine sand mixture; very fine and medium sand mixture; fine and very fine sand mixture; and fine sand. The accuracy level of k-Nearest Neighbour and Random Forest computational used has very good accuracy of 98.21 % and 96.43 % and Naevi Bayes has a lower accuracy of 58.93 %. The identified geoacoustic characteristics included the mean grain size, sound speed, density, acoustic impedance, and reflection coefficient. Faster, more effective, and efficient computational processes with high accuracy make k-Nearest Neighbour and Random Forest models the best alternative to be used as geoacoustic computational models of seafloor substrates.

DETERMINING SHALLOW WATER BATHYMETRY BY STEREO PHOTOGRAMMETRY TECHNIQUE USING WORLDVIEW-2 IMAGERY

Bathymetry in shallow-water areas plays an important role in marine environment management, marine economic resource development, and national defense and security. The echo sounding method is currently highly accurate; however, it has to deal with a variety of challenges as a result of the high cost, terrain influence, and meteorological conditions at sea. As remote sensing technology progresses, estimating bathymetry using satellite imagery will help lower measuring costs and expand monitoring coverage, particularly in shallow water, offshore areas, and difficult-to-access areas. In this article, the authors present a technique for determining bathymetry in shallow water regions by utilizing WorldView-2 stereoscopic images. The accuracy of stereoscopic depth measurement using WorldView-2 images is assessed by field depth measurement using the single-beam echo sounder. The study area is Nam Yet Island. The coefficient of determination (R2) between the two datasets (field measurement data and using satellite images) is 0.9. The stereoscopic satellite image method of depth measurement is highly accurate for regions with depths below 5 meters. The accuracy of the stereoscopic measurement decreases as the depth increases by more than 5 meters.

Estimating future bathymetric surface of Kainji Reservoir using Markov Chains and Cellular Automata algorithms

The menace of sedimentation to reservoirs has a significant implication for water quality, storage capacity and reservoir lifetime. Rainfall patterns and other anthropogenic and environmental impacts alter the erosion rate and, by extension, directly affect sedimentation rates if left unchecked. This research focused on using the integration of Markov Chains and Cellular Automata (MC – CA) models to estimate and forecast the future bathymetric surface of the Kainji reservoir in Nigeria for the year 2050. The bathymetric datasets used for this research comprise two different epochs (1990 and 2020). The datasets were acquired using a Single Beam Echosounder at Low and High frequencies of 20 kHz and 200 kHz. The preliminary investigation revealed that sedimentation is exacerbating a greater danger to the reservoir functionality. The results show that the maximum observed depth is 71.2 m, indicating a 7.53% loss in depth from the 1990 archived data and a 16.24% depth loss to sedimentation from 1968 to 2020 and 22.35% depth loss in the year 2050 as shown on the projected surface. Consequently, the integrated model (MC and CA) efficiently predicted the future bathymetric surface of the Kainji reservoir for the year 2050 based on the data characteristics. However, the proven techniques for analysing spatial data, such as the Markov Chain and Cellular Automata, best suited for analysing categorical transition data, show some artefacts (black spots) on the projected generated map which is subject to further investigation.

Challenge for multifaceted data acquisition around active volcanoes using uncrewed surface vessel

Monitoring of volcanic eruptions, the atmosphere, and the ocean, along with their scientific understanding, can be achieved through multifaceted observations that include camera images, topographic deformations, elastic waves, geology, and the chemical constituents and temperatures of air and water. However, regions of increased volcanic activity and/or shallow waters are difficult to access by crewed ship due to danger or grounding risk. To overcome these difficulties, we used an uncrewed surface vessel (USV), Bluebottle, to operate multiple observation around oceanic volcanoes in the Bonin Island arc in May 2023. Even under adverse sea conditions, the USV successfully reached a remote observation site, Nishinoshima volcano, which is about 130 km away from Chichijima Island where the USV started out from. The USV conducted five days of observations at shallower than 500 m water depth around Nishinoshima Island, the first time after violent eruptions of Nishinoshima in June 2020. The USV is equipped with various sensors and data collection technologies, including a single-beam echosounder, oceanographic and meteorological sensors, an Acoustic Doppler Current Profiler, and a time-lapse camera. These tools have provided a multi-dimensional view of the underwater landscape and marine conditions near the volcano for the first time in the world. We obtained new bathymetric data, sub-bottom images, and measurements of temperature, salinity, and pH. This study leverages advanced technologies and innovative methodologies to enhance our understanding of marine and geological phenomena.

Analysis of internal wave in the Buru Island coastal waters, Banda Sea, Indonesia

The Indonesian throughflow (ITF) in the eastern part of Indonesia passes through the Maluku, Taliabu, Sula, and Buru Islands to the Banda Sea. The average depth of the Buru and Sula Islands is between 1000 m and 5000 m, with a narrow gap (sill) located to the north and south at a depth of 165 m on the sea map. This topography makes for interesting research on the western waters of Buru Island. Therefore, this study aimed to obtain salinity, temperature, and density values as water column stratification associated with the internal wave (IW), thermocline area, and current patterns at specific depths in the waters of Buru Island, Banda Sea. Data were collected from initial observations of Sentinel 1 satellite imagery of Buru Island to obtain an image of the waves in the water area. Furthermore, a single beam echosounder (SBES), conductivity temperature depth (CTD), and Copernicus Marine were analysed at the same position and time. The research found a non-linear IW Mode 2 at depths of 440–540 m with an estimated amplitude length is 40 km and an amplitude height of 100 m. Based on SBES echogram imaging, CTD data analysis, and modelling, there was an increase in IW density, a 35.25 PSU increase in salinity value at depths of 50∼200 m, a temperature decrease of 27.5 °C to 10 °C at depths of 50∼300 m, and a density stratification of 23.5 kg/m³ to 27 kg/m³ at depths of 50∼300 m.

Integration of Different Density UAV Lidar and Single Beam Echo Sounder (SBES) for River and Riparian Area Digital Terrain Model (DTM) Construction

Rivers and riparian areas are vital components of ecosystems, but accurately modeling their terrain presents challenges, especially in detecting the river surface. This paper proposes an integrated approach that combines UAV LiDAR and Single Beam Echo Sounder (SBES) data to construct a Digital Terrain Model (DTM) of river and riparian areas. The objective is to overcome the limitations posed by water, which absorbs near-infrared laser energy, resulting in weak or absent LiDAR returns. Different UAV LiDAR densities were examined to determine the optimal configuration for capturing riparian areas. Evaluation of the results utilized various metrics, including root mean square error (RMSE), mean square error (MSE), mean absolute error (MAE), mean bias error (MBE), and correlation coefficient (CC). Three ground filtering methods were implemented and assessed: morphological filters, adaptive triangulated irregular network (ATIN) filtering, and above-ground level (AGL) filtering. Among the evaluated methods, the DTM constructed using ATIN with an 80-meter flight configuration yielded the most accurate results. It achieved an RMSE of 0.18m, an MSE of 0.03m, an MAE of 0.17m, an MBE of 9.08m, and a CC of 1.00. Comparatively, other methods exhibited higher error values and lower correlation coefficients. The findings highlight the efficacy of ATIN filtering in conjunction with an 80-meter UAV LiDAR flight for obtaining reliable DTMs of river and riparian areas. This approach demonstrates significant improvement in accuracy, particularly in terms of RMSE and MSE. The derived DTM can be a valuable tool for safeguarding and managing these critical ecosystems. In summary, this paper successfully addresses the challenge of modeling river and riparian terrains by integrating UAV LiDAR and SBES data. By employing ATIN filtering with an 80-meter flight configuration, the study achieves a highly accurate DTM. By employing ATIN filtering with an 80-meter flight configuration, the study achieves a precise, high DTM with minimal error. The developed model contributes to protecting and preserving river and riparian ecosystems.

Gas Emission Characteristics and Tectonic Implications in the Southernmost Okinawa Trough From Split‐Beam Echo Sounder Observations

AbstractTraditionally, single‐beam echo sounder (SBES) data are used to determine the position of emission structures in the form of a two‐dimensional profile, which may not be straightforward enough to correlate the data of adjacent profiles and determine the exact discharge area. In this study, we develop semiautomatic software to remove noise and select possible flare signals to enhance the speed and precision of the data processing. The program also allows for the transformation of the data into a three‐dimensional point cloud distribution by computing the receiving angle of the data. By applying this method to investigate the distribution and mechanism of gas emission structures in the South Okinawa Trough (SOT), we determine four high flux areas and 22 isolated plumes with roots. Widespread gas flares usually occur in areas with large‐scale volcanic activity or gas‐enriched structures. Isolated gas plumes could be found for a single knoll outcrop and normal faulting structures. The energy of the flares around the knoll area is generally stronger than that observed along the normal faults. Compared with other geophysical data, we find that the widespread distribution of gas flares generally implies a larger hydrothermal potential, which may not be revealed by single‐profile acoustic image observations. We also find that the direction of flares is strongly influenced by tides, and the height of the flare represents the thermocline as a strong boundary for bubbles composited by carbon dioxide.

A Complete Coverage Path Planning Approach for an Autonomous Underwater Helicopter in Unknown Environment Based on VFH+ Algorithm

An Autonomous Underwater Helicopter (AUH) is a disk-shaped, multi-propelled Autonomous Underwater Vehicle (AUV), which is intended to work autonomously in underwater environments. The near-bottom area sweep in unknown environments is a typical application scenario, in which the complete coverage path planning (CCPP) is essential for AUH. A complete coverage path planning approach for AUH with a single beam echo sounder, including the initial path planning and online local collision avoidance strategy, is proposed. First, the initial path is planned using boustrophedon motion. Based on its mobility, a multi-dimensional obstacle sensing method is designed with a single beam range sonar mounted on the AUH. The VFH+ algorithm is configured for the heading decision-making procedure before encountering obstacles, based on their range information at a fixed position. The online local obstacle avoidance procedure is simulated and analyzed with variations of the desired heading direction and corresponding polar histograms. Finally, several simulation cases are set up, simulated and compared by analyzing the heading decision in front of different obstacle situations. The simulation results demonstrate the feasibility of the complete coverage path planning approach proposed, which proves that AUH completing a full coverage area sweep in unknown environments with a single beam sonar is viable.

A Terrain-Following Control Method for Autonomous Underwater Vehicles with Single-Beam Sensor Configuration

This paper investigates the terrain-following problem for an autonomous underwater vehicle (AUV) from control perspectives with full consideration of terrain characteristics. By equipping the AUV with three simple single-beam echo sounders, a set of precise along-track bottom slopes are obtained in a real-time manner, and the occurrence of the lost bottom lock phenomenon caused by a single sonar altimeter is eliminated. A slope-based data processing method is developed, which enables an AUV to characterize seafloor features with complementary sensing modalities to generate proper adaptive height-modified values. In order to keep a fixed height when maneuvering over rugged terrains, a back-stepping depth control is implemented by adjusting horizontal rudder angle, and Lyapunov theory is adopted to analyze the asymptotic stability of the resulting terrain-following control system. At last, simulation results indicate the feasibility and effectiveness of the proposed methodology with a discussion of various sensor configurations.

A contour-based path planning method for terrain-aided navigation systems with a single beam echo sounder

Underwater terrain-aided navigation (TAN) methods with a single beam echo sounder (SBES) have the potential to facilitate long-term underwater navigation for underwater vehicles. However, the limited bathymetric measurement of the SBES often makes the accuracy and robustness of TAN navigational results greatly affected by the complexity of the terrain. Therefore, effective path planning for SBES-TAN is essential. This paper proposes a contour-based path planning method for SBES-TAN, which can yield robust navigational results even with noisy SBES measurements. Moreover, both the density and smoothness of contour lines are used to quantify terrain complexity. Moreover, a fuzzy comprehensive evaluation-based theory is used to identify TAN-suitable areas. Path planning is accomplished using the rapid-exploration random tree* algorithm, while a Monte Carlo-based TAN estimate handles the challenges posed by noisy SBES measurements. The performance of the proposed method has been verified through simulation using field bathymetric data, by comparing it with state-of-the-art methods.

A COMPARISON OF DIFFERENT GIS-BASED INTERPOLATION METHODS FOR BATHYMETRIC DATA: CASE STUDY OF BAWEAN ISLAND, EAST JAVA

The bottom surface’s portrayal is crucial in many different practices. Therefore, accurate bathymetry data is required. The interpolation method is one element that influences the accuracy of a Single Beam Echosounder’s depth data. IDW, Kriging, and TIN are three standard interpolation techniques. This study compares these three methods with two scenarios utilizing the spatial analysis to establish the most effective technique for producing the digital elevation model of the seafloor beneath Bawean Island. The IDW exhibits the strongest R-squared (0.9998779 in Scenario-1 and 0.9999875 in Scenario-2) and correlation (0.9998796 in Scenario-1 and 0.9999595 in Scenario-2). It indicates that IDW and bathymetric data have the closest relationships. IDW has the lowest error, as measured by the MAE value (0.02 in Scenario-1 and 0.009 in Scenario-2), followed in both cases by Kriging and TIN. Additionally, the RMSE for IDW shows the same outcome (0.045 in Scenario 1 and 0.016 in Scenario 2). In the meantime, comparing the first and second scenarios reveals that the second, which has fewer data, is preferable to the first. Since the MAE and RMSE in the first scenario are greater than those in the second, we may infer that more data leads to more significant errors.

Seabed Sediment Classification using Multi-Frequency MBES Bathymetric and Its Features

Principally, for a few decades, hydrographical surveys have been only to determine the depth of seawater. Sonar measurement tehcnology is the most widely used to conduct hydrographical surveys employing a singlebeam echosounder (SBES) and multibeam echosounder (MBES). In addition to depth information, seafloor sediment distribution maps are essential for port planning and management. In general, the distribution of seafloor sediments is predicted using backscatter data from SBES and MBES at single and multiple frequencies. The bathymetric data generated by the echosounder can be derived into several bathymetric features such as slope, ruggedness, roughness, aspect, bathymetric position index (BPI), and curvature. This study examines the possibility of using bathymetric measurement and bathymetric derivation of multi-frequency MBES to predict the distribution of seafloor sediments, especially in the harbor pond area. The study used a deep neural network (DDN) to classify the distribution of seabed sediments with bathymetric and bathymetric features input, validated with 74 in situ sediment samples (clayey sand, silt, sandy silt, and silty sand). Up to 75% of data sample sediments are used for training and 25% for validation. The classification results by DNN showed 42.6% clayey sand, 7.4% sandy silt, 46.7% silt, and 3.35% silty sand. The overall accuracy (AO) and Kappa classification of seabed sediments with DDN were 59.5% and 0.54 (moderate), respectively.

Target strength of Nile tilapia (Oreochromis niloticus) from 200 kHz calibrated fish finder and scientific echosounder: laboratory measurement and modeling

Target strength (TS) values from laboratory measurement and TS values from the model were measured and calculated from Nile tilapia (Oreochromis niloticus). Nile tilapia is one of the fastest growing aquaculture species, the fourth most produced fish globally, easily available in various sizes and lengths, and more importantly, it has a one-chambered swimbladder, which is suitable for TS measurement and modeling. The most common technique of measuring fish TS is utilizing a scientific echosounder. However, this instrument has a low implementation for small-scale fisheries due to its relatively high cost compared to the conventional fish finder. Thus, the objective of this study is to offer a solution that considers the instrument’s cost and usefulness using calibrated fish finder and scientific echosounder. TS values were produced by the two instruments that later being examined with TS from the Kirchhoff-ray mode (KRM) model to validate the result. Two single-beam echosounder instruments (Furuno FCV-628 fish finder and Simrad EK15 scientific echosounder) operated at a frequency of 200 kHz were used to assess the TS values for 30 samples of living Nile tilapia whose total length (TL) was in a range of 6 to 26 cm. In conclusion, statistically, the results showed no significant differences in TS measurement between the two instruments compared to TS values from the model. The TS values from the KRM model agreed well based on the regression analysis with the TS values from both instruments in the laboratory measurement.

Cross-Comparison of the “BathySent” Coastal Bathymetry to Sonar Measurements and Ratio Model Technique: Pilot Sites in the Aegean Sea (Greece)

The proposed novel “BathySent” approach for coastal bathymetric mapping, using the Copernicus Sentinel-2 mission, as well as the assessment and specification of the uncertainties of the derived depth results, are the objectives of this research effort. For this reason, Sentinel-2 bathymetry retrieval results for three different pilot sites in Greece (islands of Kos, Kasos, and Crete) were compared with ground-truth data. These data comprised high-resolution swath bathymetry measurements, single-beam echosounder measurements at very shallow waters (1–10 m), and the EMODnet DTM 2018 release. The synthetic tests showed that the “BathySent” approach could restitute bathymetry in the range of 5–14 m depth, showing a standard deviation of 2 m with respect to the sonar-based bathymetry. In addition, a comparison with the “ratio model” multispectral technique was performed. The absolute differences between conventional Earth Observation-based bathymetry retrieval approaches (i.e., linear ratio model) and the suggested innovative solution, using the Sentinel-2 data, were mainly lower than 2 m. According to the outcome evaluation, both models were considered to provide results that are more reliable within the depth zone of 5–25 m. The “ratio model” technique exhibits a saturation at ~25 m depth and demands ground calibration. Though, the “BathySent” method provides bathymetric data at a lower spatial resolution compared to the “ratio model” technique; however, it does not require in situ calibration and can also perform reliably deeper than 25 m.

Creating an Autonomous Hovercraft for Bathymetric Surveying in Extremely Shallow Water (

Coastal shallow water environments (<5 m) are extremely biodiverse and dynamic yet are often mapped too infrequently or at too low resolutions to capture the important processes occurring in these regions. Common forms of coastal surveying can leave gaps in data in the shallow water zone due to optical instrument capabilities and a vessel's ability to navigate in this region. One solution to these issues is an autonomous hovercraft that can fly over land and water and begin surveying at sub-meter water depths, bridging the gap between common optical and acoustic surveying methods. The craft's autonomy is tested via four autonomous flight paths, or missions, and the desired path is compared to both the observed heading and direction of motion. Although the accuracy for each track in the mission varies, most headings and directions of motion of the hovercraft are within 50 degrees of the desired direction. A single-beam echo sounder was used to map the bathymetry of the study site, showing a gently sloping beach.

Method for determining of shallow water depths based on data recorded by UAV/USV vehicles and processed using the SVR algorithm

Bathymetric measurements in waters shallower than 1 m are necessary to monitor seafloor relief changes in the coastal zone. This is especially important for ensuring the safety of navigation, navigation efficiency, as well as during the design and monitoring of hydrotechnical structures. Therefore, the aim of this article is to present a method for determining of shallow water depths based on data recorded by Unmanned Aerial Vehicle (UAV) and Unmanned Surface Vehicle (USV), as well as processed using the Support Vector Regression (SVR) algorithm. Validation studies of this method was carried out on two selected waterbodies (inland and sea) using the DJI Phantom 4 Real Time Kinematic (RTK) UAV and the AutoDron USV. Then, the geospatial data recorded by a drone was applied to determine depths of shallow waterbodies using the SfM algorithm. Subsequently, the determined depths were compared with the depths measured by a Global Navigation Satellite System (GNSS) RTK receiver or a Single Beam Echo Sounder (SBES), in order to assess the accuracy of the proposed method. The research showed that it is able to determine shallow waterbody depths with the accuracy requirements specified for the International Hydrographic Organization (IHO) S-44 special order (depth error ≤ 0.25 m (p = 0.95)), but only to depths not exceeding 1 m. In the inland waterbody, the depth accuracy was 0.22–0.24 m (p = 0.95), while in the sea waterbody the measurement accuracy was higher, amounting to 0.16 m (p = 0.95). However, for the depth range up to 2 m, the results are radically different, because the vertical position error with a 95% confidence level exceeds the value of 0.3 m in the analysed waterbodies.