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This paper introduced automated detection and analysis of lunar craters are crucial for advancing lunar research and facilitating mission planning. This study introduces a comprehensive multi-scale approach for crater detection on the lunar surface using LROC (Lunar Reconnaissance Orbiter Camera) Dataset, enabling the identification of craters across varying scales and enhancing overall detection accuracy and efficiency. The process involves preprocessing lunar imagery to enhance features and delineate potential crater regions, utilizing edge detection algorithms to extract crater boundaries. Clustering techniques are then applied to group similar edge points and isolate potential crater candidates. A thresholding mechanism based on statistical edge intensity analysis refines the detection process. To address multiple detections of the same crater at slightly different diameters, radius criteria are implemented, yielding high diameter accuracy of 84% for mare Imbrium (test site 1) and 80% for mare Nubium (test site 2). Subsequently, a depth-diameter analysis validates crater-like characteristics by combining depth measurements with crater diameter estimation, showcasing the authenticity of potential craters. we compare our diameter and depth with different reference papers and we get high accuracy of R2 =0.99 then other methods. The results highlight the potential of this multi-scale approach for automated lunar crater detection, providing deeper insights into the Moon's surface morphology and history for future lunar exploration missions. [ABSTRACT FROM AUTHOR]

The empirical approach of satellite-derived bathymetry provides a straightforward, easily-implemented, and very effective way of estimating shallow-water depths from high-spatial-resolution satellite images. However, this approach has a great challenge that it requires high-quality in-situ depth data, which often do not exist or are not available due to financial and/or technical reasons, as the depth calibration data. To address this problem, this article assesses the feasibility of replacing high-quality in-situ depth data with four kinds of possible sourced depth data in satellite-derived empirical bathymetry. These four kinds of depth data are satellite altimeter depth data from laser altimeter systems on some earth observing satellites; satellite photogrammetric depth data, which are derived from satellite stereo-images with the photogrammetric method; nautical chart depth data, which come from existing electronic or paper charts; and radiative transfer model-based depth data, which are simulated in accordance with a bio-optical radiative transfer model (RTM). Correspondingly, four kinds of empirical bathymetry's model calibration data are referred to as altimeter data, photogrammetric data, chart data, and RTM data, respectively. The objective of this article is to assess the similarities, differences, limitations, and applicability of these four kinds of possible model calibration data, in order to know which of them is most suitable for a certain empirical bathymetry task. WorldView-2 and Sentinel-2A multi-spectral images covering four typical shallow water areas in Hawaii and Xisha Islands and Stumpf's logarithmic band ratio model were used to compare and contrast the bathymetric performance of these four kinds of possible model calibration data. The result showed that all four kinds of possible model calibration data can be used for satellite-derived empirical bathymetry when the high-quality in-situ depth data are not provided, but they will provide different bathymetric accuracy values. According to five evaluation indexes (i.e., bathymetric performance, data availability, data quality, complexity of data generation, and data adaptability), the altimeter data perform best, the chart data perform second best, the RTM data follow with the third performance, and the photogrammetric data perform markedly worse than other three kinds of model calibration data. Such factors as the in-situ property, spatial coverage, co-registration and independence of model calibration data must be taken into consideration as well during a model calibration data selection. [ABSTRACT FROM AUTHOR]

Effective coverage path planning for USVs is essential to optimize the performance of bathymetric surveys. Traditionally, it is well recognized that the best sweep direction for coverage path planning is the parallel direction that finds the minimum span of the region of interest (ROI). However, the results in this paper first reveals that it is not always the case when the water current is involved. In this paper, we first formulate an energy consumption estimation model for USV and introduce a novel coverage path planning strategy. Then, we investigate the relationship between sweep direction and USV energy consumption under the influence of water currents, referred to as the E - β curve. We then systematically analyze the variations of the E - β curve under different shapes of ROIs, various water current attacking angles, and different coverage strategies. Finally, the model is extended to more realistic scenarios involving non-convex ROIs. The practicality of the model is validated USV semi-physical model. The results indicate that, under water currents, our proposed model allows for an optimal sweep direction that minimizes the energy consumption of USVs. This contrasts with traditional methods, which fail to achieve the optimal energy cost. The results hold significant implications for the design of USV mapping strategies in inland river. • This paper is the first to unveil the relationship between sweep direction and USV energy consumption under water currents, referred to as E - β curve. • Systematical analysis has been conducted on the factors that may impact the E - β curve. • An energy consumption estimation model for USV is constructed. • The model is extended to realistic scenarios involving non-convex polygonal ROIs and semi-physical simulation. [ABSTRACT FROM AUTHOR]

Monocular 3D object detection aims to localize objects in 3D space from a single image. This is a difficult problem due to the lack of accurate depth measurements. Many methods predict depths upfront using a pre-trained vision-based depth estimator to assist in 3D object detection. However, the methods show limited improved performances because of the depth inaccuracy and the neglect of depth confidence. In this paper, we propose a new end-to-end 3D object detection framework by combining a monocular camera with a cheap 4-beam LiDAR. The minimal LiDAR signal is leveraged as an additional input to predict high-quality and dense depth maps from monocular images. Meanwhile, several 3D proposals are generated by a keypoint-based detector. The key challenge is encoding the depth confidence to capture the depth estimation uncertainty. Therefore, we propose probabilistic instance shape reconstruction to exploit instance shape information for box refinement. Our method employs a fully differentiable end-to-end framework, making it simple and efficient. The experimental results on the KITTI dataset demonstrate that the proposed method achieves state-of-the-art performance, thus validating the effectiveness of the sparse LiDAR data and the probabilistic instance shape reconstruction. Code is available at https://github.com/xjtuwh/SparseLiDAR_fusion. [ABSTRACT FROM AUTHOR]

Terrain-aided navigation (TAN) is one of the key techniques for autonomous navigation and positioning of AUVs. This paper develops a novel integrated navigation system that combines the inertial navigation system (INS) and TAN into one filter, in contrast to the conventional INS/TAN model. This method not only provides a position estimate for the carrier but also the INS error, which increases the filtering dimension significantly. Thus, the Rao-Blackwellized particle filter (RBPF) technique is introduced to address the "dimensional disaster" problem. A three-dimensional (3-D) model is established to estimate the horizontal position while compensating for the tidal inaccuracy by extending the tidal depth bias to the state space. Furthermore, the variable and complex underwater environment can potentially result in outlier interference in depth measurements, which significantly degrades the performance of the RBPF-based estimation algorithm. This paper thus presents a 3-D adaptive RBPF method based on the maximum correntropy criterion (MCC) to suppress the influence of measurement outliers on positioning precision. Simulations and experimental tests verify the effectiveness of the proposed algorithm. The results demonstrated that the 3-D model-based AMCCRBPF method can effectively improve robustness to outliers and provide an accurate estimate of the tidal depth bias. • A tightly integrated INS and TAN system is created to enhance algorithm stability when tide information is inaccurate. • Based on the MCC, the likelihood function is improved to enhance the estimation accuracy of nonlinear states. • Adaptive estimation of noise characteristics is done to enhance the accuracy of linear state estimation. [ABSTRACT FROM AUTHOR]

• The principal purpose of this paper is the development in numerical treatments for the resonance problem of multi-phase systems by constructing a well-balanced finite volume scheme for two-dimensional shallow water equations with variable topography. • This scheme is constructed based on exact solution of local planar Riemann problems at each grid cells. • The well-balancedness of this scheme is shown in the sense that it can preserve exactly the lake at rest solution over both smooth and non-smooth bottom. • Several numerical experiments related to steady and time-dependent problems are conducted to show the potential of this approach. • The remain challenges are the ineffectiveness of this scheme towards time-dependent solutions throughout a long process and the instability of errors caused by the relaxation while coding. • This work provides an impetus to enhance the performance of this scheme for time-dependent solutions, and motivates further studies in numerical treatments of the resonance problem for multi-phase flow models as well. We consider in this paper a finite volume scheme based on local planar Riemann solutions for the two-dimensional shallow water equations with bathymetry. The model involves a nonconservative term, which often makes standard schemes difficult to approximate solutions in certain regions. The scheme to be presented is a development of the preliminary works that will be cited below. Our foremost purpose is to extend those results to two-dimensional formalism while preserving the physical and mathematical properties, including the well-balancedness. The proposed scheme is applied to some specific families of solutions, especially lake at rest and partially well-balanced solution. The numerical results show that this approach can give a good accuracy, except for resonant cases. Furthermore, it is proved that our finite volume scheme can preserve the C -property in the sense that it can capture exactly the lake at rest solution. [ABSTRACT FROM AUTHOR]

Bathymetric data is crucial for navigation safety and various applications. However, only a small portion of the seafloor has been systematically mapped through direct measurement. The remaining bathymetry is estimated from satellite altimeter data, providing only an approximate representation of the seafloor's shape. To address this issue, the convolutional neural network (CNN) is introduced for the analysis of seabed topography. To the best of our knowledge, this marks the first attempt to incorporate the CNN into the definitive map of the world ocean floor. By employing skip connections based on residual learning, we construct a deeper CNN layer that effectively reduces training complexity. The deeper convolutional neural network layer is used to create a more complex nonlinear mapping model, which is then employed to downscale low-resolution seabed topographic data in order to obtain high-precision seabed topographic information. This process enhances the representation of seabed topographic data to reflect the actual terrain more accurately. The results are compared with those obtained using the bicubic difference method. Conducting tests near the Gulf of Thailand, where Malaysia Airlines Flight MH370 was lost, the results demonstrate that the method proposed in this paper achieves higher accuracy in processing the downscaling of seabed topographic data. • Convolutional neural networks refine seabed terrain does not direct electromagnetic detection. • The first attempt to incorporate a CNN into the final map of the world's seabed. • Basic application of artificial intelligence algorithms in "smart ocean". • Specific application of seabed research in the missing area of Malaysia Airlines Flight MH370. • It contributes a new idea to the global seabed geomorphologic map. [ABSTRACT FROM AUTHOR]

A robust mathematical model is presented in this paper for the multi-connected domain with variable bathymetry using dual reciprocity boundary element method (DRBEM) to analyze the combined effects of wave diffraction-refraction and reflection on the arbitrarily shaped harbor. The influence of sloping bathymetry and the impact of the bottom friction on the harbor resonance are investigated. The fluid domain is primarily separated into two regions Region-I (open sea region) and Region-II (harbor region). Further, Region-II is divided into multi-connected regions. The mild slope equation is rearranged to obtain the non-homogeneous Helmholtz equation, and utilizing the ordinary boundary element method to this non-homogeneous equation, the non-homogeneous part will convert into a domain integral. The present model is verified by comparing it with the analytical examination of Wang et al.2015; Shao et al.2017. The wave amplification is determined for the T-shaped and TT-shaped domains to analyze the influence of bottom friction, and slopping bathymetry. Further, the present numerical approach is employed to the realistic port, Visakhapatnam port, India, and the four key locations are identified to analyze harbor resonance in the bottom friction and slopping bathymetry of the multi-connected region. • A Dual reciprocity boundary element method (DRBEM) with wave diffraction-refraction on the arbitrarily shaped harbor. • The influence of sloping bathymetry and effect of the bottom friction is also investigated. • Wave Amplification of the T-shaped and TT-shaped domains to analyze the influence of bottom friction, and bathymetry. • Implemented on the realistic Visakhapatnam port, Andhra Pradesh, India. • To analyze the harbor resonance on slopping bathymetry and effectively for redesigning, renovating and constructing ports. [ABSTRACT FROM AUTHOR]

This paper aims to explore the effects of earthquakes on the properties of medium-height reinforced concrete houses in China. The results demonstrated a significant decrease in ultrasonic resonance frequency, indicating structural damage, with reductions of 26.5 %, 30.2 %, and 37 % observed for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Similarly, the dynamic modulus of elasticity exhibited a reduction of over 50 %. Measurements of carbonation depth revealed values of 34.65 mm, 38.97 mm, and 46.12 mm for earthquakes of magnitudes 5.0, 5.3, and 5.7, respectively. Accordingly, the percentage of mass loss amounted to 22.17 %, 36.87 %, and 49.78 %. Furthermore, experiments identified the least favourable outcomes during maximum seismic activity, with a recorded peak stress of 447.3 MPa at a deformation of 0.63 mm. These findings contribute to a better understanding of the impact of seismic events on reinforced concrete structures and the associated corrosion mechanisms. [ABSTRACT FROM AUTHOR]

This study introduces an innovative technique specifically designed to effectively mitigate multibeam sonar noise in intricate scenarios where conventional denoising methods have typically faltered. These traditional methods have historically struggled to maintain a delicate balance between sensitivity, specificity, and interpretability, leading many cartographers and research professionals to resort to laborious and time-consuming manual processing techniques. In response to this prevalent challenge, we meticulously formulated a mathematical model to represent each individual step involved in the manual editing process. The approach involves parameterization of cartographers' perceptual manipulation, resulting in a novel noise rejection methodology. A notable attribute of this method is its simplicity and intuitive nature; users are required to set only a handful of fundamental parameters to obtain highly accurate processing results. Importantly, this technique spares the data from exposure to linear filters such as lowpass or average filters, enhancing the fidelity and reliability of the results. Furthermore, our proposed method retains the interpretability of the processed seafloor bathymetry as it abstains from implementing opaque methodologies such as Neural Networks. This aspect of the technique makes it an ideal choice for researchers and cartographers who prioritize understanding the underlying processes affecting their data. In the discussion segment of this paper, we present a quantitative comparison of the data processed by manual edit, the commercially mature algorithm, and our newly proposed method. This comparison underscores the superior performance and effectiveness of our technique, further reinforcing its potential applicability in real-world scenarios. • MBES denoising method, turning manual editing procedures into a mathematical model. • Using intuitive parameters, keeps high accuracy, clarity and interpretability. • Tested on various terrains, showing high universality and reliability. [ABSTRACT FROM AUTHOR]

RGB-D cameras such as RealSense and Structure Sensors have been widely used in most robotics systems. This paper presents a system for estimating the trajectory of an RGB-D camera and IMU in indoor environments. The system uses a novel relative pose estimation method that utilizes depth measurements and epipolar constraints for initialization. An adaptive depth estimation method is also proposed, which fuses a depth uncertainty model and multi-view triangulation. In the backend, a sliding window framework is used to optimize the system state by minimizing the residuals of pre-integrated IMU, 3D features re-projection, and 2D features epipolar constraint. The effectiveness of the system is evaluated using publicly available datasets with ground truth trajectories. • This paper uses the depth uncertainty model of the depth camera to divide feature point pairs into 3D–3D and 2D–2D pairs based on their depth measurement noise. A robust pose estimation method is then introduced to fuse 3D–2D and 2D–2D constraints for initialization. • An adaptive depth estimation method is proposed, which combines the depth uncertainty model and multi-view triangulation to achieve high-precision feature point depth estimation. • The paper presents a nonlinear optimization framework in the backend that combines epipolar and re-projection constraints. [ABSTRACT FROM AUTHOR]

Tidal turbines at sea are subject to complex flow conditions. Among that complexity, wide bathymetry obstacles can generate powerful coherent flow structures whose impact on horizontal axis tidal turbines was proved to be highly detrimental. Consequently, the present paper aims at studying the effects of such coherent flow structures on the response of another tidal turbine geometry, namely a bottom-mounted ducted twin vertical axis tidal turbine (2-VATT). We tested a 1/20 scale model of such a 2-VATT in Ifremer's flume tank either with a flat bed or downstream of a wide bathymetry obstacle at a constant far upstream velocity and we measured the turbine response simultaneously with the flow velocity. These flow measurements make it possible to compute cross-correlations in order to analyse the influence of the velocity fluctuation on the turbine response. The results reveal a strong drop in the average power and loads coefficients of the 2-VATT combined with significantly larger fluctuation. The velocity deficit and the high level of turbulence in the obstacle wake is responsible for a 40% lower average power coefficient and more than 3 times higher standard deviation compared to the flat bed configuration. The loads standard deviations are multiplied by 2 for the drag and by 10 for the lift when the 2-VATT is downstream of the bathymetry obstacle. This behaviour strongly increases the risks of structural fatigue failure, but the turbine drifting or overturning risks under those conditions remain lower than with the flat bed. The power fluctuation increase appears to be mostly due to the flow shear in the obstacle wake whereas the load fluctuation is mostly due to the periodical passing of the coherent flow structures. Thus, a proper characterisation of the flow at each precise turbine locations prior deployment at sea is highly recommended to design their structure accordingly. • Vertical axis turbine in the wake of uneven bathymetry generating flow variation. • Obstacle wake induces strong drop in the average power and loads coefficients. • Sheared flow and turbulence extend the torque and power fluctuations. • Coherent flow structures induce load fluctuations. [ABSTRACT FROM AUTHOR]

There is a pressing need for a fast and efficient satellite remote sensing tool to estimate coastal bathymetry for any coastline in the world. To date, satellite methods for deriving bathymetry have mainly focused on linking the radiometric response to a known water depth, as with SPOT, Landsat and Sentinel. Here, wave properties (static and dynamic) are approximated using the small time delay between the different color bands of Sentinel-2 to then calculate a depth using wave linear dispersion theory. In this paper, we present a spatial correlation method within the S2Shores (Satellites to Shores) Python toolbox: a processing chain/toolbox of coastal observations using methods applied to optical satellites. The resulting individual bathymetries are finally qualified according to the standards of the International Hydrographic Organization, anticipating their operational use. • S2Shores spatial-correlation method for optical satellite coastal observations. • Bathymetry qualified with the International Hydrographic Organization standards. • Wave characteristics from the time delay between spectral bands of Sentinel-2. [ABSTRACT FROM AUTHOR]

With portable and cost-effective attributes, unmanned surface vehicles (USVs) are becoming a crucial role in coastal bathymetric surveys. However, in practical applications, the deployment of USVs for bathymetry encounters challenges from multiple facets, including intricacies of coastline shapes, determination of optimal coverage paths, and the sub-region sequencing. To address these issues, this paper introduces a novel coverage planning scheme designed for a coastal bathymetric survey in a lake region. The scheme commences with the Control Point Douglas-Peucker algorithm that effectively utilizes control points to envelope complex coastal lines, ensuring coastline accuracy while facilitating cellular decomposition. Subsequently, an optimal coverage strategy, characterized by fast convergence, complete coverage, and solution optimality, is meticulously designed to generate the most effective back-and-forth survey paths. Finally, by applying the mapping mechanism and fuzzy rules, a Fuzzy Biased Random Key Evolutionary Algorithm is devised to determine the optimal sequence of survey areas. Extensive simulation studies and comparative evaluations substantiate the superiority of the proposed scheme over existing state-of-the-art methods across various problem variants. In addition, real-world lake trials with USV SL-20 are conducted, providing empirical validation and emphasizing the augmented practicality of implementing the proposed methodology in engineering applications. • A Control Point Douglas-Peucker method is proposed to approximate the intricate coastal lines. • A novel coverage strategy is designed to achieve fast convergence, solution optimality, and complete coverage. • A Fuzzy Biased Random Key Evolutionary Algorithm is proposed to determine the mapping sequence of sub-regions. • The practicability is validated through lake trials using USV SL-20. [ABSTRACT FROM AUTHOR]

The safeguard of existing masonry buildings requires a meticulous characterisation of the component materials (units and mortar) by using in-situ minimally intrusive techniques. This need is especially prominent in the case of heritage buildings in order to minimize their damage and alteration. This paper presents a research on some minor destructive techniques (MDT) for the in-situ evaluation of the mechanical properties of masonry components. In the research, the results derived from MDT were empirically correlated with the compressive strength obtained by using well-known destructive testing (DT) techniques executed in the laboratory. The experimental campaign focused on two different MDT techniques, namely the Pin Penetration Test (PPT) and the Helix screw Pull-out Test (HPT). The PPT is based on the measurement of the depth of penetration of a steel pin. The HPT is based on the measurement of the pull-out load necessary to extract a steel tie inserted into a hole drilled in a brick or in a mortar joint. The experimental campaign also included an evaluation of the Double Punch Test (DPT) by comparison with strength values obtained from mortar specimens prepared and tested following the standard EN 1015–11. The experimental results show a satisfactory agreement between the MDT measurements and the compressive strength obtained with DT. Although both the PPT and HPT are useful for the evaluation of the compressive strength of masonry components, the former exhibits a lower scattering in the experimental measurements. • 541 destructive tests on modern and historical solid clay bricks and mortar joints. • 741 minor destructive tests on solid fired clay bricks and mortar joints. • Compressive strength in mortar using Double Punch Test and EN 1015–11 procedure. • Compressive strength evaluation of specimens using the Pin Penetration Technique. • Compressive strength evaluation of specimens using the Helix screw Pull-out Test. [ABSTRACT FROM AUTHOR]

[Display omitted] Lake Urmia, once the second-largest saline lake worldwide, has almost dried. Several studies have provided bathymetric maps for the lake using different data and techniques but rarely identified the associated uncertainties. This paper provides a comprehensive review of Lake Urmia bathymetric studies and discusses the underlying uncertainties. We developed an updated hybrid bathymetry and hypsometric relationships for Lake Urmia using in-situ and satellite data. The proposed hybrid bathymetry was validated against independent in-situ depth data (with an RMSE < 20 cm) and applied as a baseline for comparison with other available bathymetry models. Results revealed that uncertainties in lake depth measurement, water delineation algorithms from satellite data, spatial interpolation method, and sensor resolution have the highest uncertainty, respectively. Furthermore, the width of the uncertainty bands in the lake level-area relationships is not uniform and peaks at lake levels between 1270 and 1272 m, which are critical for conserving crucial ecosystem services of Lake Urmia, such as island conservation and dust control. Our synthesis indicated that the application of various Lake Urmia bathymetries could lead to about 0.5 and 1 km3 differences in the estimated lake volumes for obtaining the ecological and dust control levels, respectively. Our findings provide useful insights for Lake Urmia managers, also applicable for other saline lakes, into considering the dynamic of lake topography and associated uncertainties in lake conservation/restoration programs. [ABSTRACT FROM AUTHOR]

In this paper, the effects of regular waves propagating against the current on the wake of a wide bathymetric obstacle are experimentally investigated. For that purpose, a square cylinder of height representing 1 / 8 t h of the water column, mounted perpendicular to the flow, is used. Both Reynolds and Froude numbers are close to the ones encountered at sea and swell properties (amplitude, frequency and wavelength) which are typical conditions in the English Channel. To study this complex hydrodynamic interaction, PIV measurements are used to capture the velocity field around and in the wake of the cylinder. The wake of this wide cylinder has been extensively studied and is characterised by its direction towards the water surface and by energetic and wide vortices arising from the sheared layer at a Strouhal number of approximatively 0.06, after a merging of smaller eddies. In this work, the focus is on how surface gravity waves, propagating against the current, modify the generation of these turbulent structures. The results show that the cylinder wake is strongly modified in the presence of waves, even if, on average, the main wake structure is globally conserved. The waves act both on the vortex generation and the wake development with modifications in terms of turbulent energy distribution and level, wake recovery and ascent rate. The vortex shedding becomes highly energetic and well-organised from the cylinder position. Its return period is extremely regular and corresponds to half of the wave frequency which is really close to the natural vortex shedding frequency. That results in a doubling of the statistical length scale of the vortices. • Swell induced-motion effects on high and isolated bathymetry roughness. • Bottom mounted cylinder wake characterisation in presence of waves opposing current. • Vortex generation and dynamic study. • Energy transfer between wave and vortex shedding frequency in the near-wake. [ABSTRACT FROM AUTHOR]

EM-MWD systems transmit downhole data via an information channel composed of drill string and formation, and the formation has a strong attenuation effect on the signal. Signal attenuation in EM wave transmission in the formation limits the application well depth. This paper discusses several commonly used methods to improve the depth of EM-MWD applications, including turbine power supplies, adaptive power outputs, transmitting antenna extensions, and repeater transceivers. Based on both theory and practice, the characteristics of these methods are analyzed. An EM-MWD system in which signals are received from an adjacent well is proposed, and a formula for calculating the receiving voltage for an adjacent well is derived based on a model of this system. According to this formula, the proposed EM-MWD system can greatly increase the receiving voltage, where deeper adjacent wells provide a greater increase in the receiving voltage and a greater maximum transmission depth for the EM-MWD system. In-hole experiments of this EM-MWD system based on signals received from an adjacent well demonstrate that this method can effectively increase the voltage of the received signals on the ground, in agreement with theoretical results. • This paper discusses several methods to improve the depth of EM-MWD applications. • An EM-MWD system in which signals are received from an adjacent well is proposed. • A formula for calculating the receiving voltage of the system is derived. • Experiments demonstrate that this method can effectively increase received voltage. [ABSTRACT FROM AUTHOR]

This paper presents a theoretical and numerical analysis based on a model of mangrove forests incorporating stems and roots to determine the nearshore wave angle and wave height for one-dimensional (1-D) and two-dimensional (2-D) problems. The shallow water equations are solved using the two-step Lax-Wendroff method. The resulting wave height and wave direction vectors are displayed and analyzed to assess the impact of mangrove effects on various bathymetries, including constant, sloping, and parabolic profiles. This procedure is also applied to actual bathymetric data obtained from the Hatiya channel to analyze the influence of mangrove forests and shoreline geometry on the amplitude and wave directionality of nearshore waves. The obtained numerical results demonstrate that both coastal geometry and vegetation exhibit non-linear characteristics in wave behavior. Furthermore, these factors significantly contribute to the directionality and attenuation of nearshore waves. • Mangrove models studied for nearshore wave angle and height via theoretical and numerical methods. • Wave vectors explore mangrove impact on various bathymetries: constant, sloping, parabolic, real. • Numerical results show nonlinear wave behavior due to coastal geometry and vegetation. [ABSTRACT FROM AUTHOR]

• UAV-captured images were applicable for estimating surface water volume of tufa lake group. • Water area extraction was improved by adding surface elevation to inputs of classification ANN. • Deep bathymetry network underestimated water depths of tufa lakes compared with shallow one. • RGB-E classification network and shallow bathymetry network were the optimum combination. Quantitative acquisition of surface water volume of tufa lake group is significant for protecting the tufa landscapes. Limited by low spatial resolution, satellite remote sensing failed to extract the surface water distribution of small and scattered tufa lakes. In recent years, Unmanned Aerial Vehicle (UAV) remote sensing has been increasingly applied to survey aquatic resources and environments, posing great potential for accurately measuring surface water volume of tufa lake group. In this paper, taking the Shuzheng Lakes in Jiuzhai Valley of China as the study site, we used UAV-captured images and Artificial Neural Network (ANN) models to precisely estimate the surface water volume of the tufa lake group. Digital Surface Model (DSM) and orthomosaic were first generated using aerial triangulation. Next, the two classification networks were trained to separate water from vegetation, and then the water extents of individual tufa lakes were extracted. Subsequently, the water depth map of each tufa lake was retrieved using the transferred shallow and deep bathymetry networks. Lastly, the total surface water volume of tufa lake group was achieved by summing the products of pixel unit area and the water depth of each pixel. As results, the surface water volume of tufa lake group estimated by the optimum model combination was approximately 181,360 m3, and the corresponding R-squared was 0.92. These demonstrated the effectiveness of utilizing UAV-based remote sensing and integrated ANN models to accurately estimate surface water volume of tufa lakes. [ABSTRACT FROM AUTHOR]

• The principle of the absolute hydrostatic leveling system as a means to establish online height datum is proposed. • A non-contact absolute hydrostatic level is designed. • Based on precise measurement of liquid depth, an absolute calibration of the level with an accuracy of 0.031 mm can be achieved. • The validation scheme of AHLS and absolute height accuracy is designed and 2-point AHLS can achieve absolute height with an accuracy of no less than 0.05 mm within a 10 m range. The fourth generation light source HEPS under construction in China demands higher alignment accuracy. However, it is difficult to improve height accuracy based on the overlap method of geometric and tracker leveling. Based on the study of hydrostatic leveling systems for ground settlement monitoring, this paper proposes a new method, Absolute Hydrostatic Leveling System (AHLS), for establishing height datum. The principle of establishing height datum for AHLS is described in detail, and it is emphasized that absolute calibration of the level is crucial for implementing this plan. A set of absolute calibration methods for non-contact absolute hydrostatic level is proposed, including measuring key dimensions of the level and precise measurement of liquid depth. The absolute calibration accuracy reaches 0.031 mm. The height accuracy of validating an AHLS between two points within 10 m using a laser tracker is more than 0.05 mm. The results demonstrate the feasibility of using AHLS to establish absolute height datum with high precision. With this method, the absolute height of each point can be obtained independently without any accumulated errors, allowing the establishment of height datum with high precision on a large scale. This approach can be used in the next generation of accelerator devices and also represents a novel method for achieving high-precision vertical monitoring. [ABSTRACT FROM AUTHOR]

In this paper, to improve the pose measurement accuracy of the Time-of-Flight (ToF) camera for space non-cooperative targets, a pose estimation method based on ORBFPFH Simultaneous Localization and Mapping (SLAM) with effective integration of strength and depth measurement information is proposed. The primary process of the method is as follows: First, a unique ORBFPFH Bag of Words (BoW) model for space targets is trained based on the ToF image dataset of spacecraft; Secondly, the pose of the non-cooperative space target is tracked based on the ORBFPFH feature and optimized using the pose graph; Then, based on the ORBFPFH BoW model, loop closure is detected to reduce the cumulative error. Finally, the proposed method is tested on the ToF image dataset: compared with the advanced ORB-SLAM2 algorithm, the proposed method has a minor translation error and rotation error on the test data, with a mean translation error less than 0.144 m and mean rotation error less than 0.642°. The test results show that the proposed method can improve the pose estimation accuracy of space non-cooperative targets, achieve a better 3D point cloud reconstruction effect, and provide technical support for space applications such as rendezvous and docking of non-cooperative spacecraft. © 2001 Elsevier Science. All rights reserved [ABSTRACT FROM AUTHOR]

[Display omitted] • A new method for mobile measurement of RCSs based on a UAV platform is proposed. • A self-made UAVB instrument provides deep, turbidity, flowing river underwater cross-section measurement. • The UAVB can improve the accuracy of UAV images in calculating discharge. Accurate river cross-section (RCS) data is critical for hydrological research and applications; however, in most rivers, hydrographic stations are extremely limited and RCS data are scarce. A new method for mobile measurements of RCS is herein proposed based on an unreviewed aerial vehicle (UAV) platform, i.e., using UAV aerial survey to obtain above-water cross-sections and a self-made UAV bathymetric instrument to attain underwater cross-sections. Underwater cross-sectional measurement is the focus of this paper, namely UAV bathymetry (UAVB). The effectiveness of this method has been verified in rivers with different widths, water depths, turbidity, and flow velocities. The results show that the UAVB cross-section is consistent with the underwater cross-section measured in the field via conventional surveying. The surface velocity is the main factor affecting the accuracy of UAVB, and the corresponding measurement accuracy is ～4%, ～8%, and ～18% of the actual water depth when the surface velocity is less than 1 m/s, 1–2 m/s, and greater than 2 m/s, respectively. From the combination of hydraulic parameters obtained by UAV aerial survey and the calculated discharge results of three types of RCSs (measured cross-section, UAVB cross-section, and generalized cross-section), our results indicate that discharge calculated from the measured cross-section has the highest accuracy with a mean relative error (MRE) of ～5%, followed by the UAVB cross-section with MRE of ～15%, and the generalized cross-section has the worst accuracy with MRE ～35%. [ABSTRACT FROM AUTHOR]

This paper uses physics-informed neural networks (PINNs) to simultaneously determine nearshore water depths and wave height fields based on remote sensing of the ocean surface with limited or sparse measurements. Two methods that integrate the knowledge of water wave mechanics and fully connected neural networks are introduced. The first method utilizes observed wave celerity fields and scarce measurements of wave height as training data. The model performance was examined with linear waves over an alongshore varying barred beach and nonlinear waves over an alongshore uniform barred beach. The second method uses scarce wave height and water depth measurements as training points, and the model performance was investigated with water waves over a circular shoal and the alongshore varying barred beach. One advantage of applying PINNs to solve bathymetry inversion problems is that wave height and bathymetry can be simultaneously estimated by PINN models. Thus, the impact of wave amplitude dispersion on depth inversion in nonlinear wave systems can be considered without measuring the entire wave height field. Overall, this study demonstrates the potential of the inverse PINN model as a promising tool for estimating nearshore bathymetry and reconstructing wave fields using observations from different remote sensing platforms. • Inverse PINN models were developed by integrating the knowledge of wave mechanics and fully connected neural networks. • The developed PINN models can map bathymetry and wave fields with limited field observations as training data. • The effect of wave nonlinearity can be embedded in PINNs to solve depth inversion problems. • Physics-informed deep learning is a promising tool for bathymetry retrieval from remote sensing data. [ABSTRACT FROM AUTHOR]

Convergence of sensing and communication in the same architecture is being considered for implementation in the future sixth-generation (6G) networks due to spectrum congestion and cost efficiency. This paper presents an integrated architecture for time-of-flight (ToF) depth sensing and optical communication simultaneously based on Hamiltonian coding function. The feasibility and performance of this framework are verified by theoretical simulation and experiments. Compared with sinusoid coding scheme, the proposed system based on single-frequency Hamiltonian coding modulation achieves a depth measurement accuracy of tens of millimeters and zero error code in communication, and the data rate 20 Mbps. By developing a multi-frequency Hamiltonian coding fusion algorithm, not only the maximum unambiguous range is increased from 15 m to 60 m, but the average ranging precision is improved to 4.46 mm as well. Experimentally, information of 1000 bits carried by single-frequency is demonstrated. Multi-frequency fusion system can accommodate three times that of single frequency. Within the maximum measurable experimental scope, the value of communication bit error rate (BER) always tends to be zero, under 7% pre-forward error correction (pre-FEC) limit of 3. 8 × 1 0 − 3 . • Integrated framework of time-of-flight depth sensing and optical communication based on Hamiltonian coding is proposed. • The framework enables both high precision ranging (7.5mm@2 ∼ 4m&K=5) and 20Mbps data rate based on single-frequency modulation. • A multi-frequency Hamiltonian coding fusion algorithm is proposed, the maximum unambiguous range is extended from 15m to 60m • Experimentally, the ranging precision is beyond 2 times and the communication capacity is 3 times that of single frequency. [ABSTRACT FROM AUTHOR]

Because of the autonomous underwater vehicles' (AUVs') slow motion and insufficient excitations, monocular visual-inertial odometry (VIO) systems for AUVs still have large-scale errors and a lengthy initialization period. In this paper, we present a relative-depth-aided monocular visual-inertial odometry (RD-VIO) system based on two innovative methods: Inertial Measurement Unit (IMU)-depth joint initialization and relative depth tightly coupled with visual-inertial. The RD-VIO performs reprojection bundle adjustment with dynamic weight factors for visual residuals. Depth measurements acquired by depth gauge or pressure sensor are compensated with reliable inter-image IMU pre-integration to account for different sensor frequencies. Also, we adopt an IMU-depth joint initialization using relative depth measurements and IMU excitations to estimate the scale and gravity direction together, which captures the complete AUV motion changes, improving scale estimation and decreasing initialization time. To reduce scale drift and improve global accuracy and consistency, a tight coupling of relative depth and visual-inertial in the RD-VIO is employed to optimize the AUV pose from depth measurements. Using two open-source datasets and our experiments from Sanya, we evaluated the performance of RD-VIO. The evaluation results show that the proposed system can achieve a more accurate trajectory than the state-of-the-art algorithms with less system initialization time and scale error. [ABSTRACT FROM AUTHOR]

• A single-band unmanned shipborne bathymetric LiDAR. • A two-channel receiving system for improvement of detection ability to the echo signals from water bottom. • The polarized optical systems for suppression of the laser echo energy from the water surface based on the polarization state difference of the laser echo between from water surface and from the water bottom. When a bathymetric LiDAR (Laser Detection And Ranging) onboard unmanned ship is close to the water surface less than 50 cm, the laser echo energy from the water surface is much higher than that from the water bottom. This phenomenon causes a large dynamic range of echo signals that is output from the PMT (Photomultiplier Tube) detector, resulting in that the echo signal from the water bottom cannot correctly be detected in shallow water. For this reason, this paper proposes an optics system to suppress the amplitude of the echo signal from water surface through suppressing the laser echo energy. A two-channel receiving optical system, which receives echo signals from shallow water and deep water is designed and implemented, and then a polarized optical system is designed to embedded inside to suppress the laser echo energy from the water surface. The verifications are carried out through three sets of indoors experiments, and three sets of outdoors experiments. The experimental results demonstrate that the proposed system can effectively suppress 80.7% of the amplitude of the echo signal from the water surface when the voltage control of PMT detector is 0.40 V, which can largely improve the detection ability of the echo signals from water bottom in shallow water. [ABSTRACT FROM AUTHOR]

• A 3D measurement method of bubbles through the use of edge gradient segmentation by a single light field camera. • A 3D reconstruction method of bubbles with orthogonal dual light field cameras. • Influence of the bubble size on the bubble depth measurement was revealed. Based on the light field imaging technology, a three-dimensional(3D) measurement method of bubbles through the use of edge gradient segmentation (TMBEGS) is proposed in this paper. From the characteristic that the bubble edge image has great gray gradient, the coordinates of the bubble edge pixels are determined. The depths of the edge pixels are further derived by evaluating the sharpness of the edge pixels in the refocused light field images. On this basis, the depth coordinate of the bubble is calculated by averaging the depths of all edge pixels, and the 3D measurement of the bubble is then achieved by combining the centroid coordinate and equivalent diameter of the bubble. Finally, experiments are carried out to evaluate TMBEGS on a calibration setup and a bubbling bed experimental device. Results indicated that the relative errors of the bubble diameter and depth by TMBEGS are less than 1.18 % and 5.93 %, which are better than 2.99 % and 17.51 % by the existing method, respectively. On the bubbling bed experimental device, the equivalent diameter of bubbles is increased by 5.69 % compared with the existing method, and the standard deviation of the bubble depth is less than 1.78 mm, which is 21.3 % lower than the existing method. With the increase of the bubble equivalent diameter, the bubble surface deformation intensifies under the effects of the bubble surface tension, viscous force, and inertia force, which affects the imaging quality of the bubble, and reduces the measurement accuracy of the bubble edge and depth. These results illustrated that TMBEGS has high measurement accuracy of the bubbles and is capable of charactering the bubbles in the gas–liquid two-phase flow system. [ABSTRACT FROM AUTHOR]

• Drone-borne GPR can be deployed to measure shallow freshwater bathymetry. • To efficiently map bathymetry, the flight altitude should be limited to 0.5 m. • Bathymetry measured with drone-borne GPR showed an accuracy better than 0.1 m. • GPR outperformed sonar in measuring bathymetry of shallow vegetated waterbodies. Bathymetry of inland water bodies is essential for river maintenance and flood risk management. Traditionally, in shallow water bodies, bathymetry is retrieved by operators wading through the water body with Real Time Kinematic (RTK) Global Navigation Satellite System (GNSS), whilst in deeper waters, it is retrieved with sonar instruments on manned or unmanned boats. In the past, researchers have documented the use of Ground Penetrating Radar (GPR) on boats (i.e. water-coupled GPR) for monitoring the bathymetry of frozen and non-frozen water bodies. Furthermore, GPR has been used on helicopters for monitoring ice and snow thickness. However, deployment of GPR on board Unmanned Aerial Systems (UASs) in non-frozen inland water bodies with electric conductivity higher than 100 μS/cm (as is common in most inland waterbodies in non-polar regions) is unexplored. In this paper, we document the possibility to use drone-borne and water-coupled GPR in several cross-sections located in three different waterbodies (1 lake and 2 rivers) in Denmark. These waterbodies had different bed sediment materials and vegetation conditions, an electric conductivity varying from 200 to 340 μS/cm and depths up to 2.5 m. Drone-borne GPR showed accuracy similar to water-coupled GPR when compared to RTK GNSS ground-truth measurements, with a Mean Absolute Error (MAE) of approx. 8 cm. The only limitations of drone-borne GPR were i) more restrictive minimum depth requirement (typically 0.8–1.1 m for drone-borne GPR, while 0.3–0.4 m for water-coupled GPR) ii) requirement to fly the GPR antenna at altitudes of approx. 0.5 m above the water surface to avoid high spreading losses and strong surface clutter events hiding the signal. Finally, GPR measurements were benchmarked against traditional sonar measurements, showing that GPR measurements significantly outperform sonar measurements in waterbodies with medium or high density of aquatic vegetation. [ABSTRACT FROM AUTHOR]

• UAV-acquired overlapping images were applicable to obtaining water depth map of clear tufa lakes. • Single bathymetric methods caused depth anomalies in water areas with uniform texture or shadows. • Photogrammetric and spectral-based bathymetric methods were combined using neural network (NN). • NN-based bathymetric methods realized fully-covered and non-contact bathymetry of tufa lakes. • Shallow NN model achieved highest bathymetric accuracy while deep NN model added more details. Accurate and updated bathymetric data is of great significance for the management and protection of alpine tufa lakes. In recent years, unmanned aerial vehicle (UAV)-borne optical remote sensing has become a cost-effective technique for obtaining water depth of small and clear waters like tufa lakes. UAV-based bathymetry can be categorized into photogrammetric approach and spectrally derived approach. Photogrammetric bathymetry is contactless but invalid in water areas with uniform texture, while spectral-based bathymetry requires a large amount of in-situ depth measurements. In this paper, we combined the strengths of the two bathymetric methods to retrieve the depth of clear tufa lakes using neural networks. The surface elevation and orthoimage were first produced from UAV-acquired overlapping images, and then water color-depth tie points were sampled in the orthoimage and refraction-corrected bathymetric map. Next, the shallow and deep neural networks were separately used to train the regression models for predicting water depth. Lastly, the combined bathymetric methods were compared with the single ones in terms of effective spatial coverage and bathymetry accuracy. The results indicated that the combined methods were superior to single bathymetric methods in fully-covered bathymetry of clear tufa lakes. The shallow neural network-based model achieved the highest accuracy, with the coefficient of determination (R2) of 0.91 and the Root Mean Square Error (RMSE) of 1.12 m, whereas the deep neural network-based model increased the details of water depth distribution. [ABSTRACT FROM AUTHOR]

How did the Arctic seabed become a political space despite its almost complete inaccessibility to humans? While we can explain the causes of this in geopolitical and economic terms, theorizing the process is more difficult. This article argues that spatial constructions of the Arctic seabed emerge from the interaction among human actors, technologies, and the material environment. This interaction generates representations which are then fed into the overall process of spatializing the seabed. By highlighting the role of technology, this paper offers a way of relating human agency and materiality in the construction of oceanic space. The case study of bathymetry in the ongoing disputes over the Arctic continental shelf illustrates how technological and scientific advancements are embedded into global politics and themselves cause evolutions in the spatial construction of the seabed. [ABSTRACT FROM AUTHOR]

Assessing corrosion is crucial in the petrochemical and marine industries. Usual ultrasonic methods based on pulse-echo and guided waves to detect corrosion lack of precision and struggle in structures with a complex shape. In this paper, a complementary and sensitive ultrasonic method based on coda wave interferometry is presented to detect and quantify thickness loss caused by saltwater corrosion of a steel sample. The method consists in exciting the sample and measuring periodically the scattered coda signal. Correlation of the coda signal with a reference taken for the sample initial state permits the monitoring of corrosion spread with a high accuracy. A laboratory experiment is conducted with two steel samples immersed in saltwater with coda and temperature measured simultaneously. One of the samples is protected from corrosion and is used as a control sample to determine the influence of temperature on the coda signals. It is shown that the coda signals on the corroded sample can be temperature-corrected using the temperature measurement only. A control sample is not needed. A good correlation is found between a parameter quantifying the stretching of the coda over time and the corrosion surface, which is monitored with a camera. Finally, a simple theoretical model of coda signal is proposed to quantify the real-time average corrosion rate during the experiment with a sub-micrometric precision. The estimated final average corrosion depth is validated by independent depth profile measurements. The uncertainties and sensitivity of the presented method are investigated. • An ultrasonic method is presented to monitor saltwater corrosion on steel. • The method, based on coda wave interferometry, is more sensitive than standard ultrasonic methods. • The coda dependence to temperature is corrected using a reference sample or temperature. • A laboratory experiment is conducted in saltwater with temperature and coda measurements. • The temperature-compensated coda stretching factor correlates with the early corrosion surface. • The instantaneous corrosion depth is quantified with a simple coda model and validated. [ABSTRACT FROM AUTHOR]

The propagation of plane incident waves over a long submerged uniform rectangular structured ridge protruding from the sea bed is considered. The ridge is comprised of a uniform closely-spaced array of vertical barriers between which the fluid is allowed to flow. In addition to the height and width of the ridge, the orientation and thickness of the barriers are adjustable design parameters. Particular interest centres negative refraction of obliquely-incident waves, shown to be possible provided the barriers extend sufficiently close to the surface. A key result is that the modulus of reflection and transmission coefficients are symmetric functions of the incident wave heading and the barrier orientation. This implies perfect transmission of wave energy for thin barrier elements at incident angles that are the reverse of the barrier orientation, extending the result of Porter (2021) to structured plate arrays of any submergence. The paper details two mathematical approaches to the solution of the problem, one for general barrier orientations and the other for a specific orientation where special treatment of the resulting problem is required. Numerical computations compare favourably with a variety of established results and good agreement with an existing shallow water approximation is confirmed for sufficiently long wavelengths. • A full depth-dependent solution to scattering of oblique waves by a water wave metamaterial comprised of thin vertical barrier elements is described. • The reflected and transmitted wave amplitudes are shown to be symmetric in both wave direction and barrier orientation. • Perfect negatively-refracted transmission is possible for all wave frequencies for certain metamaterial ridges and wave headings. • Certain designs of structured ridge are shown to have high broadbanded reflective qualities. [ABSTRACT FROM AUTHOR]

This paper assesses the possibility of measuring small, shallow defects in low thermal diffusivity materials with existing pulse thermography techniques. Defects like these are commonly introduced in additive manufacturing (AM), and their presence can cause inconsistencies in the mechanical properties of the final part. An axisymmetric, numerical model was created to simulate the heat transfer within these low thermal diffusivity structures during flash thermography. Deviations from the ideal conditions commonly used in flash thermography models such as conduction across the flaw and in-depth absorption of the incident pulse were included in the model and their effects on defect measurability were investigated. These nonideal conditions (in addition to free convection) introduce depth measurement errors of >10% even for large aspect ratio defects (such as delaminations). The figures provided quantify the amount of error associated with these individual parameters and can be used to determine if a given thermography system is ideal. The simulation results also demonstrate that traditional 1D thermography models may be used to approximate the depth of a defect with negligible error if the defect has an aspect ratio greater than 6. Smaller defects may also be measured with minimal error. If flash thermography were performed during AM to identify the layers where defects most likely reside, the measurement limits would be even less restrictive. • Nonideal conditions introduce depth measurement errors of >10% even for large aspect ratio defects. • 1D thermography models may be used to approximate defect depth with negligible error if the defect has an aspect ratio >6. • Defects with an aspect ratio greater than 4 may be measured with minimal error. • Defect boundaries are nearly adiabatic boundaries if the ratio of thermal conductivities of the defect and surrounding material is <0.07. • Effects from spectral in-depth absorption cause <15% error if at least 95% of the irradiation is absorbed above the defect. [ABSTRACT FROM AUTHOR]

The morphology of the southwestern North Sea is greatly influenced by sand banks. With this paper these features have been identified by analysing bathymetric data and estimating their geometric properties. This allowed an assessment of the dimensions of the structures and enabled an economical evaluation of the associated sand resources. In fact, there are several aspects that are of economic interest, which include the sand as a potential exploitable resource and the interaction of the sand banks with submarine infrastructures, such as cables, pipelines and shipping channels. Therefore, this study aimed to evaluate and compare several oceanographic and sedimentary factors on the formation and distribution of the sand banks in the southwestern North Sea to create a prediction model for the bank occurance. The main focus was on the relation between critical shear stress of the bedload and the shear stress of currents and waves and it's effects on the sand bank formation. It has been figured out that the maximum bed shear stress needs to exceed the critical shear stress by a factor of nine to allow sand bank formation to a greater extend. Thus, this study contributes new knowledge about sand banks in the southern North Sea. • The ratio between bed shear stress and critical shear stress of the sediment is critical for sand bank formation. • Significant sand bank formation occurs, when the maximum bed shear stress exceeds the critical shear stress by a factor of 9. • The degree of tidal reversal is subjected to have great effects on the sand bank occurance. • The sand bank prediction achieves similar accuracies to existing models, but is more accurate in certain areas. [ABSTRACT FROM AUTHOR]

• A method to measure depth based on single camera was proposed. • A μLED with a length of 40 μm was used to test this system. • The uncertainty was analyzed. Highly precise measurement of depth in micro meter is very important in many fields. Many methods measuring depth for spherical objects have been proposed. However, few of them can measure the depth for plane objects, such as μLED, which has advantages in brightness, power consumption and response speed. The depth measurement is one of the key technology for the transfer printing of μLED. In this paper, we proposed a method measuring depth for μLED array using single camera. The proposed method was calibrated by a precision stage. The uncertainties, such as camera distortion, camera tilt, curve fitting and surface roughness of μLED were estimated. The results showed that the relative standard uncertainty in depth position was about 2.2%. This showed that the proposed system was very stable and repeatable. [ABSTRACT FROM AUTHOR]

• Method for hydraulic model derived stage fall discharge. • Spatially distributed variational calibration of a hydraulic network model. • Multi-mission altimetry data assimilation. • Stage-fall-discharge laws amenable to satellite altimetry. Current and forthcoming altimetry satellites provide increasing hydraulic visibility of river surface variabilities. However, due to unobservable river bathymetry and friction, as well as the sampling and quality of remote sensing data, discharge estimation remains a challenging problem. This paper proposes a new rigorous methodology to estimate stage-fall-discharge laws at any point of a hydrographic network including backwater affected reaches. This methodology is adapted to operational estimation of discharge from multi-mission satellite altimetry data. The cornerstone of the method is to take advantage of meaningful hydraulic signatures, including water surface slopes, simulated by a river network model optimally combined with multi-satellite noisy observations. This optimal combination of heterogeneous multi-source data with a river network model is achieved through variational data assimilation performed using the DassFlow-HiVDI hydraulic model inflowed by MGB regional hydrological model. It is newly applied to the large and complex Negro-Branco River network in the Amazon basin. An effective model is obtained by variational calibration using Jason-3 and Sentinel-3A and -3B altimetry observations between February 2016 and May 2019. A fairly good fit bellow 1 m for 80 % of the altimetric observations is obtained. Using this hydrodynamic model as a fine spatio-temporal extrapolator of hydraulic quantities, and in particular of multi-scale water surface slope signatures, the parameters of a general SFD law, as well as the uncertainties estimations, can be constrained at any location within the river network domain using a Bayesian optimization method. This methodology is tested over 4 virtual stations representing various hydraulic complexities. Accurate discharge estimates and meaningful SFD parameters are obtained compared to those of the reference low Froude model at these locations. Analyses are also performed on a reference case with fine-scale bathymetry data of the Garonne River, France. The strength of the method lies in its applicability to noisy multi-satellite data while ensuring physical consistency. It should be applicable in real time to any river basin, using nadir altimetry only or combined to the forthcoming SWOT satellite data. Moreover, the method allows to take full advantage, via the hydrodynamic model, of variable water masks observations and physical segmentations of river networks. The method is implemented in the open source hydrodynamic data assimilation platform DassFlow. [ABSTRACT FROM AUTHOR]

Numerous estuaries worldwide have been modified in the past decades by human interventions. The shoreline and bathymetry in the Pearl River Estuary (PRE) have changed greatly over the past 40 years due to the influence of land reclamation and waterway dredging, which have resulted in the corresponding adjustment of its hydrodynamics. Utilizing the ROMS numerical model, this paper studies the hydrodynamic responses to changes in shoreline and bathymetry in the PRE from 1971 to 2012. The results show that, on one hand, during neap tide, the change in the shoreline makes the residual current in the West Channel (WC) increase by 0.10 (0.05) m/s at maximum in the surface (near bottom) layer. Therefore, the exchange flow increases by 9.5% and the longitudinal circulation strengthens. The surface isohalines move southward up to 18 km, but the bottom isohalines move northward ∼2 km in the WC and East Channel (EC), which is different from the previous conclusion that the seaward extension of coastlines inhibits saltwater intrusion. The decrease in salinity in the upper layer reduces the upper seaward salt transport, resulting in a larger net landward salt transport from 25.21 × 103 kg/s to 35.44 × 103 kg/s. During spring tide, the changes are relatively weaker, but the direction of salt transport changes to seaward and the net seaward transport also increases. Moreover, the change in shoreline reduces the water area and volume in the PRE by 21.3% and 15.6% respectively, which causes a reduction of 11.3% (17.1%) in tidal prism during spring (neap) tide. The wave celerity is enhanced (>23%) and the amplification of semidiurnal tide is strengthened (>20%) in the WC and West Shoal (WS). The reduction in tidal prism together with the strengthened reflection of tidal waves with a larger phase lag between elevation and velocity of M 2 tidal component cause a significant decrease of 19.0% in tidal energy flux entering the PRE. However, the tidal range increases by ∼0.30 m (mainly due to the increase in M 2 tidal amplitude) in the EC , which is induced by lower tidal energy dissipation there. On the other hand, during neap tide, the change in bathymetry greatly enhances the bottom landward residual current whose peak value increases by 80% in the WC , thereby increasing approximately 14 km of the intrusion distance of saline water, enhancing the exchange flow by 27.5% and strengthening the longitudinal circulation. The net landward salt transport increases to 38.39 × 103 kg/s. The results during spring tide are similar to those during neap tide but with smaller changes, and the net seaward salt transport decreases. Moreover, the wave celerity is slightly reduced (<8%) and the amplification of semidiurnal tide is also decreased (<10%) in the WC and WS. Meanwhile, the change in bathymetry only decreases the water volume by 4.7%, leading to a relatively smaller effect on the tidal prism, and it strengthens (weakens) the reflection of tidal waves in the West Shoal and Middle Shoal (WC and EC), resulting in a slight reduction in tidal energy flux entering the bay. In the WC , the tidal range is basically unchanged since the increased tidal energy flux is offset by the increased dissipation. The quantitative results obtained in this study may provide some references for the development and protection of the PRE and other estuaries that are subject to strong human interventions. • Seaward extension of coastlines increases tidal range, wave celerity and saltwater intrusion. • Change in bathymetry increases ∼14 km of the intrusion distance of saltwater. • Change in bathymetry enhances exchange flow by 27.5%, reduces tidal energy flux by 2.4%. [ABSTRACT FROM AUTHOR]

This paper presents the geomorphic classification and bathymetry (at 100 m) of 12 major floodplains along a 900 km reach of the middle-lower Amazon River (Manaus – Monte Alegre; total floodplain area of 5164 km2), based on the inundation frequency (IF) derived from 36 yr of Landsat data. Using a mathematical relationship between IF and surveyed depth at the Curuai floodplain in June 2004, this IF-depth model is applied across floodplains of the middle-lower Amazon to estimate bathymetry. The applicability of the model is justified by similar grain size distribution (dominantly silt and clay) of sediment in the surface water of floodplain lakes (the main materials constructing the floodplains), as well as a hydrogeomorphic classification of this reach: seven floodplains lying on the alluvial plain dominated by the Amazon-flood pulse (Type I), three floodplains incised in valleys dominated by sediment-poor upland tributaries (Type II) and two floodplains of mixed types. This classification is used to distinguish the sensitivity of floodplains to the IF-depth model, where Type I floodplains of higher sensitivity provide a more accurate depth estimation. The bathymetry for both types is validated with field survey data across eight floodplains (covering over 200 km survey distance) collected in June – July 2016 and adjusted by the difference between mean June 2004 and June/July 2016 water level. Correlation coefficients of 0.87 (Type I) and 0.94 (Type II) indicate a strong relationship between estimated and measured depth for both floodplain types, while the root mean square error of 1.03 m (Type I) and 1.02 m (Type II) suggest that bathymetry is estimated to around 1 m error, equivalent to 10.9% and 10.8% of maximum water level variability, respectively. We offer the first field-validated and complete bathymetry map for the middle-lower Amazon River with accuracy that can be used to evaluate the role of floodplains in influencing biodiversity, sedimentation, flood control and biogeochemical cycling. • First field-validated floodplain bathymetry of the middle lower Amazon River • Depth estimation is based on inundation frequency and field survey data. • Floodplain classification based on morphology, geology and flooding dynamics [ABSTRACT FROM AUTHOR]

Shape-from-focus depth measurement is widely used in equipment manufacturing, biomedicine, heritage conservation, engineering measurement, etc. However, the acquisition of multi-focus image sequence is not very flexible and time-consuming in conventional shape from focus. Here, a novel depth measurement from shape from focus method based on ultrafast optical axial scanning was proposed. An electronically tunable lens was used to achieve high-speed focus shift, by synchronizing a CCD with the electronically tunable lens, multi-focus image sequence can be acquired at high speed (up to 2.5 ms). The focusing area of each multi-focus image was extracted by the energy of image gradient operator. Finally, the motionless depth measurement can be achieved. A tilted marker pen was used to test the performance of the depth measurement, the results show that the depth resolution of the proposed method is measured to be ∼ 3.2 cm in a depth range of ∼ 24 cm. The feasibility of the proposed method was verified using misplaced portrait sculptures. This method will further expand the application of depth measurement from shape from focus in human–computer interaction, 3D shape measurement, and augmented reality. [ABSTRACT FROM AUTHOR]

This research investigates the viability of using Machine Learning (ML) for predicting bathymetry. We built and trained several models using ocean features aggregated from multiple sources and predicted bathymetry from the ETOPO dataset at a 2-min resolution. Each model was evaluated to identify a global best fit, however we found that none performed well on a global scale. When training on subsets of the world, we observed that some models performed significantly better, which led to developing a novel model selection technique that identifies the best performing model and most relevant features for a given geospatial coverage. This leads to improved predictions and more reliable results. This model selection technique can be generalized to be applied to any set of models. • Viability of Machine Learning for predicting bathymetry. • Feature-based selective model outperforms global model in bathymetry prediction. • Compared a plethora of Machine Learning approaches. • Divided the world into a set of coverages based on computational expenses. [ABSTRACT FROM AUTHOR]

We present a revised estimate of the maximum depth of the Challenger Deep, generally considered the deepest area of the world's oceans, based on a series of submersible dives conducted in June 2020. These depth estimates are derived from acoustic altimeter profiles referenced to in-situ pressure and corrected for observed oceanographic properties of the water-column, atmospheric pressure, gravity and gravity-gradient anomalies, and water-level effects. We also present comprehensive methods to determine depth from observed pressure using modern standards and estimate the associated uncertainty. For the Challenger Deep, the deepest observed seafloor depth was 10,935 m (±6 m at 95% C.I.) below mean sea level. For this work, the error term is dominated by the uncertainty of the pressure sensor used but we show that the gravity correction is substantial. We compare to these new results other recent acoustic and pressure-based measurements for the Challenger Deep. • 10,935 m (±6 m at 95% C.I.) is the most accurate and precise estimate of the maximum depth of the ocean, to date. • Corrections for gravity anomalies are nearly half the magnitude of steric effects for the Challenger Deep. • Pressure-based depth measurements at sub-meter absolute accuracy seem achievable in near term. [ABSTRACT FROM AUTHOR]