Satellite-Derived Bathymetry (SDB) can be calculated using analytical or empirical approaches. Analytical approaches require several water properties and assumptions, which might not be known. Empirical approaches rely on the linear relationship between reflectances and in-situ depths, but the relationship may not be entirely linear due to bottom type variation, water column effect, and noise. Machine learning approaches have been used to address nonlinearity, but those treat pixels independently, while adjacent pixels are spatially correlated in depth. Convolutional Neural Networks (CNN) can detect this characteristic of the local connectivity. Therefore, this paper conducts a study of SDB using CNN and compares the accuracies between different areas and different amounts of training data, i.e., single and multi-temporal images. Furthermore, this paper discusses the accuracies of SDB when a pre-trained CNN model from one or a combination of multiple locations is applied to a new location. The results show that the accuracy of SDB using the CNN method outperforms existing works with other methods. Multi-temporal images enhance the variety in the training data and improve the CNN accuracy. SDB computation using the pre-trained model shows several limitations at particular depths or when water conditions differ.

In the next generation, the use of dual-frequency Embedded GNSS Chipset in the smart devices, which will be widely used in engineering applications, has been used for the first time in Xiaomi Mi8. Considering this development dynamics, a kinematic test was carried out in the marine environment monitoring with a geodetic GNSS receiver and an android smartphone in Turkey Oyak Port. According to the results of the test, RMSE for horizontal coordinate components were found as 0.0423 m and 5.9493 m for reference solution and PPP-AR solution of geodetic receiver, and reference solution and PPP solution of smartphone, respectively. Moreover, the positional errors of individual epochs were computed as 0.0411 m and 4.6871 m with respect to given order. The solution obtained from Xiaomi Mi8 raw GNSS data with PPP approach provides the Order 2 for hydrographic survey standards IHO S-44 in terms of Total Horizontal Uncertainty (THU).

Sediment characteristics and distribution analysis along the Chandipur Coast in Odisha, India was performed using a variety of techniques that include sedimentary characteristics including variation in grain size, shape and character of quartz grain surfaces (determined in light microscope and electron microscope scanning). Samples were taken from various locations representing high-tide areas and low-tide areas for analysis of the grain size, intended to determine physical properties and textural parameters such as mean, sorting, skewness and kurtosis. Grain size distribution research was conducted to characterize sedimentary transportation behaviours. CM diagram defines the rolling, saltation and graded suspension process for sediment deposition at the beach. Linear Discriminant Function (LDF) indicates the superiority of marine environment with lower deposition areas. Scanning Electron Microscope (SEM) was used to examine the quartz grains to determine the origin of the sediments and to establish the physical and chemical processes that occurred during their period of deposition in recent coastal sediments.

Marine Geodesy will publish a special issue on Seafloor Geodesy and Acoustic Positioning in early 2022. The guest editors will be Prof. Yuanxi Yang from Xi'an Research Institute of Surveying and Ma...

In the present methods to estimate seafloor topography from gravimetric data, some parameters need be computed in advance from the known bathymetric data, which leads some uncertainties in applying the methods. To overcome such uncertainties, an analytical method to estimate the seafloor topography from the vertical gravity gradient (VGG) is introduced in the paper. Based on the expression of VGG generated by a cubic prism, the observation equations for the seabed depth are established firstly. Then, the simulation results show that the observation equations established are solvable. Especially, the piecewise bilinear interpolation is introduced to separate the influence of the far-field anomalous bodies on VGG. In addition, some imitation arithmetic examples are given in order to examine the solvability of the observation equations and estimate the accuracies of their solutions. Finally, an actual seafloor topography located in South China Sea (117.6-118.25°E, 17-17.65°N), is estimated by the method proposed in the paper, and compared with ship depth sounding, the root mean square (RMS) error of bathymetry prediction is 77 m.

Traditionally, geoid models have been validated using GNSS-levelling benchmarks on land only. As such benchmarks cannot be established offshore, marine areas of geoid models must be evaluated in a different way. In this research, we present a marine GNSS/gravity campaign where existing geoid models were validated at sea areas by GNSS measurements in combination with sea surface models. Additionally, a new geoid model, calculated using the newly collected marine gravity data, was validated. The campaign was carried out with the marine geology research catamaran Geomari (operated by the Geological Survey of Finland), which sailed back and forth the eastern part of the Finnish territorial waters of the Gulf of Finland during the early summer of 2018. From the GNSS and sea surface data we were able to obtain geoid heights at sea areas with an accuracy of a few centimetres. When the GNSS derived geoid heights are compared with geoid heights from the geoid models differences between the respective models are seen in the most eastern and southern parts of the campaign area. The new gravity data changed the geoid model heights by up to 15 cm in areas of sparse/non-existing gravity data.

Arctic coasts are sensitive indicators of polar environment change. Here we present the results of a study that examines the coastal morphodynamics of the Calypsostranda coastline in Svalbard (High Arctic) between 2007 to 2017 and compare these short-term changes to previous studies for the period 1936–2007. During the 2007–2017 study period, the study area lost ca. 10,710 m2, at a mean Net Shoreline Movement (NSM) of −1.86 m and End Point Rate (EPR) −0.19 m/yr. Erosion also dominated between 1936–2007, −28,800 m2, at a mean NSM of −4.99 m and EPR −0.07 m/yr. Using EPR and Linear Regression Rate (LRR) parameters, we divide the Calypsostranda coastline into eroding and aggrading zones. The overall pattern of coastline change during the two study periods is similar, but the rate of erosion is higher in the recent interval, reflecting stronger climate-driven processes. Recent climate warming in the study area has been accompanied by an intensification of extreme events such as storms (e.g. ocean swell). The situation is becoming more pronounced due to the progressively reduced period of winter shore ice. Depending on the anemometric conditions, the Calypsostranda coast is modified by wind waves, and consequently longshore currents and associated sediment movement.

Based on hydrological data obtained during the 7th to 9th Chinese National Arctic Research Expeditions in the summers of 2016–2018, the main water structure on the shelf of the northern Bering Sea and the volume and heat fluxes of the Bering Strait throughflow were analyzed. Distinct variability was identified in the three Pacific water masses feeding the strait - Anadyr Water (AW), Bering Shelf Water (BSW) and Alaskan coastal water (ACW). Overall, the temperature and salinity of the entire section increased each year, with 2018 showing significant anomalies, i.e., a temperature anomaly of up to 1 °C and a maximum salinity anomaly of 2. From 2016 to 2018, the extent of the ACW gradually narrowed in the eastern part of this section, while the AW expanded eastward each year. The net volume transport through each of the three sections increased poleward from 1.65 Sv to 2.76 Sv, with the AW increasing from 0 Sv to 1.03 Sv, the BSW varying between 0.52–1.65 Sv, and the ACW gradually decreasing from 1.04 Sv to disappearing completely. The net heat fluxes were also poleward, varying between 25.77 TW and 61.50 TW, and showing a significant increase. Significant variations in magnitude and extent were observed in each water mass of the Bering Strait throughflow, which could produce widespread effects in the Arctic Ocean and the global ocean beyond.

The Port of Saint John is a highly stratified, hyper-tidal estuary that requires frequent hydrographic surveys to ensure that minimum under-keel clearances are maintained and to monitor dredge operations. The potential achievable accuracy and efficiency of a multibeam sonar survey correlates to the knowledge of the physical oceanographic conditions of the harbour. A high-resolution baroclinic hydrodynamic model of the Port of Saint John was constructed to understand the dynamic physical oceanographic environment over four periods representing the limits in river flow conditions. The model provides time-varying outputs of temperature and salinity at predefined depth intervals over the domain. Sound speed is derived from the model output and is used for ray-tracing multibeam sonar data and survey planning to minimize refraction errors. Ray-tracing depth error statistics are calculated from Moving Vessel Profiler (MVP) temperature and salinity casts and used to evaluate the model skill. Results demonstrate that the model can be used to replace observed sound speed profiles and stay within depth accuracy specifications within a swath width of 60 degrees, or more, for most of the year throughout the harbour. Uncertainty increases for swath widths of more than 55 degrees during the most severe stratification of the spring freshet.

An essential role of the FAMOS international cooperation project is to obtain new marine gravity observations over the Baltic Sea for improving gravimetric geoid modelling. To achieve targeted 5 cm modelling accuracy, it is important to acquire new gravimetric data, as the existing data over some regions are inaccurate and sparse. As the accuracy of contemporary geoid models over marine areas remains unknown, it is important to evaluate geoid modelling outcome by independent data. Thus, this study presents results of a shipborne marine gravity and GNSS campaign for validation of existing geoid models conducted in the eastern section of the Baltic Sea. Challenging aspects for utilizing shipborne GNSS profiles tend to be with quantifying vessel’s attitude, processing of noise in the data and referencing to the required datum. Consequently, the novelty of this study is in the development of methodology that considers the above-mentioned challenges. In addition, tide gauge records in conjunction with an operational hydrodynamic model are used to identify offshore sea level dynamics during the marine measurements. The results show improvements in geoid modelling due to new marine gravimetric data. It is concluded that the marine GNSS profiles can potentially provide complementary constraints in problematic geoid modelling areas.