Scientific management of coral reefs is a global research topic due to their latent economic value and ecological significance. This research benefits from optical and acoustic remote sensing ...technology with high spatial resolution, sufficient coverage, and stable repeatability. However, each sensor with its own set of limitations, such as insufficient penetration ability, limited sensor resolution and range, which often hinder their applications in the precise classification of coral reef habitats. To address these issues, a novel scheme integrating airborne laser bathymetry (ALB), multibeam echo sounder (MBES) and the multispectral image is designed to serve large-scale and high-precision coral reef habitat sediments research. This scheme focuses on valuable attribute mining, inconsistent coverage, feature default, and redundancy according to multi-source data used in engineering demands. After per-system pretreating, numerous properties, including band, waveform, intensity, terrain, and derivative characteristics, are extracted and quantitatively analyzed to be responsible for habitat description. Subsequently, a complete seabed terrain is generated using the LightGBM regression model to establish the conversion relationship between satellite images and depth. Eventually, a new benthic habitat sediments classification method called RF-SAPSO-LightGBM is introduced with a powerful generalization ability. The unique functions of automatic default feature completion and optimal parameter search improve the discrimination ability of complex sediments. The results indicate that the new method outperforms five other approaches in sediment classification accuracy, and the combination of multi-source data provides more extensive coverage and higher accuracy with an overall of 87. 9%. In comparison, the accuracy values for multispectral image and terrain data alone are 74.5% and 54.7% respectively.
•Optical-acoustic sensors were more effective when used together rather than separately for mapping coral reef habitat.•The SAPSO algorithm for LightGBM parameter optimization improved the sediment classification accuracy by 7.4%.•Feature completion effectively improved the accuracy of coral reef habitat mapping.•The RMSE of the derived depth by the LightGMB regression model reached 0.89 m.
This work focuses on the characterization of background levels of heavy metals (As, Cd, Cr, Cu, Hg, Ni, Pb, Zn) in seabed marine sediments of the central Adriatic Sea, collected up to 10 km far from ...the Abruzzo region coastline (Italy). The used approach follows the guidelines established by the Decree of the Italian Ministry of Environment, n. 173/2016, concerning the determination of threshold values of metal concentration, and including only samples with low or absent toxicological content. A statistical analysis, using the adjusted Tuckey's boxplot to identify the percentiles and potential outliers, was performed. The background concentrations were calculated as the values of the 90th percentile of distribution, according to the national regulation. This study represents the first attempt to calculate the background levels of marine sediments done at regional level in Abruzzo. A few outliers have been found, and interpreted as potential anthropic contamination.
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•Background of heavy metals in central Adriatic Sea, according to environmental laws.•As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn have been quantified in 110 sediment samples.•Anomalous values have been identified through univariate and multivariate statistics.•90th percentile has been used to identify the metal local background L1loc.
Abstract
In this paper, a comprehensive detection device for the mechanical properties of seabed sediments and shallow gas is designed, which is mainly composed of the seabed sediment mechanical ...properties detection part, the shallow gas detection part and the ultrasonic wireless transmission part. The mud water gas separation structure of the shallow gas detection part separates the shallow gas from the mud water, and then the methane concentration in the shallow gas is measured by the non-dispersive infrared methane sensor, which realizes the collection of the submarine shallow gas and the automatic real-time monitoring of the concentration. The measurement of the mechanical properties of seabed sediments realizes the real-time measurement of the three parameters of cone resistance, sidewall friction and pore water pressure, which characterize the mechanical properties of seabed sediments, through strain-sensitive elements. The ultrasonic wireless data transmission part is mainly for the data detected by the mechanical properties of the seabed sediments to be wirelessly transmitted to the sensor placement room through the ultrasonic transducer across the mud-water-gas separation structure. Finally, the data measured by the two parts are transmitted to the mother ship through the cable located in the sensor placement room. The experimental results show that it has the ability to comprehensively detect the mechanical properties of seabed sediments and shallow gas, and has strong operability.
Despite recent increase in microplastics-related studies, little is known about their abundance in seabed sediment areas. However, the quantity of microplastics (MPs) in sediments is imperative for ...an overall understanding of worldwide MPs pollution. To address the above-mentioned gap, this study was performed on 43 seabed sediment stations from the Marmara Sea of Turkey. Studied stations vary between marine (MRN), pier (PIER), stream (STR), sea discharge (SD), and deep-sea discharge (DSD) stations. Collected seabed sediment samples were analyzed for MPs abundance, shape, size and color distribution. Besides, an investigation on the effect of sea depth on MPs' total abundance, size, and shape was investigated using Pearson's and Spearman's product momentum correlation coefficient. Empirical data analysis showed that the highest MPs abundance at STR stations changed between 1956.5 ± 3031.8 and 3256.2 ± 5168.2 particle/kg (dry weight: d.w.) for small MPs particles (SMP) and large MPs particles (LMP), respectively. Contrarily, the lowest abundance was found as 224.8 ± 423.05 and 287.68 ± 218.6 particle/kg (d.w.) for SMP and LMP fractions, respectively at DSD stations. The MPs abundance were found at 5 categorized stations in the following order; STR>PIER>MRN>SD>DSD, noted that the highest MPs quantity was found at STR-6 station located in Golden Horn. The isolated MPs were predominantly filament and fragment in shape (42.34 ± 6.10% and 33.91 ± 6.92%), blue and white in color (40.46 ± 4.66% and 24.75 ± 3.83%). Mean MPs abundance was determined to be 1957.37 ± 4079.96 particle/kg (d.w) at all 43 stations and sizes between 1 and 5 mm was found to be predominant at depths between 5 and 71m. Furthermore, a negative correlation was found between sea depth and parameters such as total MPs abundance, shape, and size. The overall results revealed the widespread presence of MPs in the seas surrounding Istanbul.
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•This paper focuses on microplastics in sea-sediments in the coastal areas of Istanbul.•Marine, pier, stream and sea discharge stations were comprehensively studied.•The highest microplastics were found for stream station pouring into Golden Horn.•The lowest microplastic particles were obtained for deep sea discharge stations.•Alarming microplastic pollution was noticed in the Golden Horn located stations.
Seabed sediment classification has important applications in ocean engineering and submarine pipeline design. This paper proposed the dimension-invariant residual network to improve the seabed ...sediments classification accuracy. The dimension of each channel of the feature extracted from the dimension-invariant residual block is the same as the original image. Compared with down-sampling, each feature vector has more feature parameters, which can improve the accuracy of seabed sediments classification. Shortcut connections were introduced in the proposed network, which can make the network easier to optimize and achieve good performance by using only a not very deep network. It also has a lower complexity compared to powerful classifiers like Transformer and has a better performance in small-scale seabed sediment classification. And to improve the accuracy of seabed sediment classification without consuming too much time for training the classifier, the network parameters optimization method was proposed in this paper. Recording the classification accuracy and training time of the network with these different parameters. Determining the parameters of the network by the proposed optimization method. The proposed classification model and optimization method were validated by using the side-scan sonar images, acquired from the area around the Shandong Peninsula of China. The layers and convolutional kernel sizes were determined to be 8 and 3, respectively. The classification accuracy of overall, rock, sand, and mud of the dimension-invariant residual network model were 97.83%, 94.04%, 97.80%, and 98.02% respectively. In comparison with state-of-the-art classifiers, the experimental results demonstrated that the proposed classification model achieved better performance, and the network parameters optimization method enables the network to achieve satisfactory classification accuracy while spending less time. The proposed classification model and network parameters optimization method show great potential in seabed sediments classification, which can also be extended to the task of underwater target recognition in future research.
•The dimension-invariant residual network identifies seabed sediments more accurately.•The dimension-invariant residual block can retain more features than the traditional.•Network parameter optimization methods can balance the training time and performance.
An ability to estimate the large-scale spatial variability of seabed sediment type in the absence of extensive observational data is valuable for many applications. In some physical (e.g., ...morphodynamic) models, knowledge of seabed sediment type is important for inputting spatially-varying bed roughness, and in biological studies, an ability to estimate the distribution of seabed sediment benefits habitat mapping (e.g., scallop dredging). Although shelf sea sediment motion is complex, driven by a combination of tidal currents, waves, and wind-driven currents, in many tidally energetic seas, such as the Irish Sea, long-term seabed sediment transport is dominated by tidal currents. We compare observations of seabed sediment grain size from 242 Irish Sea seabed samples with simulated tidal-induced bed shear stress from a three-dimensional tidal model (ROMS) to quantitatively define the relationship between observed grain size and simulated bed shear stress. With focus on the median grain size of well-sorted seabed sediment samples, we present predictive maps of the distribution of seabed sediment classes in the Irish Sea, ranging from mud to gravel. When compared with the distribution of well-sorted sediment classifications (mud, sand and gravel) from the British Geological Survey digital seabed sediment map of Irish Sea sediments (DigSBS250), this ‘grain size tidal current proxy’ (GSTCP) correctly estimates the observed seabed sediment classification in over 73% of the area.
•We compare seabed sediment grain size with simulated tidal-induced bed shear stress.•A proxy for sediment grain size is developed using the quantified relationship.•Predictive maps of (non-mixed) seabed sediment classes are generated.•The proxy reproduces large-scale patterns of seabed sediment class distribution.•Sediment distribution maps are useful in physical modelling and biological studies.
Abstract
While in most species the adult sex ratio is around 1:1, it can be strongly skewed in some species; some of this can be explained by ecological conditions and limits to dispersal. We ...hypothesize that stronger isolation imposed by ecological conditions leads to more pronounced female-biased sex ratios in the groundwater peracarid genus Ingolfiella Hansen, 1903. About 75% of all adults are female, and female-biased sex ratios are present in 30/42 of species for which individuals have been sexed. Sex ratios were not correlated with sexual size dimorphism. The adult sex ratio varied little between species found in different habitats (caves, beach sand, and seabed) thus not supporting our hypothesis that ecological conditions shape adult sex ratios. It appears that sediment structure in most habitats restrict ingolfiellids in their movement. Limited dispersal abilities and small mating assemblages may favour strongly female-biased sex ratios.
Tsuruta, T.; Shiribiki, T.; Misonou, T.; Nakanishi, T.; Sanada Y., and Urabe, Y., 2021. Vertical profiles of radioactive Cs distributions and temporal changes in seabed sediments near river mouth in ...coastal area of Fukushima prefecture. In: Lee, J.L.; Suh, K.-S.; Lee, B.; Shin, S., and Lee, J. (eds.), Crisis and Integrated Management for Coastal and Marine Safety. Journal of Coastal Research, Special Issue No. 114, pp. 320–324. Coconut Creek (Florida), ISSN 0749-0208. Understanding the features of radioactive Cs (137Cs) in seabed sediments in coastal areas linked with rivers, which are major settlement areas for particulate 137Cs, is a key issue in evaluating the supply of 137Cs from river discharges. The vertical profile of 137Cs distribution in seabed sediments is an important clue for elucidating the settlement process of particulate 137Cs near river mouth. Therefore, we sampled seabed sediments using a long core sampler (vibrocoring; the maximum lengths of the core was approximately 100 cm) to clarify the entire vertical profile of the 137Cs distribution and changes in seabed sediments near the river mouth in the coastal area of Fukushima Prefecture. From 2014 through 2019, the 137Cs concentration along the entire vertical profile did not increase, and there was no remarkable migration of the 137Cs toward the deeper layers of the seabed sediments. On the contrary, the amount of 137Cs decreased by more than 70% throughout the entire depth, and the 137Cs distributions in the depth direction become uniform. These results suggest that the supply of 137Cs from the river discharge is not a major concern near the river mouth in the coastal area of Fukushima Prefecture. Resuspension of particle-bound 137Cs and offshore transport are the main factors that reduce the 137Cs concentration in the coastal seabed sediments.
Perception of the seabed environment is an important capability of autonomous underwater vehicles. This paper focuses on defining and extracting robust texture features from visual images that lead ...to useful and practical automated identification of the types of seabed sediments. The visual texture features are described by using a gray-level co-occurrence matrix (GLCM) and fractal dimension, after which an unsupervised learning method, self-organizing map (SOM), is adopted to evaluate the validity of features descriptors on three types of seabed sediments. Subsequently, a kernel-based approach that exhibits robustness versus low numbers of high-dimensional samples, named support vector domain description (SVDD), is applied to classify the types of seabed sediments. In comparison with state-of-the-art classifiers, the experimental results demonstrated the effectiveness of the SVDD on the classification of seabed sediments.
•The visual images of seabed sediments are characterized by the texture features which are extracted based on the GLCM and fractal theory.•A multi-class classification strategy for seabed sediments is proposed by adding a distance measure after SVDD implementation.•The experimental results demonstrate that the proposed classification strategy is feasible in recognizing the type of seabed sediments.
Sediments in the seabed hold vital clues to the study of marine geology, microbial communities and history of ocean life, and the remote operated vehicle (ROV) mounted tubular sampling is an ...important way to obtain sediments. However, sampling in the seabed is a particularly difficult and complicated task due to the difficulty accessing deep water layers. The sampling is affected by the sampler’s structural parameters, operation parameters and the interaction between the sampling tube and sediments, which usually results in low volume and coring rate of sediments obtained. This paper simulated the soft viscous seabed sediments as non-Newtonian Herschel-Bulkley viscoplastic fluids and established a numerical model for the tubular sampling based on the volume of fluid (VOF) method. The influence rules of the sampling tube diameter, drainage area rate, penetration velocity, and sediments dynamic viscosity on coring rate and volume were studied. The results showed that coring volume was negatively correlated with all the parameters except the sampling tube diameter. Furthermore, coring rate decreased with increases in penetration velocity, drainage area rate, and sediments dynamic viscosity. The coring rate first increased and then decreased with increasing of the sampling tube diameter, and the peak value was also influenced by penetration velocity. Then, based on the numerical simulation results, an experimental sampling platform was set up and real-world sampling experiments were conducted. The simulation results tallied with the experimental results, with a maximum absolute error of only 4.6%, which verified that the numerical simulation model accurately reflected real-world sampling. The findings in this paper can provide a theoretical basis for facilitating the optimal design of the geometric structure of the seabed sediments samplers and the parameters in the sampling process.
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