Sea Background Research Articles

Methane plume detection after the 2022 Nord Stream pipeline explosion in the Baltic Sea

On September 26th, 2022, the detonations at the gas pipelines Nord Stream 1 and 2 resulted in some of the largest non-natural releases of methane known. The distribution of methane in the surrounding seawater and the possible effects were not apparent. To trace the pathways of methane we recorded CH4 concentrations and the isotopic signal (δ13C-CH4) in seawater, and air. A week post-explosion, we detected methane concentrations up to 4 orders of magnitude above the natural Baltic Sea background. The released fossil methane created a distinct plume with δ13C-CH4 ratios differing from natural background values. The strong water stratification preserved the distribution pattern initiated by the explosion, shown by the laterally strong concentration gradient within the plume. Our analysis encompasses three stages of the explosion's impact; the initial sea-air methane release, measurements taken during our research expedition one week later, and a third stage triggered by the shift from summer to winter conditions as an outlook on how winter mixing and microbial activity will influence the plume.

Cenozoic structure of the Zhu 3 Depression in the Pearl River Mouth Basin and its response to the dynamic background of the South China Sea

The Zhu 3 Depression is located at the transition between the South China Sea and the South China Block. The Cenozoic structure reflects the dynamic background of the South China Sea. We used 3D seismic and log data to study the structural evolution of the Zhu 3 Depression. We defined the characteristics of Cenozoic rift deformation and the migration of the depocentre based on fault activity and the distribution of sediment thickness. The spatial and temporal differences in the Cenozoic structure of the Zhu 3 Depression are due to the influence of pre-existing faults and regional stresses. Our results show that there are three populations of faults in the Zhu 3 Depression, striking NE, east–west and NW. The NE-striking faults are mainly large-scale boundary faults. The east–west-striking faults are small and were activated in the later stages of deformation. The NW-striking faults are continuous at depth, but are en echelon and parallel to each other at shallow depths. Based on these results, we suggest that the NE- and NW-striking pre-existing faults divide the Zhu 3 Depression into different structural zones and controlled the differences in deformation in the basin. The regional stress direction, which is controlled by regional plate interactions and the Red River Fault Zone, changed clockwise from NW-trending during the Paleocene to NE-trending during the Mid-Miocene. These findings will contribute to a better understanding of the evolution of the entire South China Sea. Thematic collection: This article is part of the Emerging knowledge on the tectonics of the South China Sea collection available at: https://www.lyellcollection.org/topic/collections/south-china-sea

Infrared Maritime Small-Target Detection Based on Fusion Gray Gradient Clutter Suppression

The long-distance ship target turns into a small spot in an infrared image, which has the characteristics of small size, weak intensity, limited texture information, and is easily affected by noise. Moreover, the presence of heavy sea clutter, including sun glints that exhibit local contrast similar to small targets, negatively impacts the performance of small-target detection methods. To address these challenges, we propose an effective detection scheme called fusion gray gradient clutter suppression (FGGCS), which leverages the disparities in grayscale and gradient between the target and its surrounding background. Firstly, we designed a harmonic contrast map (HCM) by using the two-dimensional difference of Gaussian (2D-DoG) filter and eigenvalue harmonic mean of the structure tensor to highlight high-contrast regions of interest. Secondly, a local gradient difference measure (LGDM) is designed to distinguish isotropic small targets from background edges with local gradients in a specific direction. Subsequently, by integrating the HCM and LGDM, we designed a fusion gray gradient clutter suppression map (FGGCSM) to effectively enhance the target and suppress clutter from the sea background. Finally, an adaptive constant false alarm threshold is adopted to extract the targets. Extensive experiments on five real infrared maritime image sequences full of sea glints, including a small target and sea–sky background, show that FGGCS effectively increases the signal-to-clutter ratio gain (SCRG) and the background suppression factor (BSF) by more than 22% and 82%, respectively. Furthermore, its receiver operating characteristic (ROC) curve has an obviously more rapid convergence rate than those of other typical detection algorithms and improves the accuracy of small-target detection in complex maritime backgrounds.

Infrared Small Dim Target Detection Using Group Regularized Principle Component Pursuit

The detection of an infrared small target faces the problems of background interference and non-obvious target features, which have yet to be efficiently solved. By employing the non-local self-correlation characteristic of the infrared images, the principle component pursuit (PCP)-based methods are demonstrated to be applicable to infrared small target detection in a complex scene. However, existing PCP-based methods heavily depend on the uniform distribution of the background pixels and are prone to generating a high number of false alarms under strong clutter situations. In this paper, we propose a group low-rank regularized principle component pursuit model (GPCP) to solve this problem. First, the local image patches are clustered into several groups that correspond to different grayscale distributions. These patch groups are regularized with a group low-rank constraint, enabling an independent recovery of different background regions. Then, GPCP model integrates the group low-rank components with a global sparse component to extract small targets from the background. Different singular value thresholds can be exploited for image groups corresponding to different brightness and grayscale variance, boosting the recovery of background clutters and also enhancing the detection of small targets. Finally, a customized optimization approach based on alternating direction method of multipliers is proposed to solve this model. We set three representative detection scenes, including the ground background, sea background and sky background for experiment analysis and model comparison. The evaluation results show the proposed model has superiority in background suppression and achieves better adaptability for different scenes compared with various state-of-the-art methods.

The Late-comer Friend: Iranian Interests on the Horn of Africa

In the competition among the great powers as well as Middle Eastern regional actors the Horn, especially with its background of the Red Sea, has become the scene of two regional overlapping rivalries, namely between Saudi Arabia/the United Arab Emirates/Egypt and Qatar/Turkey on the one hand, and Saudi Arabia and Iran, on the other. While Iran seems to be far from the Horn of Africa, its participation in the war in Yemen as well as its strategic position both along the land route and the maritime route of the Chinese Belt and Road Initiative make it an unavoidable party. Iran is operating on the Horn of Africa to extend its strategic depth, resist the pressure of rival powers and counterbalance their activities, and increase its political and economic gains. Compared to other Gulf states, Tehran started its campaign relatively late, and Iran’s economic potential is more limited as well. The lack of significant Shi’a presence in East Africa is also an obstacle for expansion. Therefore, Iran is still a secondary actor on the Horn of Africa.

Research on electromagnetic scattering characteristics of high voltage transmission lines considering rough surface

With the continuous construction of the UHV power grid in China, the electromagnetic scattering of electromagnetic waves from random rough surfaces will have a certain impact on the passive interference of high-voltage transmission lines. To solve the problem of solving the propagation law of electromagnetic scattering in the electromagnetic interference of high-voltage transmission lines to radio stations, this paper is based on the approximation method and moment method of electromagnetic scattering, This paper explores the influence of lossless rough surface and lossy rough surface on the passive interference of high-voltage tower line, focusing on the influence of sea level and dielectric constant of seawater on the electromagnetic scattering characteristics of the target under the sea background, and obtains the general law.

Maritime Infrared Target Detection Using a Dual-Mode Background Model

With the rapid development of marine business, the intelligent detection of ship targets has become the key to marine safety. However, it is difficult to accurately detect maritime infrared targets due to severe sea clutter interference in strong wind waves or dim sea scenes. To adapt to diverse marine environments, a dual-mode sea background model is proposed for target detection. According to the global contrast of the image, the scene is divided into the sea surface with violent changes and the sea surface with stable changes. In the first stage, the preliminary background model suitable for steadily changing scenes is proposed. The pixel-level foreground mask is generated through the background block filter and the posterior probability criterion. Moreover, the learning rate parameter is adjusted using the detection results of two adjacent frames. In the second stage, the background model suitable for highly fluctuating scenes is proposed. Moreover, the local correlation feature is used to enhance the local contrast of the frame. The experimental results for the different scenes show that the proposed method has a better detection performance than the other comparison algorithms.

Experimental study of extreme waves based on nonlinear Schrödinger equation under background of a random sea

The Peregrine breather (PB) solution of the nonlinear Schrödinger equation is used to model ocean extreme waves in a water wave flume. Triangular spectral features of wave elevations are observed over the nonlinear evolution of the extreme waves, which can be applied for early detection of the formation of extreme waves. To model a more realistic sea state, a background random wave is superposed to the PB in this study. We examine the spectral features of the nonlinear wave evolution with random background waves by the spectral analysis. It is found that the wave elevations show similar triangular spectral features for extreme waves with a relatively mild background wave. Moreover, we find that the second harmonic elevations of the extreme waves also show triangular spectral features, suggesting the potential use of the second harmonic elevations (in addition to the first) for detection of the formation of extreme waves.

S-DETR: A Transformer Model for Real-Time Detection of Marine Ships

Due to the ever-changing shape and scale of ships, as well as the complex sea background, accurately detecting multi-scale ships on the sea while considering real-time requirements remains a challenge. To address this problem, we propose a model called S-DETR based on the DETR framework for end-to-end detection of ships on the sea. A scale attention module is designed to effectively learn the weights of different scale information by utilizing the global information brought by global average pooling. We analyzed the potential reasons for the performance degradation of the end-to-end detector and proposed a decoder based on Dense Query. Although the computational complexity and convergence of the entire S-DETR model have not been rigorously proven mathematically, Dense Query can reduce the computational complexity of multi-head self-attention from O(Nq2) into O(Nq). To evaluate the performance of S-DETR, we conducted experiments on the Singapore Maritime Dataset and Marine Image Dataset. The experimental results show that the proposed method can effectively solve the problem of multi-scale ship detection in complex marine environments and achieve state-of-the-art performance. The model inference speed of S-DETR is comparable to that of single-stage target detection models and meets the real-time requirements of shoreside ship detection.

Joint spatio-temporal features and sea background prior for infrared dim and small target detection

The detection of dim and small targets in the complex sea background poses new challenges to automatic target search and interception by infrared air-to-air missiles at sea. To solve the problems of low detection rate of dim targets and massive suspected targets caused by the shadow region of clutter on the sea surface, this paper proposes a detection method for dim and small targets with spatio-temporal features and background prior information. Firstly, by combining the ideas of local energy factor and multi-scale patch contrast measure, an improved dim target detection method is proposed, which can effectively enhance the contrast of dim targets and suppress background clutter. Then, according to the grayscale probability distribution difference between the background and the target, a double-Gaussian model is established for the residual background and the target region and a background suppression method based on the spatial prior information is proposed to further suppress the residual background. Finally, a dim target detection method is proposed by combining the above dim target detection, background suppression, and dynamic pipeline filtering methods. The results indicate the average detection rate of the detection method proposed in this study is 91.44%. Also, the average number of false alarms in a single frame is reduced to 9.89, which is more than 80% lower than that of other algorithms.

Geochemical characteristics of hydrogen, oxygen, carbon isotopes and REE of cenozoic dolomites in Well Xike 1, Xisha Islands, South China sea and the significance for dolomitization in island-reef areas

Due to the special tectonic background and complex geological evolution characteristics of the South China Sea, reef dolomite reservoirs (sush as Well Xike 1) are widely developed. Based on the drilling core data of Well Xike 1, the structure and geochemical characteristics of dolomite reservoirs, including carbon, oxygen, hydrogen isotopes and REE were systematically studied using geochemical and petrological methods. It is found that the geochemical characteristics of REE show that the main diagenetic environment of dolomites is a low-temperature alkaline semi open oxidation environment; the carbon and oxygen isotopes of the dolomites are generally lack of correlation, the δD value is significantly lower than the hydrogen isotope value of seawater. Meanwhile, the oxygen isotope value of deep dolomites is negatively biased, which may be due to the increase or decrease of pore water temperature caused by deep thermal convection that related to the regional tectonic movements of the South China Sea. The δ18O value is also consistent with the geological reality of increasing saddle dolomite content in deep dolomites. The distribution of the δ13C value indicates that the dolomite inherited the carbon of the original limestone during dolomitization, while the characteristic of the δD value shows that it may be affected by the mixing of atmospheric precipitation and concentrated seawater in the quasi contemporaneous period. Based on the comprehensive analysis of the geochemical characteristics of the Well Xike 1, it is considered that the higher diagenetic temperature could be an important factor leading to the huge differences between the diagenetic model of deep and shallow dolomites. The geochemical characteristics of the shallow dolomites show that it is mainly reflux infiltration dolomitization under the micro evaporation and concentration sea water environments, while the deep dolomite is transformed by the hot water fluids in the epigenetic diagenetic evolution stage.

Human vision-inspired detection for infrared small targets under scaly light background on sea surface

The automatic detection and search of small targets by the infrared guidance system is challenged by the complex sea background environment, particularly the dense scaly light generated by the reflection of sunlight by the sea clutter and the appearance of boundaries. To address this issue, inspired by the significant sensitivity, classification perception, reverse exclusion, and association prediction characteristics of the human visual system, this paper proposes a human vision-inspired detection model for infrared small targets under scaly light background on the sea surface. Firstly, the local energy factor and multi-scale patch contrast measure are fused to construct a significance analysis model and enhance the contrast of the target region of interest. Then, the image is classified into different regions according to the detection of grayscale fluctuations and mutation points in the background, and a region self-classification perception model is constructed for adaptive segmentation of scene images. Next, the prior information of the target gradient is used to construct a reverse exclusion analysis model for suppressing the residual background of the boundary. Subsequently, by using the fluctuation law and characteristic difference of the spatial energy and size features of the target and the scaly light background in the time domain, the correlation prediction analysis model is constructed to further suppress the residual background. Finally, through the combination of the above four visual feature models, a new detector with good adaptability is proposed for small targets under scaly light background on the sea surface. The experimental results indicate that the average detection rate of our detector is 95.26%, and the number of false alarms in a single frame is reduced by 93.77% compared with the typical detectors.

MLBR-YOLOX: An Efficient SAR Ship Detection Network With Multilevel Background Removing Modules

On the remote sensing images of marine synthetic aperture radar (SAR), ship targets often occupy only a small part of an image, and the rest are all sea and coastal backgrounds. Existing neural networks based on SAR ship detection often directly detect an entire SAR image, which consumes a large amount of computing resources. In this article, a new marine SAR ship detection network, called multilevel background removing–you only look once X (MLBR-YOLOX), is proposed. First, a new plug-and-play module, called standalone spatial patch detector, is proposed to predetect the position of ships and filter out most of the sea backgrounds at the source image level. Second, a deep spatial feature detector is presented for detecting deep semantic features of the output of the backbone module to further reduce the computational cost of the neck and head modules. Finally, the original YOLOX network is adopted to locate and classify the pre-detected results. Experimental results on the SAR ship detection dataset and the high-resolution SAR images dataset indicate that the detection performance of MLBR-YOLOX is close to that of YOLOX, but the computational complexity is merely 23.97% and 12.50% of YOLOX's, respectively. Moreover, the experiment conducted on a large-scene Sentinel-1 SAR image illustrates that the proposed network has good migration application capability.

Simulation method for infrared radiation transmission characteristics of typical ship targets based on optical remote sensing

SummaryIn order to meet the needs of the application of optical detection and recognition of ship targets in complex sea environment, based on the full link of optical remote sensing detection, the radiation transmission mechanism of ship target characteristics is analyzed. Then, the radiation characteristics model of ship target, the radiation model of ship target thermal wake, and the radiation characteristics model of sea background are established, and the simulation calculation of focal plane radiation characteristics for sea surface ship target is realized according to the space‐based detection and imaging mechanism; Finally, based on the simulation calculation model, the variation law of ship target radiation characteristics under different sea surface conditions and different imaging time are analyzed, which can provide theoretical basis and scientific guidance for the key index design of Space‐Based Surveillance and detection system and the optimization of target detection and recognition algorithm.

Nonlinear Ship Wake Detection in SAR Images Based on Electromagnetic Scattering Model and YOLOv5

Traditional wake detection methods have been successfully applied to the detection of a simple linear ship wake. However, they cannot effectively detect nonlinear wake and weak wake under high sea state conditions, whereas the deep-learning-based detection method could play to its strengths in this respect. Due to the lack of sufficient measured SAR images of ship wake to meet the training requirement for deep learning method, this paper explores the method to detect the nonlinear ship wake by combining electromagnetic scattering model with deep learning technique. The composite scene model of the sea surface and its wake is established first, then the facet scattering distribution of the ship wake and the sea background is analyzed with the help of the electromagnetic scattering model, and the simulation of the wake SAR images under the sea background is finally accomplished based on the modulation model. Combined with the simulation results and measured wake SAR images, the sample database is constructed. The You Only Look Once Version five algorithm (YOLOv5) based on deep learning techniques is applied to detect the wake target in complex conditions such as different sea states, multiple targets, curvilinear wakes, and weak wakes. The result show that the YOLOv5 leads to an obvious higher detection efficiency with satisfactory accuracy. Moreover, the comparison between YOLOv5 and the traditional Radon transform method for detecting nonlinear wakes in a strong noise background shows that the proposed method is better than the traditional object detection model. Thus, the proposed scheme would be a practical tool to deal with the detection of nonlinear ship wake and weak wake in complex scenarios, which will be helpful to the further remote sensing investigation of the ship.

Joe D. Cruz's Aazhi Soozh Ulagu, Korkai Novels Emphasis on Seafarer’s Life

The Tamil language has a very ancient grammatical and literary practice. It is worth noting that these grammatical and literary texts have given Tamil the status of a classical language and that these books have recorded people from all walks of life. However, modern literature is no more than traditional literature in the form of close observation of specific ethnic groups. In this way, in some specific records of the society, the condition of the maritime people belonging to the ancient natives has been identified in modern times and what is the living environment of the people, their occupation, culture, identity, culture, and rituals have been divided into types and sums and described to the world by Jodigurus's novels Aazhi Soozh Ulagu, Korkai. Among the five types of land with economic connotations in the Tamil literary tradition, uncertainty can be seen only in the Neytal tinaiyil. The next phase of development embraces great change in all other tinaiyil and lifestyles. But Neytal land has failed to reach such a level. In the last two thousand years of literature in Tamil, maritime records are very rare. Perumanal ulakam is not the as Tolkappiyam makes it out to be. Here and there we can hear about Paratavar hunting sharks by throwing them in such a way that the sea is agitated. But no Sanga poet tried to make the background of the turbulent sea in the shark hunt and imprint it in the mind of the Tamil speaker as an experience. But this is recorded by Joe D. Cruz in his novels.

Visual Saliency via Multiscale Analysis in Frequency Domain and Its Applications to Ship Detection in Optical Satellite Images.

This article proposes a bottom-up visual saliency model that uses the wavelet transform to conduct multiscale analysis and computation in the frequency domain. First, we compute the multiscale magnitude spectra by performing a wavelet transform to decompose the magnitude spectrum of the discrete cosine coefficients of an input image. Next, we obtain multiple saliency maps of different spatial scales through an inverse transformation from the frequency domain to the spatial domain, which utilizes the discrete cosine magnitude spectra after multiscale wavelet decomposition. Then, we employ an evaluation function to automatically select the two best multiscale saliency maps. A final saliency map is generated via an adaptive integration of the two selected multiscale saliency maps. The proposed model is fast, efficient, and can simultaneously detect salient regions or objects of different sizes. It outperforms state-of-the-art bottom-up saliency approaches in the experiments of psychophysical consistency, eye fixation prediction, and saliency detection for natural images. In addition, the proposed model is applied to automatic ship detection in optical satellite images. Ship detection tests on satellite data of visual optical spectrum not only demonstrate our saliency model's effectiveness in detecting small and large salient targets but also verify its robustness against various sea background disturbances.

Staggered Coprime Pulse Repetition Frequencies Synthetic Aperture Radar (SCopSAR)

High-resolution wide-swath synthetic aperture radar (HRWS-SAR) imaging is highly desirable since it allows one to produce high-resolution SAR images of large areas during a short visit time. In this article, staggered coprime pulse repetition frequencies synthetic aperture radar (SCopSAR) is proposed. It divides the time during which a scatterer is illuminated by the antenna beam pattern into two halves where, in each half, pulses are transmitted at the rate of one of two sub-Nyquist pulse repetition frequencies (PRFs). Such PRFs are related to the Nyquist PRF using two coprime subsampling factors. This allows extending the maximum range swath width that can be imaged by a number of times that equals the smaller subsampling factor at the expense of a reduction in the azimuth resolution by half. It further allows for a reduction in the amount of data to be stored and communicated. SCopSAR is an imaging modality suitable for scenes that contain a small number of bright scatterers over a dark background which, for instance, is the case when imaging ships in a calm sea background. Compared with the techniques recently proposed in the literature, SCopSAR simplifies the radar requirements since it uses only one carrier frequency, one waveform, and one channel. Simulations and real ERS-2 satellite raw data are used to validate the theoretical findings presented in this article.

Background Modeling Combined With Multiple Features in the Fourier Domain for Maritime Infrared Target Detection

To detect ship targets in dynamic sea backgrounds, a robust foreground detection method based on background modeling combined with multiple features in the Fourier domain (BMMFF) is proposed. Because the fluctuation of seawater is similar to a sine wave, the amplitude spectrum of the seawater in the Fourier domain has strong energy concentration, and the background model is built in the Fourier domain. The local statistical characteristics can effectively reflect the properties of a specific position, and the target frequency points are extracted by comparing the local statistical characteristic differences between the amplitude spectrum of the test frame and the updated background. Additionally, two different strategies are used to update the background for cases with or without sudden waves in two adjacent test frames. When the target and seawater have different contrast in different scenes, the threshold is set according to the seawater's fluctuation degree, which is classified into three different levels in the training stage. Moreover, the linear correlation feature between the test frame and the updated background and the oscillation feature of the test frame's amplitude spectrum are proposed in the Fourier domain, which can better segment targets in relatively calm and violent sea scenes, respectively. Thus, the two features are combined with the background model with a reasonable strategy to further improve the detection accuracy. The experimental results demonstrate that BMMFF outperforms related comparison algorithms in different challenging sea scenes. The average false alarm rate of BMMFF is reduced by approximately 30% in the case where its average detection rate is similar to that of other algorithms.

SAR Remote Sensing Image Ship Detection Method NanoDet Based on Visual Saliency

In the Synthetic Aperture Radar (SAR) remote sensing image, ships are visually significant targets on the sea surface. Because they are made of metal, thus the backscatter is strong, while the sea surface is smooth and the backscatter is weak. However, the large-width SAR remote sensing image has a complicated sea background, and the features of various ship targets are quite different. To solve this problem, a SAR remote sensing image ship detection model called NanoDet is proposed. NanoDet is based on visual saliency. First, the image samples are divided into various scene categories using an automatic clustering algorithm. Second, differentiated saliency detection is performed for images in various scenes. Finally, the optimized lightweight network model, NanoDet, is used to perform feature learning on the training samples added with the saliency maps, so that the system model can achieve fast and high-precision ship detection effects. This method is helpful for the real-time application of SAR images. The lightweight model is conducive to hardware transplantation in the future.This study conducts experiments based on the public data set SSDD and AIR-SARship-2.0, and the experiments results verify the effectiveness of our approach.