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In this paper, we present a full coverage path planning (CPP) algorithm for the marine surveys conducted in the convex polygon shaped search area. The survey is supposed to carry out by torpedo-type AUVs (autonomous underwater vehicles). Due to their nonholonomic mechanical characteristics, these vehicles have nonzero minimum turning radius. For any given polygon shaped search area, it can always be partitioned into one or more convex polygons. With this in mind, this paper proposes a novel search algorithm called CbSPSA (Calculation based Shortest Path Search Algorithm) for full coverage of any given convex polygon shaped search area. By aligning the search inter-tracks alongside the edge with the minimum height, we can guarantee the minimum number of the vehicle’s turns. In addition, the proposed method can guarantee the planned path is strictly located inside the polygon area without overlapped or crossed path lines, and also has the total path length as short as possible. Considering the vehicle’s nonzero minimum turning radius, we also propose a sort of smoothing algorithm which can smooth the waypoint path searched by CbSPSA so that the vehicle can exactly follow it. The smoothed path is also guaranteed to be strictly located inside the polygon. Numerical simulation analyses are also carried out to verify the effectiveness of the proposed schemes.

With the in-depth implementation of the strategy of maritime power, the state has gradually increased its financial input in marine survey and research, and the number of ocean observation instruments and equipment in maritime research institutes has increased substantially. At the same time, due to the particularity of the use of ocean observation instruments and equipment, damage or even loss of instruments and equipment sometimes occurs, which has brought new challenges to the management of instruments and equipment. Taking the ocean observation instruments related to physical oceanography as an example, this paper classified the ocean observation instruments and equipment, discussed their particularity, explored the establishment of management mechanisms in line with the characteristics of ocean observation instruments and equipment, further improved the scientific nature of asset management, to better serve the needs of teaching and scientific research.

Marine survey unmanned surface vessel (USV) has a wide range of applications.However, the attitude of USV is easily affected by wind, waves, currents and floating debris, which may cause structural damage or low precision observation.Double hull and wide deck platform of unmanned surface vessed was designed, and the transducer of multi-beam echo sounder was installed on the lifting mechanism.These designs improved the sailing attitude of the platform, the safety of the transducer and the accuracy of the observed data.In 2020, this USV was participated in the dike-inspection mission of Jiangxi’s emergency flood relief.It successfully inspected the sediment environment of 14 km dike, affected by the unfavorable working conditions like rapid water flow, turbid water and floating garbage.Four risks were located, which provided important data support for the anti-flood campaign.

The present analysis of state of the art portrays that actual time series or spectrum backscattered data from a point on the sea bottom are rarely used as features for machine learning models. The paper deals with the artificial intelligence techniques used to examine CHIRP-recorded data. The data were collected using a CHIRP sub-bottom profiler to study two sand bottom sites and two sandstone bottom sites in the offshore zone of Ashqelon City (Southern Israel). The first reflection time series and spectra of all the traces from the four sites generated two training and two test sets. Two logistic regression models were trained using the training sets and evaluated for accuracy using the test sets. The examination results indicate that types of sea bottom can be quantitatively characterized by applying logistic regression models to either the backscatter time series of a frequency-modulated signal or the spectrum of that backscatter. The examination accuracy reached 90% for the time series and 94% for the spectra. The application of spectral data as features for more advanced machine learning algorithms and the advantages of their combination with other types of data have great potential for future research and the enhancement of remote marine soil classification.

The primary objective of this research is to demonstrate advanced surveying methods and techniques for coastal erosion identification and monitoring in a densely human-populated coastline, the southern coastline of the Gulf of Patras (Greece), which diachronically suffers erosion problems expected to become worse in the forthcoming years due to climate change and human intervention. Its importance lies in the fact that it presents a robust methodology on how all modern scientific knowledge and techniques should be used in coastal erosion problems. The presented methods include the use of satellite and aerial photo imaging, shallow seabed bathymetry and morphology, sediment sampling, geotechnical investigations, as well as hydrodynamic modelling. The results are extensively analyzed in terms of their importance in coastal erosion studies and are cross-validated to define those areas most vulnerable to erosion. Towards this scope, the seabed erosion rate produced by hydrodynamic modelling is compared with the coastal vulnerability index (CVI) calculations performed in the examined area to identify which coastal zones are under a regime of intensive erosion. The results between the CVI and the seabed erosion rate appear to coincide in terms of the erosion potential, especially in zones where the vulnerability regime has been calculated as being high or very high, with the P. oceanica meadows playing an important role in reducing erosion.

Recently, rapidly developing artificial intelligence and computer vision techniques have provided technical solutions to promote production efficiency and reduce labor costs in aquaculture and marine resource surveys. Traditional manual surveys are being replaced by advanced intelligent technologies. However, underwater object detection and recognition are suffering from the image distortion and degradation issues. In this work, automatic monitoring of sea cucumber in natural conditions is implemented based on a state-of-the-art object detector, YOLOv7. To depress the image distortion and degradation issues, image enhancement methods are adopted to improve the accuracy and stability of sea cucumber detection across multiple underwater scenes. Five well-known image enhancement methods are employed to improve the detection performance of sea cucumber by YOLOv7 and YOLOv5. The effectiveness of these image enhancement methods is evaluated by experiments. Non-local image dehazing (NLD) was the most effective in sea cucumber detection from multiple underwater scenes for both YOLOv7 and YOLOv5. The best average precision (AP) of sea cucumber detection was 0.940, achieved by YOLOv7 with NLD. With NLD enhancement, the APs of YOLOv7 and YOLOv5 were increased by 1.1% and 1.6%, respectively. The best AP was 2.8% higher than YOLOv5 without image enhancement. Moreover, the real-time ability of YOLOv7 was examined and its average prediction time was 4.3 ms. Experimental results demonstrated that the proposed method can be applied to marine organism surveying by underwater mobile platforms or automatic analysis of underwater videos.

Modern studies which dealt with the frequency domain analysis showed that a frequency-domain approach has an essential advantage and mentioned an inner qualitative relationship between the subsurface structure and its frequency spectra. This paper deals with the acoustic spectral response of sand and sandstone sediments at the sea bottom. An acoustic data collection campaign was conducted over two sand sites and two sandstone sites. The analysis of the results shows that reflections of acoustic signals from sand and sandstone sea bottom are characterized by various spectral features in the 2.75–6.75 kHz range. The differences in acoustic response of sand and sandstone can be quantified by examining the maximal normalized reflected power, the mean frequency, and the number of crossings at different power levels. The statistical value distribution of these potential classifiers was calculated and analyzed. These classifiers, and especially the roughness of the spectrum quantified by the number of crossings parameter can give information to assess the probability for sand or sandstone based on the reflected spectra and be used for actual distinction between sand and sandstone in sub bottom profiler data collection campaigns.

The nation of Antigua and Barbuda has experienced major degradation of its coral reef ecosystems over the past 40+ years. The primary drivers of this degradation are multiple and are highly linked to anthropogenic influences, including over-exploitation and poor management of marine resources. The effectiveness of management actions in marine protected areas (MPAs) has often been hampered by a lack of data to inform management recommendations. This was emphasized by The Nature Conservancy’s (TNC) Coral Reef Report Card which highlighted not only the lack of data collection in Antigua and Barbuda and other Caribbean nations, but also illustrated how spatially dispersed available datasets are. The government of Antigua and Barbuda recognized the need for a marine data collection program to better inform the designation and management of MPAs as a tool to improve the health of the marine ecosystems. The Atlantic Gulf Rapid Reef Assessment (AGRRA) protocol has been identified as a means to address planning and management for marine areas. Three AGRRA surveys have been conducted in the years following the TNC 2016 report, in previously established managed areas: North East Marine Management Area (NEMMA) in 2017 and Nelson Dockyard National Park (NDNP) in 2019 as well as areas outlined for future management (Redonda in 2018). Our surveys were conducted to provide updated datasets to inform management for the aforementioned areas. While the results of these surveys mirror the underlying poor coral reef-health conditions, which have been shown to exist within the Caribbean region, they also highlight intra-site variation that exists within each survey location. This knowledge can be crucial in guiding management decisions in these marine areas, through zoning and other management prescriptions. Additionally, the marine surveys conducted around Redonda established useful marine baselines to aid in monitoring the island’s recovery following removal of terrestrial invasive species. This article provides an overview of data collected using the AGRRA methodology in marine zones across Antigua and Barbuda which have current or future management prescriptions and provides recommendations to demonstrate the data’s future utilization for marine conservation and management.

The processing of Chirp data is limited by the usual recording of the signal envelope, which enhances its immediate visibility but prevents applying methods based on wave equations. This is normally not the case for Boomer data. However, both systems are monochannel instruments, which cannot estimate properly the propagation velocity of the signal in the rocks. In this paper, we present two theorems: the first one links the Chirp or Boomer source spectrum with an expected amplitude decay curve; the second one defines conditions for the deconvolution stability of the enveloped Boomer signal when the full waveform of the source signal is known. In this way, we can jointly process and integrate heterogeneous surveys including both data types. We validated the proposed algorithms by applying them to synthetic and real data. The presented tools can improve the image resolution and the characterization of geological formations in marine surveys by reflectivity anomalies, which are distorted by standard equalization methods.

Indonesia is a maritime country with two-third of its total area consist of water. Research on marine and fisheries studies should be considered as an important matter in Indonesia. Studies on research development can be a way to evaluate and to determine research policy direction. The increasing of scientific publication database draws the need for enhancement to their quantitative techniques analysis to understand research structure; social and science structure. This study aims to map the subject area, that covered research on marine and fisheries studies and carried out by institution located in Indonesia. Social network analysis is used to show the relationship of subject area in the related research. Data that is used in this research is based on marine and fisheries studies that conducted in Indonesia and indexed by Scopus for the last ten years (2006-2015). The network map shows that the publication has changed in terms of the covered subject areas and the relationship among them. The result of this study can be used to evaluate and to support marine and fisheries research policy direction in Indonesia.

The purpose of this paper is to present a system developed for detection andaccurate mapping of ferro-metallic objects buried below the seabed in shallow waters. Thesystem comprises a precise magnetic gradiometer and navigation subsystem, both installedon a non-magnetic catamaran towed by a low-magnetic interfering boat. In addition wepresent the results of a marine survey of a near-shore area in the vicinity of Atlit, a townsituated on the Mediterranean coast of Israel, about 15 km south of Haifa. The primarypurpose of the survey was to search for a Harvard airplane that crashed into the sea in 1960.A magnetic map of the survey area (3.5 km2 on a 0.5 m grid) was created revealing theanomalies at sub-meter accuracy. For each investigated target location a correspondingferro-metallic item was dug out, one of which turned to be very similar to a part of thecrashed airplane. The accuracy of location was confirmed by matching the position of theactual dug artifacts with the magnetic map within a range of ± 1 m, in a water depth of 9 m.