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New Technologies and Methods in Coastal Observing
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New Technologies and Methods in Coastal Observing

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Physical Oceanography".

Deadline for manuscript submissions: closed (20 January 2023) | Viewed by 10489

Special Issue Editors

Dr. Piermattei Viviana

E-Mail Website
Guest Editor
Laboratory of Experimental Oceanology and Marina Ecology, Department of Ecological and Biological Sciences (DEB), University of Tuscia, 00053 Civitavecchia, Rome, Italy
Interests: biological oceanography; oceanographic technology development; low-cost sensors development; autonomous instrumentation (gliders, surface vehicles, drifters)
Dr. Francesco Rende

E-Mail Website
Guest Editor
ISPRA, Italian National Institute for Environmental Protection and Research, via Vitaliano Brancati 60, 00144 Rome, Italy
Interests: remote sensing; seagrass; underwater photogrammetry; machine learning; deep learning; artificial intelligence; object image analysis; uav; ASVs
Special Issues, Collections and Topics in MDPI journals
Dr. Marina Penna

E-Mail Website
Guest Editor
Institute for Environmental Protection and Research (ISPRA), 00144 Rome, Italy
Interests: study of the dynamics of marine coastal benthic communities for the assessment of ecological quality in relation to human activities; development of monitoring protocols and application of sampling techniques in marine matrices through innovative methods
Dr. Simone Bonamano

E-Mail
Guest Editor
1. Department of Biological and Ecological Sciences DEB, University of Tuscia, Viterbo, Italy
2. Fondazione CMCC - Centro Euro-Mediterraneo sui Cambiamenti Climatici, Lecce, Italy
Interests: physical oceanography; coastal dynamics; hydrodynamic and pollutants transport models; marine renewal energy; phytoplankton primary production

Special Issue Information

Dear Colleagues,

The coastal marine environment is increasingly subject to multiple pressures and stressors, produced by the effects of both natural inputs and human activities. Yet, even as the importance of coastal oceans continues to increase due to significant shits in social, economic, and environmental values, our knowledge of these areas remains limited. As a consequence, there exist many limitations in implementing informed management, fulfilling environmental regulations, and responsibly exploiting marine resources while following an ecosystem-based management.

The purpose of this Special Issue is to publish the most exciting research with respect to the methods, technologies, and approaches applied to coastal ecosystem study. High quality papers are encouraged for publication, directly related to the various topics mentioned below. Novel techniques for the study are encouraged.

Topics:

  • innovative methods and approach for coastal ecosystem observation and study;
  • cost-effective remote technologies applied to marine coastal observing;
  • development of early warning systems based on forecasting models;
  • analysis of potential impacts of anthropic pressures and climate change on marine ecosystems;
  • wave devices implementation and evaluation of wave energy potential

Dr. Piermattei Viviana
Dr. Francesco Rende
Dr. Marina Penna
Dr. Simone Bonamano
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • coastal observing
  • cost-effective technologies
  • Remote observing methods
  • remote sensing solutions for coastal monitoring
  • autonomous underwater and surface vehicles (AUVs, USVs) and remotely operated vehicles (ROVs)
  • ecosystem-based approach
  • wave energy potential
  • wave devices
  • hydrodynamic and pollutants transport models
  • anthropic impacts on marine ecosystems
  • climate change

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

21 pages, 7676 KiB  
Article
The Evaluation of WaveSAX Power Generation to Support Port Energy Self-Sufficiency
by Simone Bonamano, Maximo Aurelio Peviani, Giordano Agate, Calogero Giuseppe Burgio, Giorgio Fersini and Marco Marcelli
J. Mar. Sci. Eng. 2023, 11(11), 2097; https://doi.org/10.3390/jmse11112097 - 1 Nov 2023
Cited by 1 | Viewed by 1056
Abstract
Remarkable advancements have been made in wave energy converters, notably the innovative WaveSAX technology—an oscillating water column system conceptually designed for coastal structures. Proven effective in existing installations, particularly at Civitavecchia Port, Italy, where the WaveSAX-1 prototype was tested in 2018 and the [...] Read more.
Remarkable advancements have been made in wave energy converters, notably the innovative WaveSAX technology—an oscillating water column system conceptually designed for coastal structures. Proven effective in existing installations, particularly at Civitavecchia Port, Italy, where the WaveSAX-1 prototype was tested in 2018 and the WaveSAX-2 was updated in 2021. The device’s power generation capacity was evaluated using a Simulating WAves Nearshore (SWAN) model that simulated 30 years of wave conditions. Validation with radar and Acoustic Doppler Profiler instruments showed excellent performance in wave height simulation. Results revealed higher wave power generation near the harbor breakwater, surpassing offshore levels, especially in central and northern sections. WaveSAX-2, featuring an improved Wells turbine, demonstrated a remarkable 37% increase in average efficiency compared to WaveSAX-1. If a linear WaveSAX array were installed, it could produce 4 GWh annually, satisfying 20% of the port’s energy needs and reducing around 2800 tCO2e/year. Doubling arrays and incorporating triangular modules could significantly enhance sustainability for port operations, offering a promising path toward self-sufficiency and environmental responsibility. Full article
(This article belongs to the Special Issue New Technologies and Methods in Coastal Observing)
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17 pages, 8838 KiB  
Article
Impacts of High-Density Suspended Aquaculture on Water Currents: Observation and Modeling
by Xuehai Liu and Xuelei Zhang
J. Mar. Sci. Eng. 2022, 10(8), 1151; https://doi.org/10.3390/jmse10081151 - 20 Aug 2022
Cited by 5 | Viewed by 1980
Abstract
Large-scale aquaculture activities in China have been rapidly developing in coastal waters, and they inevitably affect hydrodynamic structures and, hence, substance transportation. Predicting the effects is critical for understanding the environmental ecology and biochemical processes in these waters. To realize the solution, we [...] Read more.
Large-scale aquaculture activities in China have been rapidly developing in coastal waters, and they inevitably affect hydrodynamic structures and, hence, substance transportation. Predicting the effects is critical for understanding the environmental ecology and biochemical processes in these waters. To realize the solution, we conducted a field observation in Sungo Bay, which is an important aquaculture bay in China, and we developed a three-dimensional numerical model by arranging so-called porous structures, representing the aquaculture facilities, on grids of the culture layers. The energy-loss coefficients were specified to determine the momentum loss by the friction of the structures. We determined the appropriate coefficients for the oyster, scallop, and kelp cultures by using numerical simulation. According to the observation and model results, the aquaculture substantially weakened the current velocities in the culture layers and altered the vertical structures of the water currents. For this high-density and large-scale culture bay, the decrease rates of the current velocities in the culture layer were up to ~68%, ~65% and ~60% in the culture zones of oysters, scallops, and kelps, respectively. Bivalve cultures and kelp and bivalve cultures reduced the water-exchange ability of the bay by 33% and 50%, respectively. The method and results of this study provide a reference for studies on other aquaculture bays. Full article
(This article belongs to the Special Issue New Technologies and Methods in Coastal Observing)
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18 pages, 3709 KiB  
Article
Accurate Fish Detection under Marine Background Noise Based on the Retinex Enhancement Algorithm and CNN
by Yanhu Chen, Yucheng Ling and Luning Zhang
J. Mar. Sci. Eng. 2022, 10(7), 878; https://doi.org/10.3390/jmse10070878 - 27 Jun 2022
Cited by 3 | Viewed by 2136
Abstract
Underwater detection equipment with fish detection technology has broad application prospects in marine fishery resources exploration and conservation. In this paper, we establish a multi-scale retinex enhancement algorithm and a multi-scale feature-based fish detection model to improve underwater detection accuracy and ensure real-time [...] Read more.
Underwater detection equipment with fish detection technology has broad application prospects in marine fishery resources exploration and conservation. In this paper, we establish a multi-scale retinex enhancement algorithm and a multi-scale feature-based fish detection model to improve underwater detection accuracy and ensure real-time performance. During image preprocessing, the enhancement algorithm combines the bionic structure of the fish retina and classical retinex theory to filter out underwater environmental noise. The detection model focuses on improving the detection performance on small-size targets using a deep learning method based on a convolutional neural network. We compare our method to current mainstream detection models (Faster R-CNN, RetinaNet, YOLO, SSDetc.), and the proposed model achieves better performance, with a mean Average Precision (mAP) of 78.31% and a mean Miss Rate (mMR) of 54.11% in the open fish image data set. The test results for the data from the field experiment prove the feasibility and stability of our model. Full article
(This article belongs to the Special Issue New Technologies and Methods in Coastal Observing)
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17 pages, 19127 KiB  
Article
Observation of Abrupt Changes in the Sea Surface Layer of the Adriatic Sea
by Frano Matić, Tomislav Džoić, Hrvoje Kalinić, Leon Ćatipović, David Udovičić, Tea Juretić, Lucija Rakuljić, Daria Sršen and Vjekoslav Tičina
J. Mar. Sci. Eng. 2022, 10(7), 848; https://doi.org/10.3390/jmse10070848 - 22 Jun 2022
Cited by 3 | Viewed by 2163
Abstract
We observed interannual changes in the temperature and salinity of the surface layer of the Adriatic Sea when measured during the period 2005–2020. We observed non-stationarity and a positive linear trend in the series of mixed layer depth, heat storage, and potential energy [...] Read more.
We observed interannual changes in the temperature and salinity of the surface layer of the Adriatic Sea when measured during the period 2005–2020. We observed non-stationarity and a positive linear trend in the series of mixed layer depth, heat storage, and potential energy anomalies. This non-stationarity was related to the climate regime that prevailed between 2011 and 2017. We observed significant changes in the interannual variability of salinity above and below the mixed layer depth and a positive difference in the surface barrier layer. In an effort to reconstruct the cause of this phenomenon, a multi-stage investigation was conducted. The first suspected culprit was the change in wind regime over the Mediterranean and Northeast Atlantic regions in September. Using the growing neural gas algorithm, September wind fields over the past 40 years were classified into nine distinct patterns. Further analysis of the CTD data indicated an increase in heat storage, a physical property of the Adriatic Sea known to be strongly influenced by the inflow of warm water masses controlled by the bimodal oscillating system (BiOS). The observed increase in salinity confirmed the assumption that BiOS activity affects heat storage. Unexpectedly, this analysis showed that an inverse vertical salinity profile was present during the summer months of 2015, 2017, and 2020, which can only be explained by salinity changes being a dominant factor. In addition, the aforementioned wind regime caused an increase in energy loss through latent energy dissipation, contributing to an even larger increase in salinity. While changes in the depth of the mixed layer in the Adriatic are usually due to temperature changes, this phenomenon was primarily caused by abrupt changes in salinity due to a combination of BiOS and local factors. This is the first record of such an event. Full article
(This article belongs to the Special Issue New Technologies and Methods in Coastal Observing)
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16 pages, 6189 KiB  
Article
Research on COD Soft Measurement Technology Based on Multi-Parameter Coupling Analysis Method
by Yurui Zhang, Zhiyong Duan, Anzhe Yi, Jiaqi Hu and Yanhu Chen
J. Mar. Sci. Eng. 2022, 10(5), 683; https://doi.org/10.3390/jmse10050683 - 17 May 2022
Cited by 1 | Viewed by 2163
Abstract
This paper presents a soft measurement technique for COD (Chemical Oxygen Demand) based on the multiparameter coupling analysis method. First, through mechanism analysis and correlation analysis of historical data during the measurement process, water quality parameters, such as hydrogen potential (PH), dissolved oxygen [...] Read more.
This paper presents a soft measurement technique for COD (Chemical Oxygen Demand) based on the multiparameter coupling analysis method. First, through mechanism analysis and correlation analysis of historical data during the measurement process, water quality parameters, such as hydrogen potential (PH), dissolved oxygen (DO), turbidity (TU), and electrical conductivity (EC), can be used to estimate COD values. To further improve the estimation accuracy of the water quality parameter model, we adopted a modeling method combining a BP neural network and support vector machine, which showed an average relative error of 6.13% and an absolute coefficient of up to 0.9605. Finally, experiments in a lake environment demonstrate that this method shows excellent performance, with highly reliable and accurate prediction results. Full article
(This article belongs to the Special Issue New Technologies and Methods in Coastal Observing)
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