Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
3.7
2.9
Journals
JMSE
Special Issues
Maritime Environment Monitoring
share announcement

Maritime Environment Monitoring

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312).

Deadline for manuscript submissions: closed (4 December 2017) | Viewed by 47290

Special Issue Editors

Dr. Gabriele Pieri

E-Mail Website
Guest Editor
Institute of Information Science and Technologies, Pisa, Italy
Interests: Image processing for marine environment; multi-source data fusion; environmental decision support systems; marine information systems; machine learning methods; multimedia data integration
Special Issues, Collections and Topics in MDPI journals
Dr. Ovidio Salvetti

E-Mail Website
Guest Editor
Institute of Information Science and Technologies, National Research Council of Italy, Signals and Images Laboratory, Via Moruzzi, 1-56124 Pisa, Italy
Interests: image analysis and understanding; multimedia information systems; spatial modeling and intelligent processes in computer vision and information technology; sea technologies and applications
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Protection and monitoring of maritime environments have become increasingly important due to several different factors. The reasons behind this increase are very heterogeneous and range from the high demand of oil-based products, leading to a growth of maritime traffic, to the increased amount of garbage produced by society, which endangers both protected and regular coastal and marine areas, and, furthermore, with the fast and great rise of migration flows arriving to Western countries. All these factors, combined with the augmented computational and storage capability of technological systems, and with an increased availability of data regarding the marine and maritime environment, has made it possible to have a range of varieties of information systems for the study, monitoring, and proactive support to decision makers. In general, these information systems respond to the needs in the development of intelligent systems dealing with the management of maritime spatial data, for applications related to either scientific research, safety, or maritime industry.

This Special Issue aims to cover these various and heterogeneous aspects, related to maritime environment monitoring, bringing together researchers in their respective fields to share their experiences.

The main subjects covered by this Special Issue can be summarized by the following five topics:

  • Research and applications on maritime systems for the support of decision makers;
  • Research on sensors and marine data acquisition and management;
  • Research on the smart management and integration of real-time maritime heterogeneous data;
  • Research and applications on smart interfaces for the management of real-time maritime information systems
  • Research and applications for the support of maritime industry and related organizations. 

Dr. Gabriele Pieri
Dr. Ovidio Salvetti
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

  • Decision support systems
  • Information systems interfaces
  • Real-time data management
  • Marine/Maritime sensors data acquisition
  • Heterogeneous data integration
  • Maritime data technology and applications
  • Marine/Maritime data forecasting
  • Event detection
  • Pro-active maritime information systems

Published Papers (6 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

12 pages, 4598 KiB  
Article
Monitoring Litter Inputs from the Adour River (Southwest France) to the Marine Environment
by Antoine Bruge, Cristina Barreau, Jérémy Carlot, Hélène Collin, Clément Moreno and Philippe Maison
J. Mar. Sci. Eng. 2018, 6(1), 24; https://doi.org/10.3390/jmse6010024 - 6 Mar 2018
Cited by 58 | Viewed by 6806
Abstract
Rivers are major pathways for litter to enter the ocean, especially plastic debris. Yet, further research is needed to improve knowledge on rivers contribution, increase data availability, refine litter origins, and develop relevant solutions to limit riverine litter inputs. This study presents the [...] Read more.
Rivers are major pathways for litter to enter the ocean, especially plastic debris. Yet, further research is needed to improve knowledge on rivers contribution, increase data availability, refine litter origins, and develop relevant solutions to limit riverine litter inputs. This study presents the results of three years of aquatic litter monitoring on the Adour river catchment (southwest of France). Litter monitoring consisted of collecting all litter stranded on river banks or stuck in the riparian vegetation in defined areas identified from cartographic and hydromorphological analyses, and with the support of local stakeholders. Litter samples were then sorted and counted according to a list of items containing 130 categories. Since 2014, 278 litter samplings were carried out, and 120,632 litter items were collected, sorted, and counted. 41% of litter could not be identified due to high degradation. Food and beverage packaging, smoking-related items, sewage related debris, fishery and mariculture gear, and common household items represented around 70% of identifiable items. Overall, the present study contributes to our knowledge of litter sources and pathways, with the target of reducing the amounts entering the ocean. The long-term application of this monitoring is a way forward to measure societal changes as well as assess effectiveness of measures. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

25 pages, 1588 KiB  
Article
The Level of Automation in Emergency Quick Disconnect Decision Making
by Imset Marius, Falk Kristin, Kjørstad Marianne and Nazir Salman
J. Mar. Sci. Eng. 2018, 6(1), 17; https://doi.org/10.3390/jmse6010017 - 12 Feb 2018
Cited by 4 | Viewed by 5876
Abstract
As a key measure for safety and environmental protection during offshore well operations, drill rigs are equipped with Emergency Quick Disconnect (EQD) systems. However, an EQD operation is in itself considered a risky operation with a major economic impact. For this reason, it [...] Read more.
As a key measure for safety and environmental protection during offshore well operations, drill rigs are equipped with Emergency Quick Disconnect (EQD) systems. However, an EQD operation is in itself considered a risky operation with a major economic impact. For this reason, it is of great importance to aid the operators in their assessment of the situation at all times, and help them make the best decisions. However, despite the availability of such systems, accidents do happen. This demonstrates the vulnerability of our human decision-making capabilities in extremely stressful situations. One way of improving the overall human-system performance with respect to EQD is to increase the level and quality of the automation and decision support systems. Although there is plenty of evidence that automated systems have weaknesses, there is also evidence that advanced software systems outperform humans in complex decision-making. The major challenge is to make sure that EQD is performed when necessary, but there is also a need to decrease the number of false EQDs. This paper applies an existing framework for levels of automation in order to explore the critical decision process leading to an EQD. We provide an overview of the benefits and drawbacks of existing automation and decision support systems vs. manual human decision-making. Data are collected from interviews of offshore users, suppliers, and oil companies, as well as from formal operational procedures. Findings are discussed using an established framework for the level of automation. Our conclusion is that there is an appropriate level of automation in critical situations related to the loss of the position of the drill rig, and that there is the promising potential to increase the autonomy level in a mid- and long-term situation assessment. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

19 pages, 6652 KiB  
Article
A Marine Information System for Environmental Monitoring: ARGO-MIS
by Gabriele Pieri, Michele Cocco and Ovidio Salvetti
J. Mar. Sci. Eng. 2018, 6(1), 15; https://doi.org/10.3390/jmse6010015 - 5 Feb 2018
Cited by 18 | Viewed by 6562
Abstract
Sea shipping routes have become very crowded and this, coupled with an always increasing demand of oil based products, contributes to the increase in maritime traffic density, as a consequence pollution risks have increased. Therefore, it is important to have information systems capable [...] Read more.
Sea shipping routes have become very crowded and this, coupled with an always increasing demand of oil based products, contributes to the increase in maritime traffic density, as a consequence pollution risks have increased. Therefore, it is important to have information systems capable of detecting and monitoring environmental endangering situations like oil spills at sea. In this paper, a Marine Information System, acting as an integrated and inter-operable monitoring tool is proposed and discussed. The discussion focuses on a system that is able to integrate different data acquired from various electronic sensors, and that is inter-operable among marine operators and ship traffic authorities. The available data on the system are all geo-referenced, and flows seamlessly through the system, where they are integrated in a consistent and usable manner. An important result of this integration is the capability to produce a collection of proactive services such as Decision Support ones, which can be used to improve the functionalities and facilities concerned in an intervention operation. Through the implementation of these services, we aim to demonstrate how an efficient environmental management system could benefit from being supported by a Marine Information System that can provide the dynamic links between different data, models and actors. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

13 pages, 20579 KiB  
Article
Evaluation of Underwater Image Enhancement Algorithms under Different Environmental Conditions
by Marino Mangeruga, Marco Cozza and Fabio Bruno
J. Mar. Sci. Eng. 2018, 6(1), 10; https://doi.org/10.3390/jmse6010010 - 16 Jan 2018
Cited by 41 | Viewed by 9498
Abstract
Underwater images usually suffer from poor visibility, lack of contrast and colour casting, mainly due to light absorption and scattering. In literature, there are many algorithms aimed to enhance the quality of underwater images through different approaches. Our purpose was to identify an [...] Read more.
Underwater images usually suffer from poor visibility, lack of contrast and colour casting, mainly due to light absorption and scattering. In literature, there are many algorithms aimed to enhance the quality of underwater images through different approaches. Our purpose was to identify an algorithm that performs well in different environmental conditions. We have selected some algorithms from the state of the art and we have employed them to enhance a dataset of images produced in various underwater sites, representing different environmental and illumination conditions. These enhanced images have been evaluated through some quantitative metrics. By analysing the results of these metrics, we tried to understand which of the selected algorithms performed better than the others. Another purpose of our research was to establish if a quantitative metric was enough to judge the behaviour of an underwater image enhancement algorithm. We aim to demonstrate that, even if the metrics can provide an indicative estimation of image quality, they could lead to inconsistent or erroneous evaluations. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

12 pages, 12433 KiB  
Article
Oil Spill Detection and Mapping Using Sentinel 2 Imagery
by Polychronis Kolokoussis and Vassilia Karathanassi
J. Mar. Sci. Eng. 2018, 6(1), 4; https://doi.org/10.3390/jmse6010004 - 6 Jan 2018
Cited by 77 | Viewed by 10825
Abstract
Two object-based image analysis methods are developed for detecting oil spills from known natural outflows as well as light oil spill events using Sentinel 2 imagery. The methods are applied to Sentinel 2 images of a known area of natural oil outflow as [...] Read more.
Two object-based image analysis methods are developed for detecting oil spills from known natural outflows as well as light oil spill events using Sentinel 2 imagery. The methods are applied to Sentinel 2 images of a known area of natural oil outflow as well as on a Sentinel 2 image of a recent oil spill event along the south coast of Athens, Greece. The preliminary results are considered very successful and consistent, with a high degree of applicability to other Sentinel 2 satellite images. Further testing and fine tuning of the proposed object-based methodology should be carried out using atmospheric correction and ground truth. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

20 pages, 1889 KiB  
Article
Automated Image Analysis of Offshore Infrastructure Marine Biofouling
by Kate Gormley, Faron McLellan, Christopher McCabe, Claire Hinton, Joseph Ferris, David I. Kline and Beth E. Scott
J. Mar. Sci. Eng. 2018, 6(1), 2; https://doi.org/10.3390/jmse6010002 - 3 Jan 2018
Cited by 35 | Viewed by 7002
Abstract
In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs). The project [...] Read more.
In the UK, some of the oldest oil and gas installations have been in the water for over 40 years and have considerable colonisation by marine organisms, which may lead to both industry challenges and/or potential biodiversity benefits (e.g., artificial reefs). The project objective was to test the use of an automated image analysis software (CoralNet) on images of marine biofouling from offshore platforms on the UK continental shelf, with the aim of (i) training the software to identify the main marine biofouling organisms on UK platforms; (ii) testing the software performance on 3 platforms under 3 different analysis criteria (methods A–C); (iii) calculating the percentage cover of marine biofouling organisms and (iv) providing recommendations to industry. Following software training with 857 images, and testing of three platforms, results showed that diversity of the three platforms ranged from low (in the central North Sea) to moderate (in the northern North Sea). The two central North Sea platforms were dominated by the plumose anemone Metridium dianthus; and the northern North Sea platform showed less obvious species domination. Three different analysis criteria were created, where the method of selection of points, number of points assessed and confidence level thresholds (CT) varied: (method A) random selection of 20 points with CT 80%, (method B) stratified random of 50 points with CT of 90% and (method C) a grid approach of 100 points with CT of 90%. Performed across the three platforms, the results showed that there were no significant differences across the majority of species and comparison pairs. No significant difference (across all species) was noted between confirmed annotations methods (A, B and C). It was considered that the software performed well for the classification of the main fouling species in the North Sea. Overall, the study showed that the use of automated image analysis software may enable a more efficient and consistent approach to marine biofouling analysis on offshore structures; enabling the collection of environmental data for decommissioning and other operational industries. Full article
(This article belongs to the Special Issue Maritime Environment Monitoring)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-6
Back to TopTop