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JMSE
Special Issues
Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography
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Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography

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

Deadline for manuscript submissions: 25 June 2024 | Viewed by 8174

Special Issue Editors

Dr. Juan J. Munoz-Perez

E-Mail Website
Guest Editor
Faculty of Marine Science, CASEM, Rio San Pedro s/n, University of Cadiz, 11510 Puerto Real, Spain
Interests: reef-supported beaches; sediment transportation; coastal engineering; coastal management; littoral dunes; sand characteristics; sinking phenomenon
Special Issues, Collections and Topics in MDPI journals
Dr. Bismarck Jigena-Antelo

E-Mail Website1 Website2 Website3
Guest Editor
Department of Nautical Sciences and Naval Construction, CASEM, College of Marine, Nautical Sciences and Radioelectronic Engineering, University of Cadiz, 11003 Cádiz, Spain
Interests: geodesy; topography; GPS; GIS; remote sensing; hydrography; hydrology; nautical sciences

Special Issue Information

Dear Colleagues,

Natural or anthropic phenomena such as sea level rise, storms, river floods or sediment transport induce alterations in the morphology of our littoral. Human settlements on the banks of rivers and seas, whose population continues to increase, are affected. Therefore, managers need data that allows them to make decisions with which to propose solutions to the problems arising from these changes. Thus, monitoring the evolution of these environments, both aerial and submerged, has become an urgent need nowadays. The objective of this special issue is to collect recent experiences regarding this topic that allow us to have an updated vision of the existing problems and their possible solutions.

Dr. Juan J. Munoz-Perez
Dr. Bismarck Jigena-Antelo
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

  • hydrography
  • beaches
  • navigation
  • remote sensing
  • hydrology
  • survey
  • coastal monitoring
  • waterways

Published Papers (7 papers)

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Research

18 pages, 2337 KiB  
Article
Port State Control Inspections under the Paris Memorandum of Understanding and Their Contribution to Maritime Safety: Additional Risk Classifications and Indicators Using Multivariate Techniques
by David Almorza, Jose Manuel Prieto, Víctor Amor-Esteban and Francisco Piniella
J. Mar. Sci. Eng. 2024, 12(4), 533; https://doi.org/10.3390/jmse12040533 - 23 Mar 2024
Viewed by 607
Abstract
Port State Control (PSC) inspections conducted under the Paris Memorandum of Understanding (MoU) agreement have become a crucial tool for maritime administrations in European Union countries to ensure compliance with international maritime safety standards by ships entering their ports. This paper analyses all [...] Read more.
Port State Control (PSC) inspections conducted under the Paris Memorandum of Understanding (MoU) agreement have become a crucial tool for maritime administrations in European Union countries to ensure compliance with international maritime safety standards by ships entering their ports. This paper analyses all PSC inspections conducted in 10 major European ports belonging to the Paris MoU between 2012 and 2019. For its study, a multivariate HJ-Biplot statistical analysis is carried out, which facilitates the interpretation and understanding of the underlying relationships in a multivariate data set by representing a synthesis of the data on a factorial plane, with an interpretation that is very intuitive and accessible for readers from various fields. Applying this method with ship characteristics as explanatory variables, several classifications were derived. These classifications align with the annual performance lists published by the Paris MoU and the International Association of Classification Societies list, suggesting that this method could serve as a reliable classification approach. It provides maritime authorities with an additional indicator of a ship’s risk profile, aiding in the prioritising of inspections. The method also effectively categorises ports and types of ships used for cargo transport, offering insights into the specific maritime traffic each port experiences. Furthermore, this study identifies characteristics associated with substandard ships, which is a primary objective of PSC inspections. Beyond revealing these traits, this research underscores the existence of several readily applicable techniques to enhance maritime safety and reduce the risk of ocean pollution. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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14 pages, 3631 KiB  
Article
Oil Spill Classification Using an Autoencoder and Hyperspectral Technology
by María Gema Carrasco-García, María Inmaculada Rodríguez-García, Juan Jesús Ruíz-Aguilar, Lipika Deka, David Elizondo and Ignacio José Turias Domínguez
J. Mar. Sci. Eng. 2024, 12(3), 495; https://doi.org/10.3390/jmse12030495 - 15 Mar 2024
Viewed by 565
Abstract
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the ideal solution. This research [...] Read more.
Hyperspectral technology has been playing a leading role in monitoring oil spills in marine environments, which is an issue of international concern. In the case of monitoring oil spills in local areas, hyperspectral technology of small dimensions is the ideal solution. This research explores the use of encoded hyperspectral signatures to develop automated classifiers capable of discriminating between polluted and clean water and distinguishing between various types of oil. The overall objective is to leverage these classifiers to be able to improve the performance of conventional systems that rely solely on hyperspectral imagery. The acquisition of the hyperspectral signatures of water and hydrocarbons was carried out with a spectroradiometer. The range of the spectroradiometer used in this study covers the ranges between [350–1000] (visible near-infrared) and [1000–2500] (short-wavelength infrared). This gives detailed information regarding the targets of interest. Different neural autoencoders (AEs) have been developed to reduce inputs into different dimensions, from 1 to 15. Each of these encoded sets was used to train decision tree (DT) classifiers. The results are very promising, as they show that the AE models encoded data with correlation coefficients above 0.95. The classifiers trained with the different sets provide accuracies close to 1. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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16 pages, 9005 KiB  
Article
Air Pollution PM10 Forecasting Maps in the Maritime Area of the Bay of Algeciras (Spain)
by María Inmaculada Rodríguez-García, María Gema Carrasco-García, Maria da Conceição Rodrigues Ribeiro, Javier González-Enrique, Juan Jesús Ruiz-Aguilar and Ignacio J. Turias
J. Mar. Sci. Eng. 2024, 12(3), 397; https://doi.org/10.3390/jmse12030397 - 25 Feb 2024
Viewed by 682
Abstract
Predicting the levels of a pollutant in a given area is an open problem, mainly because historical data are typically available at certain locations, where monitoring stations are located, but not at all locations in the area. This work presents an approach based [...] Read more.
Predicting the levels of a pollutant in a given area is an open problem, mainly because historical data are typically available at certain locations, where monitoring stations are located, but not at all locations in the area. This work presents an approach based on developing predictions at each of the points where an immission station is available; in this case, based on shallow Artificial Neural Networks, ANNs, and then using a simple geostatistical interpolation algorithm (Inverse Distance Weighted, IDW), a pollutant map is constructed over the entire study area, thus providing predictions at each point in the plane. The ANN models are designed to make 1 h ahead and 4 h ahead predictions, using an autoregressive scheme as inputs (in the case of 4 h ahead as a jumping strategy). The results are then compared using the Friedman and Bonferroni tests to select the best model at each location, and predictions are made with all the best models. In general, to the 1 h ahead prediction models, the optimal models typically have fewer neurons and require minimal historical data. For instance, the best model in Algeciras has an R of almost 0.89 and consists of 1 hidden neuron and 3 to 5 lags, similar to Colegio Los Barrios. In the case of 4h ahead prediction, Colegio Carteya station shows the best model, with an R of almost 0.89 and a MSE of less than 240, including 5 hidden neurons and different lags from the past. The results are sufficiently adequate, especially in the case of predictions 4 h into the future. The aim is to integrate the models into a tool for citizens and administrations to make decisions. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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16 pages, 9534 KiB  
Article
Prediction of Beach Sand Particle Size Based on Artificial Intelligence Technology Using Low-Altitude Drone Images
by Ho-Jun Yoo, Hyoseob Kim, Tae-Soon Kang, Ki-Hyun Kim, Ki-Young Bang, Jong-Beom Kim and Moon-Sang Park
J. Mar. Sci. Eng. 2024, 12(1), 172; https://doi.org/10.3390/jmse12010172 - 16 Jan 2024
Cited by 1 | Viewed by 800
Abstract
Coastal erosion is caused by various factors, such as harbor development along coastal areas and climate change. Erosion has been accelerated recently due to sea level rises, increased occurrence of swells, and higher-power storm waves. Proper understanding of the complex coastal erosion process [...] Read more.
Coastal erosion is caused by various factors, such as harbor development along coastal areas and climate change. Erosion has been accelerated recently due to sea level rises, increased occurrence of swells, and higher-power storm waves. Proper understanding of the complex coastal erosion process is vital to prepare measures when they are needed. Monitoring systems have been widely established around a high portion of the Korean coastline, supported by several levels of governments, but valid analysis of the collected data and the following preparation of measures have not been highly effective yet. In this paper, we use a drone to obtain bed material images, and an analysis system to predict the representative grain size of beach sands from the images based on artificial intelligence (AI) analysis. The predicted grain sizes are verified via field samplings. Field bed material samples for the particle size analysis are collected during two seasons, while a drone takes photo images and the exact positions are simultaneously measured at Jangsa beach, Republic of Korea. The learning and testing results of the AI technology are considered satisfactory. Finally, they are used to diagnose the overall stability of Jangsa beach. A beach diagnostic grade is proposed here, which reflects the topography of a beach and the distribution of sediments on the beach. The developed beach diagnostic grade could be used as an indicator of any beach stability on the east coast of the Republic of Korea. When the diagnostic grade changes rapidly at a beach, it is required to undergo thorough investigation to understand the reason and foresee the future of the beach conditions, if we want the beach to function as well as before. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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20 pages, 9113 KiB  
Article
Comparison between the Employment of a Multibeam Echosounder on an Unmanned Surface Vehicle and Traditional Photogrammetry as Techniques for Documentation and Monitoring of Shallow-Water Cultural Heritage Sites: A Case Study in the Bay of Algeciras
by Soledad Solana Rubio, Alberto Salas Romero, Felipe Cerezo Andreo, Raúl González Gallero, Juan Rengel, Luis Rioja, Joaquín Callejo and Manuel Bethencourt
J. Mar. Sci. Eng. 2023, 11(7), 1339; https://doi.org/10.3390/jmse11071339 - 30 Jun 2023
Cited by 5 | Viewed by 1259
Abstract
Over the last few years, due to various climatic, anthropogenic, and environmental factors, a large amount of submerged heritage has been unearthed and exposed to deterioration processes in the Bay of Algeciras. These impacts can be more severe in shallow waters, where the [...] Read more.
Over the last few years, due to various climatic, anthropogenic, and environmental factors, a large amount of submerged heritage has been unearthed and exposed to deterioration processes in the Bay of Algeciras. These impacts can be more severe in shallow waters, where the cultural heritage is more vulnerable to natural and human-induced impacts. This makes it urgent to document cultural heritage at risk of disappearing using different techniques whose efficiencies in the archaeological record need to be determined and compared. For this purpose, we have documented a shipwreck in the Bay of Algeciras using two techniques: photogrammetry and a multibeam echosounder. The photogrammetric method consists of obtaining a 3D model from numerous photographs taken of an object or a site. The processing software creates three-dimensional points from two-dimensional points found in the photographs that are equivalent to each other. Multibeam echosounders are capable of providing side scan imagery information in addition to generating contour maps and 3D perspectives of the surveyed area and can be installed in an unmanned surface vehicle. As a result, we have obtained two 3D visualisations of the shipwreck, i.e., digital copies, that are being used both for the analysis of its naval architecture and for its dissemination. Through the comparison of the two techniques, we have concluded that while a multibeam echosounder provides a detailed digital terrain model of the seabed, photogrammetry performed by divers gives the highest resolution data on objects and structures. In conclusion, our results demonstrate the benefits of this combined approach for accurately documenting and monitoring shipwrecks in shallow waters, providing valuable information for conservation and management efforts. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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19 pages, 2636 KiB  
Article
A Methodological Proposal for the Management of Submerged Cultural Heritage: Study Cases from Cartagena de Indias, Colombia
by Diana María Quintana-Saavedra, Rafael Ricardo Torres-Parra, Richard Guzmán-Martínez, Giorgio Anfuso, Juan Jose Muñoz-Pérez, Saul Vallejo and Bismarck Jigena-Antelo
J. Mar. Sci. Eng. 2023, 11(4), 694; https://doi.org/10.3390/jmse11040694 - 24 Mar 2023
Cited by 1 | Viewed by 1370
Abstract
This paper proposes a comprehensive methodology for the management of submerged cultural heritage sites despite their worldwide location. The methodology is applied to four colonial shipwrecks located in Cartagena de Indias Bay (Colombia), two of them in the Inner Bay and two in [...] Read more.
This paper proposes a comprehensive methodology for the management of submerged cultural heritage sites despite their worldwide location. The methodology is applied to four colonial shipwrecks located in Cartagena de Indias Bay (Colombia), two of them in the Inner Bay and two in the Bocachica sector. Five criteria are used and scored from 1 (indicating a low risk for the wreck) to 5 (high risk). The sum of the scores obtained at each criterion ranges from 5 to 25, and when the value obtained is higher than 15, management action is required. Five criteria were analyzed; (i) The historical criterion is based on the antiquity of the wreck. The ones investigated in this paper are associated with the Battle of Cartagena de Indias (A.D. 1741), having been submerged for ~280 years (all wrecks obtained a score of 3); (ii) The geographical criterion concerns the depth at which the wreck is located, which determines its accessibility. In Cartagena Bay, wrecks are situated at a water depth between 15.6 and 29.7 m (all wrecks were scored 4); (iii) The shipwreck condition criterion indicates the level of preservation, including organic and inorganic material, distinguishing among wooden hulls, ballast stones, and cannons. Obtained scores were 4 and 3 for the wrecks, respectively, located in the Inner Bay and in the Bocachica sector. (iv) The oceanographic criterion, linked to chemical and biological conditions of the water column, influences wreck conservation. All wrecks investigated scored 5. (v) The socioeconomic criterion indicates the multiple maritime and cultural activities presently taking place that might affect the wreck. In Cartagena Bay, all wrecks were scored 4. According to the total score obtained (20—Inner Bay and 19—Bocachica sector), guidelines for shipwreck conservation of cultural heritage in Cartagena Bay are proposed. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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14 pages, 2544 KiB  
Article
Increase in the Erosion Rate Due to the Impact of Climate Change on Sea Level Rise: Victoria Beach, a Case Study
by Maria Aguilera-Vidal, Juan J. Muñoz-Perez, Antonio Contreras, Francisco Contreras, Patricia Lopez-Garcia and Bismarck Jigena
J. Mar. Sci. Eng. 2022, 10(12), 1912; https://doi.org/10.3390/jmse10121912 - 05 Dec 2022
Cited by 4 | Viewed by 1729
Abstract
This article provides a general methodology for calculating the retreat of the coastline and the volume of sand necessary to renourish a beach due to sea level rise (SLR) in the medium-long term. An example is presented, Victoria Beach, and a projection is [...] Read more.
This article provides a general methodology for calculating the retreat of the coastline and the volume of sand necessary to renourish a beach due to sea level rise (SLR) in the medium-long term. An example is presented, Victoria Beach, and a projection is made for the years 2030, 2040, 2050, and 2100. The results obtained take into account global sea level rise (GSLR), which is worldwide, and local sea level rise (LSLR), which considers climate variability and vertical land movements. Regarding GSLR, data were provided by the projections from IPCC (Intergovernmental Panel on Climate Change) scenarios and empirical models, such as Rahmstorf and Pfeffer. The LSLR data came from the tide gauge station located in Cadiz. Finally, the results obtained showed that global warming impacts erosive effects and the subsequent volume of sand required to renourish beaches. The total sea level rise (TSLR) projections indicated for Victoria Beach are relatively higher than the GSLR projections. Even in the best IPCC scenario (RCP 2.6), Victoria Beach presents a significant erosion of 52 m, requiring a volume of sand of 1.0 Mm3 to supply renourishment. Full article
(This article belongs to the Special Issue Recent Experiences and Monitoring in Coastal, Fluvial and Marine Hydrography)
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Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

Title: Shoreline changes detection in San Andres island, Colombian Caribean, using satellite imaginery
Authors: Cabarcas-Mier, Angelica
Affiliation: Universidad de Cádizdisabled, Cadiz, Spain
Abstract: Shoreline changes detection in San Andres island, Colombian Caribean, using satellite imaginery

Title: Temporal and spatial evolution of the coastline in the Peruvian coast, using remote sensing and geographic information systems
Authors: Alpaca, Cesar
Affiliation: Alpaca, Cesar
Abstract: Temporal and spatial evolution of the coastline in the Peruvian coast, using remote sensing and geographic information systems

Title: Application of magnetometry and high resolution bathymetry techniques for the determination of underwater topography
Authors: Karem Oviedo-Prada
Affiliation: Karem Oviedo-Prada
Abstract: Application of magnetometry and high resolution bathymetry techniques for the determination of underwater topography

Title: Changes in the coastline of the Archipelago of San Andrés, Providencia and Santa Catalina, detected from satellite images analysis.
Authors: Cabarcas-Mier, Angélica; Rey-Sanchez, Wilmer; Jigena-Antelo, Bismarck; Contreras, Antonio; Muñoz-Pérez, Juan José
Affiliation: University of Cadiz, Department of Nautical Sciences and Naval Construction, CASEM, College of Marine, Nautical Sciences and Radioelectronic Engineering, 11003 Cádiz, Spain
Abstract: Changes in the coastline of the Archipelago of San Andrés, Providencia and Santa Catalina, detected from satellite images analysis.

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