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Geosciences
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Coastal Environment Monitoring
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Coastal Environment Monitoring

A special issue of Geosciences (ISSN 2076-3263). This special issue belongs to the section "Hydrogeology".

Deadline for manuscript submissions: closed (25 October 2021) | Viewed by 11577

Special Issue Editors

Prof. Dr. Giuseppe Zappalà

E-Mail Website
Guest Editor
CNR-IRBIM, National Research Council, Institute for Biological Resources and Marine Biotechnologies, Spianata S. Raineri, 86, 98122 Messina, Italy
Laboratory of Experimental Oceanology and Marine Ecology (LOSEM), Molo Vespucci, 00053 Civitavecchia (Rome), Tuscia University, Viterbo, Italy
Interests: environmental monitoring; advanced technologies; data acquisition and transmission; monitoring networks; monitoring systems
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Marco Marcelli

E-Mail Website
Guest Editor
Laboratory of Experimental Oceanology and Marine Ecology (LOSEM), Department of Biological and Ecological Sciences, Tuscia University, 01100 Viterbo, Italy
Interests: experimental oceanography; biological oceanography; fluorescence; technological development; marine low-cost technologies; primary production research
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Coastal sites represent very vulnerable environments, not only because they are the water–land interface, but also due to the variety and richness of anthropic activities they host, which that directly or indirectly involve the use of marine or fresh waters (shipyards, maritime transports, aquaculture, fisheries, recreational activities, and so on).

The exploitation of the precious resources of coastal environments is disciplined in the framework of national and international environment protection laws and directives that require a site characterization involving interdisciplinary research activities, through the integration of geology, physics, biology, zoology, chemistry, engineering, etc.

Anthropic activities, with their consequent traffic of ships, cars, and trucks, negatively influence air quality or pollute water bodies; detrimental effects are evident, taking into consideration, among others, the amount of shipyard wastes, aquaculture/fishery wastes, cooling water from industrial plants, and fresh water and sewage effluents released into the environment.

In the last thirty years, a special research interest on coastal advanced monitoring systems has arisen, stimulated by the above-mentioned laws and directives and enabled by the progress in data acquisition and transmission electronic devices that have allowed us to set up and improve low-cost monitoring networks.

Rapid methods and automatic instruments for the detection of microbial and chemical pollutants have been developed and are now in use to assess, almost in real time, the water status; at the same time, autonomous marine vehicles enable studying remote sites which are difficult to be reached; drones can fly over extended study areas to monitor their littoral geomorphology, also hosting airborne instruments for remote sensing, and a great effort is being made both to develop cost-effective technologies and to implement coastal integrated monitoring systems.

This Special Issue aims at hosting contributions on the state-of-the-art of coastal monitoring, focusing on instrumentation development and perspectives; papers dealing with the assessment of environmental status and case studies are also welcome.

Prof. Dr. Giuseppe Zappalà
Prof. Dr. Marco Marcelli
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. Geosciences 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 1800 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 monitoring
  • Monitoring networks
  • Monitoring systems
  • Data acquisition and transmission Detection methods
  • Pollution indicators
  • Oceanographic platforms
  • Cost-effective technologies
  • Coastal observing systems

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Published Papers (4 papers)

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Research

18 pages, 4250 KiB  
Article
Classification Ensembles for Beach Cast and Drifting Vegetation Mapping with Sentinel-2 and PlanetScope
by Florian Uhl, Trine Græsdal Rasmussen and Natascha Oppelt
Geosciences 2022, 12(1), 15; https://doi.org/10.3390/geosciences12010015 - 29 Dec 2021
Cited by 6 | Viewed by 2929
Abstract
Along the Baltic coastline of Germany, drifting vegetation and beach cast create overlays at the otherwise sandy or stony beaches. These overlays influence the morphodynamics and structures of the beaches. To better understand the influence of these patchy habitats on coastal environments, regular [...] Read more.
Along the Baltic coastline of Germany, drifting vegetation and beach cast create overlays at the otherwise sandy or stony beaches. These overlays influence the morphodynamics and structures of the beaches. To better understand the influence of these patchy habitats on coastal environments, regular monitoring is necessary. Most studies, however, have been conducted on spatially larger and temporally more stable occurrences of aquatic vegetation such as floating fields of Sargassum. Nevertheless, drifting vegetation and beach cast pose a particular challenge, as they exhibit high temporal dynamics and sometimes small spatial extent. Regular surveys and mappings are the traditional methods to record their habitats, but they are time-consuming and cost-intensive. Spaceborne remote sensing can provide frequent recordings of the coastal zone at lower cost. Our study therefore aims at the monitoring of drifting vegetation and beach cast on spatial scales between 3 and 10 m. We developed an automated coastline masking algorithm and tested six supervised classification methods and various classification ensembles for their suitability to detect small-scale assemblages of drifting vegetation and beach cast in a study area at the coastline of the Western Baltic Sea using multispectral data of the sensors Sentinel-2 MSI and PlanetScope. The shoreline masking algorithm shows high accuracies in masking the land area while preserving the sand-covered shoreline. We could achieve best classification results using PlanetScope data with an ensemble of a random forest classifier, cart classifier, support vector machine classifier, naïve bayes classifier and stochastic gradient boosting classifier. This ensemble accomplished a combined f1-score of 0.95. The accuracy of the Sentinel-2 classifications was lower but still achieved a combined f1-score of 0.86 for the same ensemble. The results of this study can be considered as a starting point for the development of time series analysis of the vegetation dynamics along Baltic beaches. Full article
(This article belongs to the Special Issue Coastal Environment Monitoring)
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19 pages, 6234 KiB  
Article
Beach Deployment of a Low-Cost GNSS Buoy for Determining Sea-Level and Wave Characteristics
by Philip J. Knight, Cai O. Bird, Alex Sinclair, Jonathan Higham and Andrew J. Plater
Geosciences 2021, 11(12), 494; https://doi.org/10.3390/geosciences11120494 - 1 Dec 2021
Cited by 3 | Viewed by 3282
Abstract
Spatially explicit data on tidal and waves are required as part of coastal monitoring applications (e.g., radar monitoring of coastal change) for the design of interventions to mitigate the impacts of climate change. A deployment over two tidal cycles of a low-cost Global [...] Read more.
Spatially explicit data on tidal and waves are required as part of coastal monitoring applications (e.g., radar monitoring of coastal change) for the design of interventions to mitigate the impacts of climate change. A deployment over two tidal cycles of a low-cost Global Navigation Satellite System (GNSS) buoy at Rossall (near Fleetwood), UK demonstrated the potential to record good quality sea level and wave data within the intertidal zone. During each slack water and the following ebb tide, the sea level data were of good quality and comparable with data from nearby tide gauges on the national tide gauge network. Moreover, the GNSS receiver was able to capture wave information and these compared well with data from a commercial wave buoy situated 9.5 km offshore. Discontinuities were observed in the elevation data during flood tide, coincident with high accelerations and losing satellite signal lock. These were probably due to strong tidal currents, which, combined with spilling waves, would put the mooring line under tension and allow white water to spill over the antenna resulting in the periodic loss of GNSS signals, hence degrading the vertical solutions. Full article
(This article belongs to the Special Issue Coastal Environment Monitoring)
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18 pages, 6468 KiB  
Article
Assessment of the Photosynthetic Response of Posidonia oceanica (Linneaus) Delile, 1813 along a Depth Gradient in the Northern Tyrrhenian Sea (Latium, Italy)
by Alice Madonia, Giulia Caporale, Marina Penna, Simone Bonamano and Marco Marcelli
Geosciences 2021, 11(5), 202; https://doi.org/10.3390/geosciences11050202 - 5 May 2021
Cited by 6 | Viewed by 2361
Abstract
Posidonia oceanica (L.) Delile meadows are recognized to be one of the most productive ecosystems of the Mediterranean basin. Due to the impacts of human activities in coastal areas, seagrasses are experiencing a critical decline. In this context, the understanding of the dynamics [...] Read more.
Posidonia oceanica (L.) Delile meadows are recognized to be one of the most productive ecosystems of the Mediterranean basin. Due to the impacts of human activities in coastal areas, seagrasses are experiencing a critical decline. In this context, the understanding of the dynamics of production and photosynthesis in response to the environmental factors is essential to address efficient conservation strategies that limit this trend and to assess the ecological status of marine ecosystems. Pulse Amplitude Modulated (PAM) fluorometry has been widely implemented to assess seagrass health and productivity. Here we analyzed the photosynthetic dynamics of P. oceanica according to its bathymetric distribution and daily light availability along a depth gradient to be used as baseline for monitoring purposes on the health status of the seagrass meadows in the Northern Tyrrhenian Sea. Moreover, to investigate the effects of the environmental factors on the health status of P. oceanica within the study area through a multidisciplinary approach, the models contained in the Civitavecchia Coastal Environmental Monitoring System were used. In this study, significant photo-physiological changes have been observed among the investigated meadows. Moreover, the integration of physiological and hydrodynamic information allowed the description of how P. oceanica modulates its photosynthetic capacity at different environmental conditions. Full article
(This article belongs to the Special Issue Coastal Environment Monitoring)
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16 pages, 13739 KiB  
Article
Collaborative 3D Monitoring for Coastal Survey: Conclusive Tests and First Feedbacks Using the SELPhCoAST Workflow
by Elsa Cariou, Agnes Baltzer, Donatienne Leparoux and Vincent Lacombe
Geosciences 2021, 11(3), 114; https://doi.org/10.3390/geosciences11030114 - 2 Mar 2021
Cited by 3 | Viewed by 1652
Abstract
“Structure from Motion” by smart devices photography (SfM-S) is a current promising tool to support 3D participatory monitoring of heritage and geosites. Within the ODySéYeu scientific project, which aims to analyze the sedimentary dynamics around the isle of Yeu (France), a consortium of [...] Read more.
“Structure from Motion” by smart devices photography (SfM-S) is a current promising tool to support 3D participatory monitoring of heritage and geosites. Within the ODySéYeu scientific project, which aims to analyze the sedimentary dynamics around the isle of Yeu (France), a consortium of different local actors was invited to collectively develop an integrated solution to monitor the coastal evolution of the isle in 3D. This new solution is composed of a combination of an application (SENTINELLES de la côte) and a specific workflow (SELPhCoAST), which guides citizens to acquire reliable in-situ photo datasets with their own smart device, facilitates data transmission, and allows both a reliable data treatment and a public presentation of matters and results. This study presents the results of reproducibility and accuracy tests performed on a test-site to validate the SELPhCoAST workflow, over 20 months of monitoring, with multiple operators and devices. Tests show that at least 95% of each SfM-S model is identical to the terrestrial laser scans models within a range of ±5 cm, almost independently of the operator or smartphone model. This study highlights the interest of this cost-effective participatory solution to understand coastal erosion processes, and facilitate the establishment of soft and nature-based solutions of protection, management or restoration of sites. Full article
(This article belongs to the Special Issue Coastal Environment Monitoring)
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