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Remote Sensing
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Application of Remote Sensing in Coastline Monitoring
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Application of Remote Sensing in Coastline Monitoring

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing Image Processing".

Deadline for manuscript submissions: 15 June 2025 | Viewed by 3869

Special Issue Editors

Prof. Dr. Paolo Ciavola

E-Mail Website
Guest Editor
Department of Physics and Earth Sciences, University of Ferrara, 44122 Ferrara, Italy
Interests: coastal hazards; risk evaluation; geomorphology; coastal dynamics; sediment transport
Special Issues, Collections and Topics in MDPI journals
Dr. Clara Armaroli

E-Mail Website
Guest Editor
Department of Biological, Geological, and Environmental Sciences, University of Bologna Alma Mater Studiorum, 40126 Bologna, Italy
Interests: coastal morphodynamics; coastal geomorphology; coastal risks (beach erosion and flooding); dune system dynamics and storm impacts; remote sensing; coastal hazards; risk evaluation
Dr. Juan Montes Pérez

E-Mail Website
Guest Editor
Department of Earth Sciences, International Campus of Excellence of the Sea (CEI·MAR), University of Cadiz, 11519 Cadiz, Spain
Interests: coastal geomorphology; coastal hazards; coastal processes; risk evaluation; remote sensing

Special Issue Information

Dear Colleagues,

Coastal environments are controlled and influenced by numerous natural and human-induced factors that can generate negative consequences exacerbated by the influence of climate change. At the global level, most of the population and economic activities are located along coastal areas. There is a strong need to efficiently monitor coastal systems to improve knowledge of the processes that control their evolution and to enable improve current and future coastal management.

The morphologies of coastal areas are extremely diverse, and their dynamic behaviour constrains the use of traditional coastal monitoring methods due to their low temporal resolution and/or limited spatial coverage. Remote sensing techniques have already proven to be able to overcome these problems by enabling the development of large datasets that can be used to describe the evolution of coastal areas worldwide.

This Special Issue aims to explore new techniques for monitoring geomorphological changes and processes in coastal areas. Studies that cover recent advancements in EO data processing methodologies, techniques, and future developments are welcome, as are studies focused on, but not limited to, the following aspects:

  • Remote-sensing-based shoreline detection and evolution analysis;
  • Erosion and accretion processes induced by hydrodynamic conditions;
  • Coastal sediment dynamics, including river–coast connectivity;
  • Morphological changes and evolution of dune systems;
  • Short- and long-term evolution of coastal wetlands;
  • Rocky coast dynamics;
  • Integration of remote sensing datasets for long-term studies of coastal evolution;

New remote sensing tools for coastal studies.

Prof. Dr. Paolo Ciavola
Dr. Clara Armaroli
Dr. Juan Montes Pérez
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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 morphodynamics
  • coastal evolution
  • earth observation data
  • shoreline
  • coastal wetlands
  • dunes
  • rocky shores
  • satellite images
  • UAVs
  • video monitoring systems

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Published Papers (3 papers)

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Research

21 pages, 7656 KiB  
Article
Multitemporal Monitoring for Cliff Failure Potential Using Close-Range Remote Sensing Techniques at Navagio Beach, Greece
by Aliki Konsolaki, Efstratios Karantanellis, Emmanuel Vassilakis, Evelina Kotsi and Efthymios Lekkas
Remote Sens. 2024, 16(23), 4610; https://doi.org/10.3390/rs16234610 - 9 Dec 2024
Cited by 1 | Viewed by 972
Abstract
This study aims to address the challenges associated with rockfall assessment and monitoring, focusing on the coastal cliffs of “Navagio Shipwreck Beach” in Zakynthos. A complete time-series analysis was conducted using state-of-the-art methodologies including a 2020 survey using unmanned aerial systems (UASs) and [...] Read more.
This study aims to address the challenges associated with rockfall assessment and monitoring, focusing on the coastal cliffs of “Navagio Shipwreck Beach” in Zakynthos. A complete time-series analysis was conducted using state-of-the-art methodologies including a 2020 survey using unmanned aerial systems (UASs) and two subsequent surveys, incorporating terrestrial laser scanning (TLS) and UAS survey techniques in 2023. Achieving high precision and accuracy in georeferencing involving direct georeferencing, the utilization of pseudo ground control points (pGCPs), and integrating post-processing kinematics (PPK) with global navigation satellite system (GNSS) permanent stations’ RINEX data is necessary for co-registering the multitemporal models effectively. For the change detection analysis, UAS surveys were utilized, employing the multiscale model-to-model cloud comparison (M3C2) algorithm, while TLS data were used in a validation methodology due to their very high-resolution model. The synergy of these advanced technologies and methodologies offers a comprehensive understanding of rockfall dynamics, aiding in effective assessment and monitoring strategies for coastal cliffs prone to rockfall risk. Full article
(This article belongs to the Special Issue Application of Remote Sensing in Coastline Monitoring)
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23 pages, 4848 KiB  
Article
Summer Chukchi Sea Near-Surface Salinity Variability in Satellite Observations and Ocean Models
by Semyon A. Grodsky, Nicolas Reul and Douglas Vandemark
Remote Sens. 2024, 16(18), 3397; https://doi.org/10.3390/rs16183397 - 12 Sep 2024
Viewed by 1183
Abstract
The Chukchi Sea is an open estuary in the southwestern Arctic. Its near-surface salinities are higher than those of the surrounding open Arctic waters due to the key inflow of saltier and warmer Pacific waters through the Bering Strait. This salinity distribution may [...] Read more.
The Chukchi Sea is an open estuary in the southwestern Arctic. Its near-surface salinities are higher than those of the surrounding open Arctic waters due to the key inflow of saltier and warmer Pacific waters through the Bering Strait. This salinity distribution may suggest that interannual changes in the Bering Strait mass transport are the sole and dominant factor shaping the salinity distribution in the downstream Chukchi Sea. Using satellite sea surface salinity (SSS) retrievals and altimetry-based estimates of the Bering Strait transport, the relationship between the Strait transport and Chukchi Sea SSS distributions is analyzed from 2010 onward, focusing on the ice-free summer to fall period. A comparison of five different satellite SSS products shows that anomalous SSS spatially averaged over the Chukchi Sea during the ice-free period is consistent among them. Observed interannual temporal change in satellite SSS is confirmed by comparison with collocated ship-based thermosalinograph transect datasets. Bering Strait transport variability is known to be driven by the local meridional wind stress and by the Pacific-to-Arctic sea level gradient (pressure head). This pressure head, in turn, is related to an Arctic Oscillation-like atmospheric mean sea level pattern over the high-latitude Arctic, which governs anomalous zonal winds over the Chukchi Sea and affects its sea level through Ekman dynamics. Satellite SSS anomalies averaged over the Chukchi Sea show a positive correlation with preceding months’ Strait transport anomalies. This correlation is confirmed using two longer (>40-year), separate ocean data assimilation models, with either higher- (0.1°) or lower-resolution (0.25°) spatial resolution. The relationship between the Strait transport and Chukchi Sea SSS anomalies is generally stronger in the low-resolution model. The area of SSS response correlated with the Strait transport is located along the northern coast of the Chukotka Peninsula in the Siberian Coastal Current and adjacent zones. The correlation between wind patterns governing Bering Strait variability and Siberian Coastal Current variability is driven by coastal sea level adjustments to changing winds, in turn driving the Strait transport. Due to the Chukotka coastline configuration, both zonal and meridional wind components contribute. Full article
(This article belongs to the Special Issue Application of Remote Sensing in Coastline Monitoring)
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17 pages, 4134 KiB  
Article
Direct and Remote Sensing Monitoring of Plant Salinity Stress in a Coastal Back-Barrier Environment: Mediterranean Pine Forest Stress and Mortality as a Case Study
by Luigi Alessandrino, Elisabetta Giuditta, Salvatore Faugno, Nicolò Colombani and Micòl Mastrocicco
Remote Sens. 2024, 16(17), 3150; https://doi.org/10.3390/rs16173150 - 26 Aug 2024
Viewed by 960
Abstract
The increase in atmospheric and soil temperatures in recent decades has led to unfavorable conditions for plants in many Mediterranean coastal environments. A typical example can be found along the coast of the Campania region in Italy, within the “Volturno Licola Falciano Natural [...] Read more.
The increase in atmospheric and soil temperatures in recent decades has led to unfavorable conditions for plants in many Mediterranean coastal environments. A typical example can be found along the coast of the Campania region in Italy, within the “Volturno Licola Falciano Natural Reserve”, where a pine forest suffered a dramatic loss of trees in 2021. New pines were planted in 2023 to replace the dead ones, with a larger tree layout and interspersed with Mediterranean bushes to replace the dead pine forest. A direct (in situ) monitoring program was planned to analyze the determinants of the pine salinity stress, coupled with Sentinel-2 L2A data; in particular, multispectral indices NDVI and NDMI were provided by the EU Copernicus service for plant status and water stress level information. Both the vadose zone and shallow groundwater were monitored with continuous logging probes. Vadose zone monitoring indicated that salinity peaked at a 30 cm soil depth, with values up to 1.9 g/L. These harsh conditions, combined with air temperatures reaching peaks of more than 40 °C, created severe difficulties for pine growth. The results of the shallow groundwater monitoring showed that the groundwater salinity was low (0.35–0.4 g/L) near the shoreline since the dune environment allowed rapid rainwater infiltration, preventing seawater intrusion. Meanwhile, salinity increased inland, reaching a peak at the end of the summer, with values up to 2.8 g/L. In November 2023, salts from storm-borne aerosols (“sea spray”) deposited on the soil caused the sea-facing portion of the newly planted pines to dry out. Differently, the pioneer vegetation of the Mediterranean dunes, directly facing the sea, was not affected by the massive deposition of sea spray. The NDMI and NDVI data were useful in distinguishing the old pine trees suffering from increasing stress and final death but were not accurate in detecting the stress conditions of newly planted, still rather short pine trees because their spectral reflectance largely interfered with the adjacent shrub growth. The proposed coupling of direct and remote sensing monitoring was successful and could be applied to detect the main drivers of plant stress in many other Mediterranean coastal environments. Full article
(This article belongs to the Special Issue Application of Remote Sensing in Coastline Monitoring)
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