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Remote Sensing
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Coastal and Marine Monitoring and Restoration Mapping Using UAS and...
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Coastal and Marine Monitoring and Restoration Mapping Using UAS and Remote Sensing Systems

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

Deadline for manuscript submissions: 29 August 2025 | Viewed by 1947

Special Issue Editors

Dr. Niall Burnside

E-Mail Website
Guest Editor
Scottish Association for Marine Science, Oban PA37 1QA, UK
Interests: geoinformatics; UAV and remote sensing for marine; landscape and habitat conservation and management
Special Issues, Collections and Topics in MDPI journals
Dr. Jonathan Dale

E-Mail Website
Guest Editor
Environmental Science Research Division, University of Reading, Whiteknights Campus, Reading RG6 6UR, UK
Interests: wetland restoration; coastal and estuarine management; intertidal morphology; unmanned aerial systems
Special Issues, Collections and Topics in MDPI journals
Dr. Matthew Brolly

E-Mail Website
Guest Editor
Centre for Earth Observation Science, University of Brighton, Cockcroft Building, Brighton BN2 4GJ, UK
Interests: SAR; Lidar; multispectral; hyperspectral; remote sensing; vegetation

Special Issue Information

Dear Colleagues,

The development of new remote-sensing-based monitoring methods for marine restoration and management offers a bright future for our blue environment. Access to continually improving satellite-based remote sensing systems, coupled with the ongoing development of, and increased accessibility to, uncrewed aircraft systems (UASs), presents a breadth of new possibilities for environmental assessment and monitoring. Importantly, equipped with a range of sensor types, this potential is now being explored and exploited at scale in the coastal and marine environment.

Coastal and marine monitoring and restoration mapping using UASs and remote sensing systems constitute a rapidly developing field, which can either complement or replace more traditional survey methodologies. The rapid, repeatable, adaptable, and successful monitoring of management initiatives and approaches is now achievable through these technologies and offers significant opportunities to improve our ability to monitor and map coastal and marine restoration at scale.

This Special Issue will bring together a range of papers demonstrating the capacity of satellite-based remote sensing, uncrewed aircraft systems (UASs), and UAS-mounted sensors across a diverse range of coastal and marine monitoring and restoration mapping applications.

Suggested themes and article types for submissions:

  1. Refined techniques for mapping coastal vegetated ecosystems (blue carbon).
  2. Supporting restoration success with UASs.
  3. Improving sensors for the high-resolution analysis of coastal systems and processes.

Dr. Niall Burnside
Dr. Jonathan Dale
Dr. Matthew Brolly
Guest Editors

Dr. Alasdair O’Dell
Guest Editor Assistant
Scottish Association for Marine Science, Oban PA37 1QA, UK
E-Mail: alasdair.odell@sams.ac.uk

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

  • UAVs
  • remote sensing
  • blue carbon
  • coastal vegetated systems
  • saltmarsh
  • seagrass
  • kelp
  • marine mammals
  • birds

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

Published Papers (2 papers)

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Research

19 pages, 3711 KiB  
Article
A Novel Methodology to Correct Chlorophyll-a Concentrations from Satellite Data and Assess Credible Phenological Patterns
by Irene Biliani, Ekaterini Skamnia, Polychronis Economou and Ierotheos Zacharias
Remote Sens. 2025, 17(7), 1156; https://doi.org/10.3390/rs17071156 - 25 Mar 2025
Viewed by 474
Abstract
Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tracking changes [...] Read more.
Remote sensing data play a crucial role in capturing and evaluating eutrophication, providing a comprehensive view of spatial and temporal variations in water quality parameters. Chlorophyll-a concentration time series analysis aids in understanding the current trophic state of coastal waters and tracking changes over time, enabling the evaluation of water bodies’ trophic status. This research presents a novel and replicable methodology able to derive accurate phenological patterns using remote sensing data. The methodology proposed uses the two-decade MODIS-Aqua surface reflectance dataset, analyzing data from 30-point stations and calculating chlorophyll-a concentrations from NASA’s Ocean Color algorithm. Then, a correction process is implemented through a robust, simple statistical analysis by applying LOESS smoothing to detect and remove outliers from the extensive dataset. Different scenarios are reviewed and compared with field data to calibrate the proposed methodology accurately. The results demonstrate the methodology’s capacity to produce consistent chlorophyll-a time series and to present phenological patterns that can effectively identify key indicators and trends, resulting in valuable insights into the coastal body’s trophic state. The case study of the Ambracian Gulf is characterized as hypertrophic since algal bloom during August reaches up to 5 mg/m3, while the replicate case study of Aitoliko shows algal bloom reaching up to 2.5 mg/m3. Finally, the proposed methodology successfully identifies the positive chlorophyll-a climate tendencies of the two selected Greek water bodies. This study highlights the value of integrating statistical methods with remote sensing data for accurate, long-term monitoring of water quality in aquatic ecosystems. Full article
(This article belongs to the Special Issue Coastal and Marine Monitoring and Restoration Mapping Using UAS and Remote Sensing Systems)
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26 pages, 5012 KiB  
Article
A Likelihood-Based Triangulation Method for Uncertainties in Through-Water Depth Mapping
by Mohamed Ali Ghannami, Sylvie Daniel, Guillaume Sicot and Isabelle Quidu
Remote Sens. 2024, 16(21), 4098; https://doi.org/10.3390/rs16214098 - 2 Nov 2024
Viewed by 1068
Abstract
Coastal environments, which are crucial for economic and strategic reasons, heavily rely on accurate bathymetry for safe navigation and resource monitoring. Recent advancements in through-water photogrammetry have shown promise in mapping shallow waters efficiently. However, robust uncertainty modeling methods for these techniques, especially [...] Read more.
Coastal environments, which are crucial for economic and strategic reasons, heavily rely on accurate bathymetry for safe navigation and resource monitoring. Recent advancements in through-water photogrammetry have shown promise in mapping shallow waters efficiently. However, robust uncertainty modeling methods for these techniques, especially in challenging coastal environments, are lacking. This study introduces a novel likelihood-based approach for through-water photogrammetry, focusing on uncertainties associated with camera pose—a key factor affecting depth mapping accuracy. Our methodology incorporates probabilistic modeling and stereo-photogrammetric triangulation to provide realistic estimates of uncertainty in Water Column Depth (WCD) and Water–Air Interface (WAI) height. Using simulated scenarios for both drone and airborne surveys, we demonstrate that viewing geometry and camera pose quality significantly influence resulting uncertainties, often overshadowing the impact of depth itself. Our results reveal the superior performance of the likelihood ratio statistic in scenarios involving high attitude noise, high flight altitude, and complex viewing geometries. Notably, drone-based applications show particular promise, achieving decimeter-level WCD precision and WAI height estimations comparable to high-quality GNSS measurements when using large samples. These findings highlight the potential of drone-based surveys in producing more accurate bathymetric charts for shallow coastal waters. This research contributes to the refinement of uncertainty quantification in bathymetric charting and sets a foundation for future advancements in through-water surveying methodologies. Full article
(This article belongs to the Special Issue Coastal and Marine Monitoring and Restoration Mapping Using UAS and Remote Sensing Systems)
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