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Special Issue "UAS Applications for Mapping and Monitoring Coastal Features and Processes"

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

Deadline for manuscript submissions: 31 December 2023 | Viewed by 1053

Special Issue Editors

Laboratoire ISOMer, RSBE² (Remote Sensing, Benthic Ecology and Ecotoxicology), UFR Sciences et Techniques, 2 Rue de la Houssinière BP 81227, CEDEX 3, 44322 Nantes, France
Interests: GIS; image analysis methodologies; geostatistics and geomorphology
Marine Remote Sensing Group (MRSG), Department of Marine Sciences, University of the Aegean, 81100 Lesvos, Greece
Interests: analysis of remote sensing datasets, including satellite and aerial images, for marine and coastal applications; oil spill detection; automatic detection of oceanographic phenomena; object-based image analysis; image processing algorithms and coastal mapping
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Special Issue Information

Dear Colleagues,

Coastal zones provide a home and other resources for a large part of the global population, while at the same time, they receive numerous anthropogenic and natural pressures. Unoccupied aerial systems (UASs) are increasingly gaining ground in coastal studies, covering an enormous number of diverse applications that assist in improving coastal management efforts. UASs offer a completely new aspect in the field of remote sensing, providing fast and low-cost datasets with high spatiotemporal resolution, suitable for imaging and reconstructing coastal features and processes at the landscape scale. UASs are currently used on a wide spectrum of cases, from mapping shallow bathymetry to characterizing intertidal ecosystems and monitoring onshore sediments and vegetation. Additionally, UASs are employed for identifying floating and onshore macroplastic pollution, monitoring coastal erosion and shoreline change, as well as for marine mammal and other macrofauna observations.

Considering that the catalogue of UAS coastal applications is never-ending, this SI is dedicated to highlighting novel UAS coastal applications from a wide range of research areas, indicatively data acquisition technology and sensor integration, development of algorithms for UAS image analysis, shallow bathymetry mapping, documentation of submerged archaeological sites, monitoring of coastal erosion and shoreline change, mapping of coastal and estuarine geomorphology, and monitoring of wildlife. Articles focusing on UASs for coastal zone management and mitigation of coastal pollution are particularly encouraged.


Technology and methods

  • UAS sensor types for coastal observations (RGB, multispectral, hyperspectral)
  • Integration with in situ measurements (e.g., sonar, grain-size, chemical)
  • UAS image analysis techniques and algorithms
  • 3D reconstruction of coastal features (submerged and onshore)
  • Integration with satellite imagery

Broad applications

  • Shallow bathymetry mapping
  • Monitoring shoreline change
  • Coastal erosion
  • Coastal and estuarine geomorphology
  • Mapping coastal ecosystems (onshore, intertidal, and subtidal)
  • Documentation of submerged archaeological sites
  • Wildlife tracking
  • Imaging and monitoring of coastal pollution

Dr. Evangelos Alevizos
Dr. Konstantinos Topouzelis
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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 2500 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.


  • UAS
  • drones
  • multispectral
  • hyperspectral
  • lidar
  • photogrammetry
  • coastal zone mapping
  • coastal modelling
  • coastal ecology
  • marine mammals
  • underwater archaeology
  • shallow bathymetry
  • benthic ecology
  • coastal pollution
  • coastal geomorphology

Published Papers (1 paper)

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Application of a Multispectral UAS to Assess the Cover and Biomass of the Invasive Dune Species Carpobrotus edulis
Remote Sens. 2023, 15(9), 2411; - 04 May 2023
Viewed by 686
Remote sensing can support dune ecosystem conservation. Unoccupied Aircraft Systems (UAS) equipped with multispectral cameras can provide information for identifying different vegetation species, including Carpobrotus edulis—one of the most prominent alien species in Portuguese dune ecosystems. This work investigates the use of [...] Read more.
Remote sensing can support dune ecosystem conservation. Unoccupied Aircraft Systems (UAS) equipped with multispectral cameras can provide information for identifying different vegetation species, including Carpobrotus edulis—one of the most prominent alien species in Portuguese dune ecosystems. This work investigates the use of multispectral UAS for C. edulis identification and biomass estimation. A UAS with a five-band multispectral camera was used to capture images from the sand dunes of the Cávado River spit. Simultaneously, field samples of C. edulis were collected for laboratorial quantification of biomass through Dry Weight (DW). Five supervised classification algorithms were tested to estimate the total area of C. edulis, with the Random Forest algorithm achieving the best results (C. edulis Producer Accuracy (PA) = 0.91, C. edulis User Accuracy (UA) = 0.80, kappa = 0.87, Overall Accuracy (OA) = 0.89). Sixteen vegetation indices (VIs) were assessed to estimate the Above-Ground Biomass (AGB) of C. edulis, using three regression models to correlate the sample areas VI and DW. An exponential regression model of the Renormalized Difference Vegetation Index (RDVI) presented the best fit for C. edulis DW (R2 = 0.86; p-value < 0.05; normalised root mean square error (NRMSE) = 0.09). This result was later used to estimate the total AGB in the area, which can be used for monitoring and management plans—namely, removal campaigns. Full article
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