Special Issue "Remote Sensing Applications in Coastal Environment"

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

Deadline for manuscript submissions: 31 December 2020.

Special Issue Editors

Dr. Paweł Terefenko
Website
Guest Editor
Institute of Marine and Environmental Sciences, University of Szczecin, 70-500 Szczecin, Poland
Interests: terrestrial laser scanner; remote sensing modeling of coastal environment; shoreline erosion; coastal geomorphology; coastal hazards; flood risk
Dr. Jacek Lubczonek
Website
Guest Editor
Institute of Geoinformatics, Maritime University of Szczecin, 70-500 Szczecin, Poland
Interests: image processing; shoreline extraction; spatial analyses; digital terrain modeling; sea bottom modeling; big data set reduction; neural networks
Dr. Dominik Paprotny
Website
Guest Editor
Helmholtz Centre Potsdam, GFZ German Research Centre for Geosciences, Telegrafenberg, 14473 Potsdam, Germany
Interests: coastal floods; sea level rise; coastal land use; flood risk; flood vulnerability; statistical methods; hydrodynamic modeling

Special Issue Information

Dear Colleagues,

Coastal regions are susceptible to rapid changes as they constitute the boundary between the land and sea. The resilience of a particular segment of coast depends on many factors including climate change, sea-level changes, natural and technological hazards, extraction of natural resources, population growth, and tourism. Recent research highlights the strong capabilities for remote sensing applications to monitor, inventory, and analyze the coastal environment.

This Special Issue invites high-quality and innovative scientific papers that advance the science of remote sensing for coastal ecosystems through innovative approaches and novel applications. Articles that explore, evaluate, or implement the use of remote sensing sensors from UAVs through terrestrial scanners to spaceborne equipment within both natural or built coastal environments are welcome.

The following topics are particularly encouraged:

Applied topics

  • Coastal storms and floods
  • Sea-level rise
  • Shoreline erosion
  • Demographic and economic growth
  • Land cover and use changes
  • (Integrated) coastal zone management

Technical and algorithmic advances in

  • coastal modeling
  • RS/GIS applications
  • airborne and terrestrial LiDAR
  • detection of temporal changes

We are looking forward to your submissions.

Dr. Paweł Terefenko
Dr. Jacek Lubczonek
Dr. Dominik Paprotny
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 papers will be 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 2200 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 process
  • Terrestrial, airborne, and spaceborne remote sensing
  • Sea-level rise
  • Shoreline change
  • Coastal geomorphology
  • Coastal land use
  • Risk and vulnerability assessment
  • Climate change
  • Coastal hazards
  • ICZM

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Open AccessArticle
Land Cover Changes and Flows in the Polish Baltic Coastal Zone: A Qualitative and Quantitative Approach
Remote Sens. 2020, 12(13), 2088; https://doi.org/10.3390/rs12132088 - 29 Jun 2020
Abstract
Detecting land cover changes requires timely and accurate information, which can be assured by using remotely sensed data and Geographic Information System(GIS). This paper examines spatiotemporal trends in land cover changes in the Polish Baltic coastal zone, especially the urbanisation, loss of agricultural [...] Read more.
Detecting land cover changes requires timely and accurate information, which can be assured by using remotely sensed data and Geographic Information System(GIS). This paper examines spatiotemporal trends in land cover changes in the Polish Baltic coastal zone, especially the urbanisation, loss of agricultural land, afforestation, and deforestation. The dynamics of land cover change and its impact were discussed as the major findings. The analysis revealed that land cover changes on the Polish Baltic coast have been consistent throughout the 1990–2018 period, and in the consecutive inventories of land cover, they have changed faster. As shown in the research, the area of agricultural land was subject to significant change, i.e., about 40% of the initial 8% of the land area in heterogeneous agriculture was either developed or abandoned at about equal rates. Next, the steady growth of the forest and semi-natural area also changed the land cover. The enlargement of the artificial surface was the third observed trend of land cover changes. However, the pace of land cover changes on the Baltic coast is slightly slower than in the rest of Poland and the European average. The region is very diverse both in terms of land cover, types of land transformation, and the pace of change. Hence, the Polish national authorities classified the Baltic coast as an area of strategic intervention requiring additional action to achieve territorial cohesion and the goals of sustainable development. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Graphical abstract

Open AccessArticle
Measuring Surface Moisture on a Sandy Beach based on Corrected Intensity Data of a Mobile Terrestrial LiDAR
Remote Sens. 2020, 12(2), 209; https://doi.org/10.3390/rs12020209 - 08 Jan 2020
Abstract
Surface moisture plays a key role in limiting the aeolian transport on sandy beaches. However, the existing measurement techniques cannot adequately characterize the spatial and temporal distribution of the beach surface moisture. In this study, a mobile terrestrial LiDAR (MTL) is demonstrated as [...] Read more.
Surface moisture plays a key role in limiting the aeolian transport on sandy beaches. However, the existing measurement techniques cannot adequately characterize the spatial and temporal distribution of the beach surface moisture. In this study, a mobile terrestrial LiDAR (MTL) is demonstrated as a promising method to detect the beach surface moisture using a phase-based Z&F/Leica HDS6100 laser scanner mounted on an all-terrain vehicle. Firstly, two sets of indoor calibration experiments were conducted so as to comprehensively investigate the effect of distance, incidence angle and sand moisture contents on the backscattered intensity by means of sand samples with an average grain diameter of 0.12 mm. A moisture estimation model was developed which eliminated the effects of the incidence angle and distance (it only relates to the target surface reflectance). The experimental results reveal both the distance and incidence angle influencing the backscattered intensity of the sand samples. The standard error of the moisture model amounts to 2.0% moisture, which is considerably lower than the results of the photographic method. Moreover, a field measurement was conducted using the MTL system on a sandy beach in Belgium. The accuracy and robustness of the beach surface moisture derived from the MTL data was evaluated. The results show that the MTL is a highly suitable technique to accurately and robustly measure the surface moisture variations on a sandy beach with an ultra-high spatial resolution (centimeter-level) in a short time span (12 × 200 m per minute). Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Graphical abstract

Open AccessArticle
Combining Satellite Imagery and Numerical Modelling to Study the Occurrence of Warm Upwellings in the Southern Baltic Sea in Winter
Remote Sens. 2019, 11(24), 2982; https://doi.org/10.3390/rs11242982 - 12 Dec 2019
Abstract
Coastal upwelling involves an upward movement of deeper, usually colder, water to the surface. Satellite sea surface temperature (SST) observations and simulations with a hydrodynamic model show, however, that the coastal upwelling in the Baltic Sea in winter can bring warmer water to [...] Read more.
Coastal upwelling involves an upward movement of deeper, usually colder, water to the surface. Satellite sea surface temperature (SST) observations and simulations with a hydrodynamic model show, however, that the coastal upwelling in the Baltic Sea in winter can bring warmer water to the surface. In this study, the satellite SST data collected by the advanced very high resolution radiometer (AVHRR) and the moderate-resolution imaging spectroradiometer (MODIS), as well as simulations with the Parallel Model 3D (PM3D) were used to identify upwelling events in the southern Baltic Sea during the 2010–2017 winter seasons. The PM3D is a three-dimensional hydrodynamic model of the Baltic Sea developed at the Institute of Oceanography, University of Gdańsk, Poland, in which parallel calculations enable high-resolution modelling. A validation of the model results with in situ observations and satellite-derived SST data showed the PM3D to adequately represent thermal conditions in upwelling areas in winter (91.5% agreement). Analysis of the frequency of warm upwellings in 12 areas of the southern Baltic Sea showed a high variability in January and February. In those months, the upwelling was most frequent, both in satellite imagery and in model results, off the Hel Peninsula (38% and 43% frequency, respectively). Upwelling was also frequent off the Vistula Spit, west of the Island of Rügen, and off the eastern coast of Skåne, where the upwelling frequency estimated from satellite images exceeded 26%. As determined by the PM3D, the upwelling frequency off VS and R was at least 25%, while off the eastern coast of Skåne, it reached 17%. The faithful simulation of SST variability in the winters of 2010–2017 by the high-resolution model used was shown to be a reliable tool with which to identify warm upwellings in the southern Baltic Sea. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Graphical abstract

Open AccessArticle
Multi-Temporal Cliff Erosion Analysis Using Airborne Laser Scanning Surveys
Remote Sens. 2019, 11(22), 2666; https://doi.org/10.3390/rs11222666 - 14 Nov 2019
Abstract
Rock cliffs are a significant component of world coastal zones. However, rocky coasts and factors contributing to their erosion have not received as much attention as soft cliffs. In this study, two rocky-cliff systems in the southern Baltic Sea were analyzed with Airborne [...] Read more.
Rock cliffs are a significant component of world coastal zones. However, rocky coasts and factors contributing to their erosion have not received as much attention as soft cliffs. In this study, two rocky-cliff systems in the southern Baltic Sea were analyzed with Airborne Laser Scanners (ALS) to track changes in cliff morphology. The present contribution aimed to study the volumetric changes in cliff profiles, spatial distribution of erosion, and rate of cliff retreat corresponding to the cliff exposure and rock resistance of the Jasmund National Park chalk cliffs in Rugen, Germany. The study combined multi-temporal Light Detection and Ranging (LiDAR) data analyses, rock sampling, laboratory analyses of chemical and mechanical resistance, and along-shore wave power flux estimation. The spatial distribution of the active erosion areas appear to follow the cliff exposure variations; however, that trend is weaker for the sections of the coastline in which structural changes occurred. The rate of retreat for each cliff–beach profile, including the cliff crest, vertical cliff base, and cliff base with talus material, indicates that wave action is the dominant erosive force in areas in which the cliff was eroded quickly at equal rates along the cliff profile. However, the erosion proceeded with different rates in favor of cliff toe erosion. The effects of chemical and mechanical rock resistance are shown to be less prominent than the wave action owing to very small differences in the measured values, which proves the homogeneous structure of the cliff. The rock resistance did not follow the trends of cliff erosion revealed by volume changes during the period of analysis. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Graphical abstract

Open AccessArticle
Quantifying Spatiotemporal Patterns and Major Explanatory Factors of Urban Expansion in Miami Metropolitan Area During 1992–2016
Remote Sens. 2019, 11(21), 2493; https://doi.org/10.3390/rs11212493 - 25 Oct 2019
Cited by 3
Abstract
Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion [...] Read more.
Urban expansion is one of the most dramatic forms of land transformation in the world and it is one of the greatest challenges in achieving sustainable development in the 21st century. Previous studies analyzed urbanization patterns in areas with rapid urban expansion while urban areas with low to moderate expansion have been overlooked, especially in developed countries. In this study, we examined the spatiotemporal dynamics of urban expansion patterns in South Florida, United States (US) over the last 25 years (1992–2016) using Remote Sensing and GIS techniques. The main goal of this paper was to investigate the degree and spatiotemporal patterns of urban expansion at different administrative level in the study area and how spatiotemporal variance in different explanatory factors influence urban expansion in this region. More specifically, this research quantifies the rates, types, intensity, and landscape metrics of urban expansion in Miami-Fort Lauderdale-Palm Beach, Florida Metropolitan Statistical Area (Miami MSA) which is the 7th largest MSA and 4th largest urbanized area in the US using remote sensing (satellite imageries) data from National Land Cover Datasets (NLCD) and Coastal Change Analysis Program (C-CAP) at 30 m spatial resolution. We further investigated the urban growth patterns at the county and city areas that are located within this MSA to portray the local ‘picture’ of urban growth in this region. Urban expansion in this region can be divided into two time periods: pre-2001 and post-2001 where the former experienced rapid urban expansion and the later had comparatively slow urban expansion. Results suggest that infilling was the dominant type of urban expansion followed by edge-expansion and outlying. Results from landscape metrics represent that newly developed urban lands became more aggregated and simplified in form as the time progressed in the study region. Also, new urban lands were generated away from the east coast and historic cities which eventually created new urban cores. We also used correlation analysis and multiple linear stepwise regression to address major explanatory factors of spatiotemporal change in urban expansion during the study period. Although the influence of factors on urban expansion varied temporally, Population and Distance to Coast were the strongest variables followed by Distance to Roads and Median Income that influence overall urban expansion in the study area. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Graphical abstract

Open AccessArticle
The Reduction Method of Bathymetric Datasets that Preserves True Geodata
Remote Sens. 2019, 11(13), 1610; https://doi.org/10.3390/rs11131610 - 06 Jul 2019
Cited by 1
Abstract
Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and [...] Read more.
Water areas occupy over 70 percent of the Earth’s surface and are constantly subject to research and analysis. Often, hydrographic remote sensors are used for such research, which allow for the collection of information on the shape of the water area bottom and the objects located on it. Information about the quality and reliability of the depth data is important, especially during coastal modelling. In-shore areas are liable to continuous transformations and they must be monitored and analyzed. Presently, bathymetric geodata are usually collected via modern hydrographic systems and comprise very large data point sequences that must then be connected using long and laborious processing sequences including reduction. As existing bathymetric data reduction methods utilize interpolated values, there is a clear requirement to search for new solutions. Considering the accuracy of bathymetric maps, a new method is presented here that allows real geodata to be maintained, specifically position and depth. This study presents a description of a developed method for reducing geodata while maintaining true survey values. Full article
(This article belongs to the Special Issue Remote Sensing Applications in Coastal Environment)
Show Figures

Figure 1

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: Mapping Coastal Dune Vegetation by Remotely Sensed Rao's Q Temporal Diversity
Authors: F. Marzialetti 1, M. Di Febbraro 1, M. Malavasi 2, S. Giulio 3, A.T.R. Acosta 3, M.L. Carranza 1
Affiliation: 1 Envix-Lab, Department of Bioscience and Territory, University of Molise, Contrada Fonte Lappone, 86090 Pesche (Is), Italy
2 Department of Applied Geoinformatics and Spatial Planning, Faculty of Environmental Sciences, Czech University of Life Sciences, Kamycka 129, 165 00 Prague 6, Czech Republic
3 Department of Sciences, University of Roma Tre, Viale G. Marconi 446, 00146 Rome, Italy
Abstract: The increasing human pressure on coastal areas points up the need of monitoring tools that offer updated information to decision makers and planners seeking to improve coastal management. The raising availability of free remotely sensed data at high spatial and temporal resolution allows developing cost-effective ways to evaluate the distribution of ecosystems at present and over time.
As coastal dune landscapes are heterogeneous-dynamic mosaics, which represent a challenge for static habitat mapping, we propose to use the variability of temporal series of Sentinel-2 images as a basis for coastal ecosystems mapping. In particular, we aim at properly describing the annual fluctuations of remotely sensed ecological parameters by applying Rao’s Q diversity index as a basis for classifying and mapping coastal dune vegetation. We analyzed a representative tract of the Adriatic Coast in central Italy (Molise Region). Using Sentinel-2 imagery, we described the monthly behavior of three ecologically relevant parameters on coastal areas: (1) Modified Soil Adjusted Vegetation Index 2 (MSAVI2), (2) Normalized Difference Water Index (NDWI2) and (3) Brightness Index (BI2), as surrogates of phenological fluctuations of vegetation, soil water content seasonality and bare soil amount, respectively. Based on Rao's Q temporal diversity index calculated on yearly stacks of 12 months for each ecological parameter, we implemented an unsupervised classification through three hierarchical runs of Random Forests algorithm (RF). We evaluated the accuracy of the obtained classes by inspecting 300 checkpoints collected in the field and by photo-interpretation of high resolution aerial photos (less than 1 meter). We identified seven vegetation classes, with high performance of RF and high accuracy values. Rao's Q temporal diversity looks effective for mapping coastal dune mosaics, and offers promising perspectives for exploring the utilization of synthetic indices over time with wider areas and different landscapes. Effectiveness of the proposed procedure for mapping coastal dune landscape also suggests the advantages of Sentinel-2 free images and open source RF classification algorithms, even at the fine scale of highly fragmented sand dunes.
Keywords: ecosystem monitoring, random forest classifier, Sentinel-2, Normalized Difference Vegetation Index NDVI, Normalized Difference Water Index NDVWI, Brightness Index BI

Back to TopTop