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Remote Sensing
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Monitoring Wetland Changes and Processes Using Remote Sensing Technologies
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Monitoring Wetland Changes and Processes Using Remote Sensing Technologies

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

Deadline for manuscript submissions: closed (15 September 2023) | Viewed by 11207

Special Issue Editors

Dr. Carina Lurdes Lopes

E-Mail Website
Guest Editor
Centre for Environmental and Marine Studies (CESAM), Physics Department, University of Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal
Interests: numerical modelling; satellite remote sensing; flood hazard; vulnerability and risk assessment; salt marsh dynamics
Special Issues, Collections and Topics in MDPI journals
Dr. Renato Mendes

E-Mail Website
Guest Editor
1. Collaborative Laboratory +Atlantic, 4450-017 Matosinhos, Portugal
2. Underwater Systems and Technology Laboratory (LSTS), Faculty of Engineering of University of Porto (FEUP), 4200-465 Porto, Portugal
Interests: coastal oceanography; river plumes; coastal fronts; satellite remote sensing; ocean color; autonomous underwater vehicles
Dr. Luis Pedro Almeida

E-Mail Website1 Website2
Guest Editor
CoLAB +ATLANTIC/Edifício LACS, Estrada da Malveira da Serra 920, 2750-834 Cascais, Portugal
Interests: remote sensing; coastal processes; coastal risk & hazards
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. João Miguel Dias

E-Mail Website
Guest Editor
Physics Department, CESAM, University of Aveiro, Campus Universitário de Santiago, 3810-193 Aveiro, Portugal
Interests: physical oceanography; estuaries and lagoons; coastal processes; climate change; coastal flooding; tidal processes; numerical modeling
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Coastal wetlands are among the most valuable and productive ecosystems in the world, providing a wide range of goods and services, including habitat and nursery for many animals, protection against storms, carbon storage, and water purification. However, despite their multiple benefits, the extent and condition of wetlands are declining globally, due to growing threats posed by human activities and climate changes.

A variety of remote sensing methods and sensors has provided evidence of being efficient approaches when it comes to detecting wetland condition, changes, and functions in almost inaccessible coastal regions. Moreover, mapping products derived from remote sensed sensors are crucial to assisting wetland management. However, despite the important advances in these, the remote sensing of coastal wetlands still requires improvement to address existent knowledge gaps related to the spectral, spatial, and temporal resolution of remote observations.

This Special Issue will highlight the latest developments in the remote sensing of coastal wetlands. Contributions are encouraged in topics including, but not limited to:

  • Salt marsh and mangrove extent, condition, or functioning;
  • Shoreline change detection;
  • Wetland change detection;
  • Wetland condition changes;
  • Coastal wetland hazards;
  • Coastal squeeze of wetland ecosystems;
  • Blue carbon quantification;
  • Wetland pressure detection.

Dr. Carina Lurdes Lopes
Dr. Renato Mendes
Dr. Luis Pedro Almeida
Prof. Dr. João Miguel Dias
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

  • Earth observation
  • Land cover mapping
  • Wetland processes
  • Salt marsh monitoring
  • Mangrove monitoring
  • Wetland management
  • Coastal squeeze

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Published Papers (4 papers)

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19 pages, 96859 KiB  
Article
Insights for Sea Outfall Turbid Plume Monitoring with High-Spatial-Resolution Satellite Imagery Application in Portugal
by Bruna Faria, Renato Mendes, Carina Lurdes Lopes, Ana Picado, Magda Sousa and João Miguel Dias
Remote Sens. 2023, 15(13), 3368; https://doi.org/10.3390/rs15133368 - 30 Jun 2023
Cited by 4 | Viewed by 1786
Abstract
Coastal municipalities and industries often discharge poorly treated wastewater into proximate marine and estuarine environments. The urban and/or effluent input can lead to eutrophication and lower water quality, as it holds high concentrations of nutrients and pollutants. One widely applied tool to increase [...] Read more.
Coastal municipalities and industries often discharge poorly treated wastewater into proximate marine and estuarine environments. The urban and/or effluent input can lead to eutrophication and lower water quality, as it holds high concentrations of nutrients and pollutants. One widely applied tool to increase effluent dispersion and direct it away from coastal areas, thus causing fewer impacts on human activities, is sea outfall. In Aveiro, Portugal, the São Jacinto sea outfall construction was completed in 1998; however, limited literature regarding the sea outfall’s monitoring using satellite data is available. The methodology in this study involved collecting four years’ worth (2016–2019) of satellite data to investigate visible traces of the interaction between the S. Jacinto sewage water mass and the Ria de Aveiro lagoon ecosystem using ocean color and spectral analysis, and producing new qualitative data regarding sea outfall plume dispersion monitoring through high-resolution Sentinel-2 imagery. The results showed a clear spectral signature of the sewage water mass, and a seasonal pattern was observed in which the plume was more evident in winter and autumn. Additionally, the coastal longshore current and the Aveiro lagoon’s runoff were able to restrict the marine outfall’s dispersion superficially. Ocean color data were revealed to be a factual and cost-effective tool to monitor the plume water. Finally, an exchange between the marine outfall water mass and Ria de Aveiro lagoon could happen in high tide under northern wind conditions. Therefore, it is important to monitor the water quality to ensure the coastal ecosystem’s good environmental state. Full article
(This article belongs to the Special Issue Monitoring Wetland Changes and Processes Using Remote Sensing Technologies)
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23 pages, 20092 KiB  
Article
Spatiotemporal Change Detection of Coastal Wetlands Using Multi-Band SAR Coherence and Synergetic Classification
by Jie Liu, Peng Li, Canran Tu, Houjie Wang, Zhiwei Zhou, Zhixuan Feng, Fang Shen and Zhenhong Li
Remote Sens. 2022, 14(11), 2610; https://doi.org/10.3390/rs14112610 - 29 May 2022
Cited by 14 | Viewed by 3666
Abstract
Synthetic aperture radar (SAR) signal can penetrate clouds and some vegetation canopies in all weather, and therefore, provides an important measurement tool for change detection and sustainable development of coastal wetland environments and ecosystems. However, there are a few quantitative estimations about the [...] Read more.
Synthetic aperture radar (SAR) signal can penetrate clouds and some vegetation canopies in all weather, and therefore, provides an important measurement tool for change detection and sustainable development of coastal wetland environments and ecosystems. However, there are a few quantitative estimations about the spatiotemporal coherence change with multi-band SAR images in complex coastal wetland ecosystems of the Yellow River Delta (YRD). In this study, C-band Sentinel-1 and L-band ALOS-2 PALSAR data were used to detect the spatiotemporal distribution and change pattern of interferometric coherence in the coastal wetlands of the YRD. The results show that the temporal baseline has a greater impact on the interferometric coherence than the perpendicular baseline, especially for short wavelength C-band SAR. Furthermore, the OTSU algorithm was proven to be able to distinguish the changing regions. The coherence mean and standard deviation values of different land cover types varied significantly in different seasons, while the minimum and maximum coherence changes occurred in February and August, respectively. In addition, considering three classical machine learning algorithms, namely naive Bayes (NB), random forest (RF), and multilayer perceptron (MLP), we proposed a method of synergetic classification with SAR coherence, backscatter intensity, and optical images for coastal wetland classification. The multilayer perceptron algorithm performs the best in synergetic classification with an overall accuracy of 98.3%, which is superior to a single data source or the other two algorithms. In this article, we provide an alternative cost-effective method for coastal wetland change detection, which contributes to more accurate dynamic land cover classification and to an understanding of the response mechanism of land features to climate change and human activities. Full article
(This article belongs to the Special Issue Monitoring Wetland Changes and Processes Using Remote Sensing Technologies)
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17 pages, 13486 KiB  
Technical Note
Assessing Shoreline Changes in Fringing Salt Marshes from Satellite Remote Sensing Data
by Inês J. Castro, João M. Dias and Carina L. Lopes
Remote Sens. 2023, 15(18), 4475; https://doi.org/10.3390/rs15184475 - 12 Sep 2023
Cited by 1 | Viewed by 1464
Abstract
Salt marshes are highly important wetlands; however, external pressures are causing their widespread deterioration and loss. Continuous monitoring of their extent is paramount for the preservation and recovery of deteriorated and threatened salt marshes. In general, moderate-resolution satellite remote sensing data allow for [...] Read more.
Salt marshes are highly important wetlands; however, external pressures are causing their widespread deterioration and loss. Continuous monitoring of their extent is paramount for the preservation and recovery of deteriorated and threatened salt marshes. In general, moderate-resolution satellite remote sensing data allow for the accurate detection of salt marsh shorelines; however, their detection in narrow and fringing salt marshes remains challenging. This study aims to evaluate the ability of Landsat-5 (TM), Landsat-7 (ETM+), and Sentinel-2 (MSI) data to be used to accurately determine the shoreline of narrow and fringing salt marshes, focusing on three regions of the Aveiro lagoon in Mira, Ílhavo and S. Jacinto channels. Shorelines were determined considering the Normalized Difference Vegetation Index (NDVI), and the accuracy of this methodology was evaluated against reference shorelines by computing the Root Mean Square Error (RMSE). Once validated, the method was used to determine historical salt marsh shorelines, and rates of change between 1984 and 2022 were quantified and analyzed in the three locations. Results evidence that the 30 m resolution Landsat data accurately describe the salt marsh shoreline (RMSE~15 m) and that the accuracy is maintained when increasing the spatial resolution through pan-sharpening or when using 10 m resolution Sentinel-2 (MSI) data. These also show that the salt marshes of the Ílhavo and S. Jacinto channels evolved similarly, with salt marsh shoreline stability before 2000 followed by retreats after this year. At the end of the four decades of study, an average retreat of 66.23 ± 1.03 m and 46.62 ± 0.83 m was found, respectively. In contrast to these salt marshes and to the expected evolution, the salt marsh of the Mira Channel showed retreats before 2000, followed by similar progressions after this year, resulting in an average 2.33 ± 1.18 m advance until 2022. Full article
(This article belongs to the Special Issue Monitoring Wetland Changes and Processes Using Remote Sensing Technologies)
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11 pages, 12255 KiB  
Technical Note
Suitable LiDAR Platform for Measuring the 3D Structure of Mangrove Forests
by Hideyuki Niwa, Hajime Ise and Mahito Kamada
Remote Sens. 2023, 15(4), 1033; https://doi.org/10.3390/rs15041033 - 14 Feb 2023
Cited by 3 | Viewed by 2562
Abstract
Investigating the three-dimensional structure of mangrove forests is critical for their conservation and restoration. However, mangrove forests are difficult to survey in the field, and their 3D structure is poorly understood. Light detection and ranging (LiDAR) is considered an accurate and dependable method [...] Read more.
Investigating the three-dimensional structure of mangrove forests is critical for their conservation and restoration. However, mangrove forests are difficult to survey in the field, and their 3D structure is poorly understood. Light detection and ranging (LiDAR) is considered an accurate and dependable method of measuring the 3D structure of mangrove forests. This study aimed to find a suitable LiDAR platform for obtaining attributes such as breast height diameter and canopy area, as well as for measuring a digital terrain model (DTM), the base data for hydrological analysis. A mangrove forest near the mouth of the Oura River in Aza-Oura, Nago City, Okinawa Prefecture, Japan, was studied. We used data from terrestrial LiDAR scanning “TLS” and unmanned aerial vehicle (UAV) LiDAR scanning “ULS” as well as data merged from TLS and ULS “Merge”. By interpolating point clouds of the ground surface, DTMs of 5 cm × 5 cm were created. DTMs obtained from ULS could not reproduce the heaps of Thalassina anomala or forest floor microtopography compared with those obtained from TLS. Considering that ULS had a few point clouds in the forest, automatic trunk identification could not be used to segment trees. TLS could segment trees by automatically identifying trunks, but the number of trees identified roughly doubled that of the visual identification results. The number of tree crowns identified using TLS and ULS was approximately one quarter of those identified visually, and many of them were larger in area than the visually traced crowns. The accuracy of tree segmentation using the canopy height model (CHM) was low. The number of canopy trees identified using Merge produced the best results, accounting for 61% of the visual identification results. Results of tree segmentation by CHM suggest that combining TLS and ULS measurements may improve tree canopy identification. Although ULS is a promising new technology, its applications are clearly limited, at least in mangrove forests such as the Oura River, where Bruguiera gymnorhiza is dominant. Depending on the application, using different LiDAR platforms, such as airborne LiDAR scanning, UAV LiDAR scanning, and TLS, is important. Merging 3D point clouds acquired by different platforms, as proposed in this study, is an important option in this case. Full article
(This article belongs to the Special Issue Monitoring Wetland Changes and Processes Using Remote Sensing Technologies)
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