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Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science

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

Deadline for manuscript submissions: closed (15 April 2024) | Viewed by 13051

Special Issue Editors

Dr. Terushisa Komatsu

E-Mail Website
Guest Editor
Japan Fisheries Resource Conservation Association, Towa-Akashi Building 5F, 1-1 Akashi, Chuo, Tokyo 104-0044, Japan
Interests: remote sensing; acoustics; satellite image; seaweed; seagrass; echosounder; multibeam sonar; data logger; biotelemetry
Special Issues, Collections and Topics in MDPI journals
Dr. Tatsuyuki Sagawa

E-Mail Website
Guest Editor
Remote Sensing Technology Center of Japan, Tokyo 105-0001, Japan
Interests: bathymetry; ecosystem; shallow water; remote sensing; mapping

Special Issue Information

Dear Colleagues,

Remote sensing is an important tool for filling in critical information gaps for mapping and monitoring coastal habitats that provide indispensable ecosystem services, including blue carbon production; however, significant barriers exist for operational use within ecological and conservation communities. The recent advance of remote sensing technology and free access to high-resolution RS imageries open up new opportunities for applying remote sensing to coastal habitat mapping and monitoring, not only for research, but more importantly for conservation and management. This Special Issue aims to share cutting-edge techniques with respect to coastal habitat mapping and its applications and, thus, aims to generate solutions for coastal habitat conservation for the sustainable development of coastal area by identifying direct and indirect human impacts on coastal waters and developing ICAM/MSP, eventually contributing to the Decade of Ocean Science started in 2021.

This Special Issue aims to share not only novel, improved methods/approaches and/or algorithms of remote sensing to map coastal habitats but also case studies on the conservation of coastal habitats by applying remote sensing to realize the sustainable development of coastal areas. Due to the fact that remote sensing can play an important role in this regard, it is sharing applications of remote sensing for coastal habitat conservation is indispensable. The scope of this Special Issue includes multispectral and hyperspectral remote sensing, active and passive microwave remote sensing, lidar and laser scanning, change detection, image processing and pattern recognition, operational use of remote sensing, and remote sensing applications concerning coastal habitat mapping and conservation

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: remote sensing of coastal habitats such as seagrass, seaweed and coral reefs; mangroves with human impacts such as aquaculture facilities; land use land cover change, etc.; analysis of temporal changes in coastal habitats, and applications of remote sensing to coastal habitat conservation.

Dr. Terushisa Komatsu
Dr. Tatsuyuki Sagawa
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 habitat mapping
  • conservation
  • blue carbon
  • LULC change
  • ecosystem service
  • human impacts
  • integrated coastal area management
  • marine spatial planning

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Published Papers (6 papers)

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Research

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20 pages, 22937 KiB  
Article
A Combination of Remote Sensing Datasets for Coastal Marine Habitat Mapping Using Random Forest Algorithm in Pistolet Bay, Canada
by Sahel Mahdavi, Meisam Amani, Saeid Parsian, Candace MacDonald, Michael Teasdale, Justin So, Fan Zhang and Mardi Gullage
Remote Sens. 2024, 16(14), 2654; https://doi.org/10.3390/rs16142654 - 20 Jul 2024
Viewed by 961
Abstract
Marine ecosystems serve as vital indicators of biodiversity, providing habitats for diverse flora and fauna. Canada’s extensive coastal regions encompass a rich range of marine habitats, necessitating accurate mapping techniques utilizing advanced technologies, such as remote sensing (RS). This study focused on a [...] Read more.
Marine ecosystems serve as vital indicators of biodiversity, providing habitats for diverse flora and fauna. Canada’s extensive coastal regions encompass a rich range of marine habitats, necessitating accurate mapping techniques utilizing advanced technologies, such as remote sensing (RS). This study focused on a study area in Pistolet Bay in Newfoundland and Labrador (NL), Canada, with an area of approximately 170 km2 and depths varying between 0 and −28 m. Considering the relatively large coverage and shallow depths of water of the study area, it was decided to use airborne bathymetric Light Detection and Ranging (LiDAR) data, which used green laser pulses, to map the marine habitats in this region. Along with this LiDAR data, Remotely Operated Vehicle (ROV) footage, high-resolution multispectral drone imagery, true color Google Earth (GE) imagery, and shoreline survey data were also collected. These datasets were preprocessed and categorized into five classes of Eelgrass, Rockweed, Kelp, Other vegetation, and Non-Vegetation. A marine habitat map of the study area was generated using the features extracted from LiDAR data, such as intensity, depth, slope, and canopy height, using an object-based Random Forest (RF) algorithm. Despite multiple challenges, the resulting habitat map exhibited a commendable classification accuracy of 89%. This underscores the efficacy of the developed Artificial Intelligence (AI) model for future marine habitat mapping endeavors across the country. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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17 pages, 6204 KiB  
Article
TENet: A Texture-Enhanced Network for Intertidal Sediment and Habitat Classification in Multiband PolSAR Images
by Di Zhang, Wensheng Wang, Martin Gade and Huihui Zhou
Remote Sens. 2024, 16(6), 972; https://doi.org/10.3390/rs16060972 - 10 Mar 2024
Cited by 1 | Viewed by 883
Abstract
This paper proposes a texture-enhanced network (TENet) for intertidal sediment and habitat classification using multiband multipolarization synthetic aperture radar (SAR) images. The architecture introduces the texture enhancement module (TEM) into the UNet framework to explicitly learn global texture information from SAR images. The [...] Read more.
This paper proposes a texture-enhanced network (TENet) for intertidal sediment and habitat classification using multiband multipolarization synthetic aperture radar (SAR) images. The architecture introduces the texture enhancement module (TEM) into the UNet framework to explicitly learn global texture information from SAR images. The study sites are chosen from the northern part of the intertidal zones in the German Wadden Sea. Results show that the presented TENet model is able to detail the intertidal surface types, including land, seagrass, bivalves, bright sands/beach, water, sediments, and thin coverage of vegetation or bivalves. To further assess its performance, we quantitatively compared our results from the TENet model with different instance segmentation models for the same areas of interest. The TENet model gives finer classification accuracies and shows great potential in providing more precise locations. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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19 pages, 6658 KiB  
Article
A Novel Approach for Instantaneous Waterline Extraction for Tidal Flats
by Hua Yang, Ming Chen, Xiaotao Xi and Yingxi Wang
Remote Sens. 2024, 16(2), 413; https://doi.org/10.3390/rs16020413 - 20 Jan 2024
Cited by 2 | Viewed by 1731
Abstract
For many remote sensing applications, the instantaneous waterline on the image is critical boundary information to separate land and water and for other purposes. Accurate waterline extraction from satellite images is a desirable feature in such applications. Due to the complex topography of [...] Read more.
For many remote sensing applications, the instantaneous waterline on the image is critical boundary information to separate land and water and for other purposes. Accurate waterline extraction from satellite images is a desirable feature in such applications. Due to the complex topography of low tidal flats and their indistinct spatial and spectral characteristics on satellite imagery, the waterline extraction for tidal flats (especially at low tides) from remote sensing images has always been a technically challenging problem. We developed a novel method to extract waterline from satellite images, assuming that the waterline’s elevation is level. This paper explores the utilization of bathymetry during waterline extraction and presents a novel approach to tackle the waterline extraction issue, especially for low tidal flats, using remote sensing images at mid/high tide, when most of the tidal flat area is filled with seawater. Repeated optical satellite images are easily accessible in the current days; the proposed approach first generates the bathymetry map using the mid/high-tide satellite image, and then the initial waterline is extracted using traditional methods from the low-tide satellite image; the isobath (depth contour lines of bathymetry), which corresponds to the initial waterline is robustly estimated, and finally an area-based optimization algorithm is proposed and applied to both isobath and initial waterline to obtain the final optimized waterline. A series of experiments using Sentinel-2 multispectral images are conducted on Jibei Island of Penghu Archipelago and Chongming Island to demonstrate this proposed strategy. The results from the proposed approach are compared with the Normalized Difference Water Index (NDWI) and Support Vector Machine (SVM) methods. The results indicate that more accurate waterlines can be extracted using the proposed approach, and it is very suitable for waterline extraction for tidal flats, especially at low tides. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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18 pages, 18394 KiB  
Article
Predictive Mapping of Mediterranean Seagrasses-Exploring the Influence of Seafloor Light and Wave Energy on Their Fine-Scale Spatial Variability
by Elias Fakiris, Vasileios Giannakopoulos, Georgios Leftheriotis, Athanassios Dimas and George Papatheodorou
Remote Sens. 2023, 15(11), 2943; https://doi.org/10.3390/rs15112943 - 5 Jun 2023
Cited by 1 | Viewed by 2837
Abstract
Seagrasses are flowering plants, adapted to marine environments, that are highly diverse in the Mediterranean Sea and provide a variety of ecosystem services. It is commonly recognized that light availability sets the lower limit of seagrass bathymetric distribution, while the upper limit depends [...] Read more.
Seagrasses are flowering plants, adapted to marine environments, that are highly diverse in the Mediterranean Sea and provide a variety of ecosystem services. It is commonly recognized that light availability sets the lower limit of seagrass bathymetric distribution, while the upper limit depends on the level of bottom disturbance by currents and waves. In this work, detailed distribution of seagrass, obtained through geoacoustic habitat mapping and optical ground truthing, is correlated to wave energy and light on the seafloor of the Marine Protected Area of Laganas Bay, Zakynthos Island, Greece, where the seagrasses Posidonia oceanica and Cymodocea nodosa form extensive meadows. Mean wave energy on the seafloor was estimated through wave propagation modeling, while the photosynthetically active radiation through open-access satellite-derived light parameters, reduced to the seafloor using the detailed acquired bathymetry. A significant correlation of seagrass distribution with wave energy and light was made clear, allowing for performing fine-scale predictive seagrass mapping using a random forest classifier. The predicted distributions exhibited >80% overall accuracy for P. oceanica and >90% for C. nodosa, indicating that fine-scale seagrass predictive mapping in the Mediterranean can be performed robustly through bottom wave energy and light, especially when detailed bathymetric data exist to allow for accurate estimations. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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15 pages, 4735 KiB  
Article
Land-Use Change, Habitat Connectivity, and Conservation Gaps: A Case Study of Shorebird Species in the Yellow River Delta of China Using the InVEST Model and Network Analysis
by Houlang Duan and Xiubo Yu
Remote Sens. 2022, 14(24), 6191; https://doi.org/10.3390/rs14246191 - 7 Dec 2022
Cited by 3 | Viewed by 1993
Abstract
Coastal wetlands form a transition zone between terrestrial and marine environments and provide important ecosystem services. Land-use change in the coastal zone has a substantial effect on habitat connectivity and biodiversity. However, few studies have characterized the effects of land-use change on coastal [...] Read more.
Coastal wetlands form a transition zone between terrestrial and marine environments and provide important ecosystem services. Land-use change in the coastal zone has a substantial effect on habitat connectivity and biodiversity. However, few studies have characterized the effects of land-use change on coastal habitat connectivity. We conducted remote sensing analysis, modeling with the Integrated Valuation of Ecosystem Services and Trade-offs model, geospatial analysis, and habitat connectivity analysis to evaluate historical spatiotemporal changes in the habitat quality and habitat connectivity of migratory shorebirds in the Yellow River Delta, which is an important stopover site along the East Asian–Australasian Flyway migratory route. Several high- and medium-quality areas have been converted to industrial mining and mariculture sites because of land reclamation. The probability of connectivity decreased by −66.7% between 1975 and 2020. Approximately 71.0%, 11.6%, and 5.8% of patches with high importance have been converted to non-habitat patches, habitat patches with medium importance, and habitat patches with low importance, respectively; approximately 58.9% and 11.7% of the patches with medium importance have been converted to non-habitat patches and habitat patches with low importance, respectively. The total priority conservation area was 389.4 km2, and 125.0 km2 (32.1%) of this area remains unprotected; these unprotected areas are mainly distributed in the northwestern and eastern parts of the Yellow River Delta. We recommend that the boundary of the Yellow River Delta National Nature Reserve be expanded to incorporate these unprotected areas. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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15 pages, 2808 KiB  
Technical Note
Baseline Assessment of Ecological Quality Index (EQI) of the Marine Coastal Habitats of Tonga Archipelago: Application for Management of Remote Regions in the Pacific
by Andrea Peirano, Mattia Barsanti, Ivana Delbono, Elena Candigliota, Silvia Cocito, Ta’hirih Hokafonu, Francesco Immordino, Lorenzo Moretti and Atelaite Lupe Matoto
Remote Sens. 2023, 15(4), 909; https://doi.org/10.3390/rs15040909 - 7 Feb 2023
Viewed by 3194
Abstract
The loss of coral habitats and associated biodiversity have direct effects both on the physical dynamics of the coast and on natural resources, threatening the survival of local populations. Conservative actions, such as the creation of new Marine Protected Areas, are urgent measures [...] Read more.
The loss of coral habitats and associated biodiversity have direct effects both on the physical dynamics of the coast and on natural resources, threatening the survival of local populations. Conservative actions, such as the creation of new Marine Protected Areas, are urgent measures needed to face climate change. Managers need fast and simple methods to evaluate marine habitats for planning conservation areas. Here, we present the application of an Ecological Quality Index (EQI), developed for regional-scale habitat maps of the Atlas of the Marine Coastal Habitats of the Kingdom of Tonga, by processing Copernicus Sentinel-2 imagery. Both the habitat mapping classification and the EQI application were focused on the importance of coral reef, seagrass and mangrove habitats, both as natural defense and sustenance for the local populations. Twelve main Pacific reef habitats were evaluated through a three-level EQI score assigned to six parameters: nursery ground, connectivity, species reservoir, fish attraction, biodiversity and primary production. The EQI was integrated into a developed georeferenced database associated to the QGIS software providing the ability to identify on the maps the area of interest and the associated habitats, and to quantify their ecological relevance. The EQI is proposed as a tool that can offer to stakeholders and environmental managers a simple and direct indicator of the value of the marine coastal environment. The index may be handled for management purposes of vast areas with remote and uninhabited islands. Full article
(This article belongs to the Special Issue Remote Sensing for Coastal Habitat Mapping and Decade of Ocean Science)
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