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Ecological Environment Remote Sensing and Sustainable Development Evaluation in Coastal Zones

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

Deadline for manuscript submissions: 29 June 2025 | Viewed by 1393

Special Issue Editors

Prof. Dr. Xiyong Hou

E-Mail Website
Guest Editor
Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, China
Interests: remote sensing of resources and environments in coastal zones; coastal risk assessment; integrated coastal zone management (ICZM)
Special Issues, Collections and Topics in MDPI journals
Dr. Chao Chen

E-Mail Website
Guest Editor
School of Geography Science and Geomatics Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Interests: remote sensing; coastal environments
Special Issues, Collections and Topics in MDPI journals
Dr. Peng Li

E-Mail Website
Guest Editor
Institute of Estuarine and Coastal Zone, College of Marine Geosciences, Ocean University of China, Qingdao 266005, China
Interests: radar remote sensing; machine learning and change detection; coastal wetlands mapping; GNSS; UAV LiDAR; SAR; multispectral and hyperspectral remote sensing
Special Issues, Collections and Topics in MDPI journals
Dr. Qi Wang

E-Mail
Guest Editor
Institute of Estuarine and Coastal Zone Research, Shandong Jianzhu University, Jinan 250101, China
Interests: nighttime light remote sensing; ecological security pattern; remote sensing data mining; remote sensing of offshore hydrocarbon platforms; ecological remote sensing and modeling; ecological quality assessment

Special Issue Information

Dear Colleagues,

Coastal zones, as a distinct interface between land and ocean, represent not only one of the most productive ecosystems on Earth, but also a region of concentrated human habitation and economic activity. However, factors such as global climate change, population growth, urbanization, and resource exploitation have placed unprecedented pressure on these areas. These stressors have given rise to a multitude of eco-environmental issues, including coastal erosion, water quality degradation, land subsidence, biodiversity loss, declining ecological health, landscape fragmentation, etc. Collectively, these challenges pose severe threats to the sustainability and resilience of coastal zone ecosystems.

Recent advances in remote sensing technology have provided powerful techniques for monitoring and evaluating the ecological environment of coastal zones. High-resolution, multimodal satellite imagery; unmanned aerial vehicles (UAVs); and ground-based sensors now allow for more precise identification and tracking of dynamic changes within these ecosystems while also providing decision-makers with timely and actionable information. Additionally, the integration of landscape ecology theory and environmental modeling theory with Geographic Information System (GIS) technologies offers a robust framework for understanding the eco-environmental processes driving these changes, as well as their implications for sustainable development. Nevertheless, significant challenges and unresolved concerns persist in this fields.

This Special Issue seeks to compile the latest research findings on remote sensing monitoring of coastal zone ecological environments, as well as on theoretical methods and technologies from multidisciplinary perspectives such as GIS and landscape ecology in the assessment and management of coastal zones. It seeks to explore how these resources can be utilized to enhance our understanding of the health of coastal ecosystems and to promote the formulation of effective strategies for protecting ecological security and achieving sustainable development.

We invite original research papers and comprehensive review articles addressing the following topics:

  • Intelligent Interpretations and Change Analysis of Typical Land Covers and Targets in Coastal Zones;
  • Monitoring and Assessment of Ecological Environments in Coastal Zones;
  • Simulation and Optimization of Ecological Environment Processes in Coastal Zones;
  • Identification and Optimization of Production–Living–Ecological Spaces in Coastal Zones;
  • Construction and Optimization of Landscape Ecological Security in Coastal Zones;
  • Monitoring and Inversion of Land Subsidence Safety in Coastal Zones;
  • Assessment and Optimization of Sustainable Development in Coastal Zones.

Prof. Dr. Xiyong Hou
Dr. Chao Chen
Dr. Peng Li
Dr. Qi Wang
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 zones
  • intelligent remote sensing interpretation
  • ecological environment remote sensing
  • ecological pro-cesses
  • landscape ecological security
  • land subsidence safety
  • sustainable development

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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

13 pages, 10327 KiB  
Article
Extraction Method for Factory Aquaculture Based on Multiscale Residual Attention Network
by Haiwei Zhang, Jialan Chu, Guize Liu, Yanlong Chen and Kaifei He
Remote Sens. 2025, 17(6), 1093; https://doi.org/10.3390/rs17061093 - 20 Mar 2025
Viewed by 230
Abstract
The rapid development of factory aquaculture not only brings economic benefits to coastal areas but also poses numerous ecological and environmental challenges. Therefore, understanding the distribution of coastal factory aquaculture is of great significance for ecological protection. To tackle the issue of the [...] Read more.
The rapid development of factory aquaculture not only brings economic benefits to coastal areas but also poses numerous ecological and environmental challenges. Therefore, understanding the distribution of coastal factory aquaculture is of great significance for ecological protection. To tackle the issue of the complex spectral and spatial characteristics in remote-sensing images of different factory aquaculture plants in coastal areas, a multiscale residual attention network (MRAN) model for extracting factory aquaculture information is proposed in this study. MRAN is a modification of the U-Net model. By introducing a residual structure, an attention module, and a multiscale connection MRAN can solve the problem of inadequately detailed information extraction from a complex background. In addition, the coastal areas of Huludao City and Dalian City in Liaoning Province were selected as the research areas, and experiments were conducted using the domestic Gaofen-1 remote-sensing image data. The results indicate that the pixel accuracy (PA), mean PA, and mean intersection over union of the proposed model are 98.31%, 97.85%, and 92.46%, respectively, which are superior to those of other comparison models. Moreover, the proposed model can effectively reduce misidentification and missing identification phenomena caused by complex backgrounds and multiple scales. Full article
(This article belongs to the Special Issue Ecological Environment Remote Sensing and Sustainable Development Evaluation in Coastal Zones)
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15 pages, 3870 KiB  
Article
Global Patterns and Changes of River Backwater Points over Two Decades
by Hao Yu, Dongjie Fu, Fenzhen Su, Jiasheng Tang, Ze Yuan, Vincent Lyne, Ye Xiao and Lu Kang
Remote Sens. 2025, 17(5), 886; https://doi.org/10.3390/rs17050886 - 2 Mar 2025
Viewed by 635
Abstract
The study of river backwater points (bpts) is pivotal for understanding the interactions between riverine and coastal systems, including brackish water dynamics, coastal flooding, and ecosystem processes. Despite extensive research, the global spatio-temporal dynamics of bpts, particularly in rivers with [...] Read more.
The study of river backwater points (bpts) is pivotal for understanding the interactions between riverine and coastal systems, including brackish water dynamics, coastal flooding, and ecosystem processes. Despite extensive research, the global spatio-temporal dynamics of bpts, particularly in rivers with minimal human intervention, remains underexplored. This study investigates backwater lengths and shifts in 18 major global rivers (discharge > 5000 m3/s) from 2000 to 2020, uncovering significant hydrological and geographical patterns. In 2000, backwater lengths ranged from 113.16 km (Salween) to 828.75 km (Amur), with bpts consistently positioned upstream of apex points. By 2020, all rivers exhibited upstream retreats of their bpts, ranging from 10.43 km (Salween) to 132.51 km (Amazon), and retreat ratios typically falling between 0% and 20%. The Salween, Niger (60%), and Irrawaddy (38%) demonstrated the most significant proportional shifts. Geographical transitions of bpts varied widely: rivers such as the Ganges and Amur shifted toward urbanized areas, while the Amazon and Orinoco remained in remote regions, reflecting the differential impact of human activity and natural processes. There was a general correlation between backwater length and river discharge, with exceptions like the Amur indicating the influence of other factors such as geomorphic settings and sediment dynamics. While sea-level rise (0.019–0.115 m) affected estuarine conditions, it showed no consistent relationship with bpt retreat at the global scale, but a regional-scale analysis indicates that sea-level rise can lead to the retreat of bpts for those rivers with macro-tidal environments and high sediment yields with less human intervention, suggesting localized interactions dominate backwater dynamics. These findings highlight the complex interplay of environmental and anthropogenic pressures on global river systems. They provide a critical foundation for advancing hydrological modeling, improving river management strategies, and understanding the broader implications of spatio-temporal bpt dynamics under changing climatic and human influences. Full article
(This article belongs to the Special Issue Ecological Environment Remote Sensing and Sustainable Development Evaluation in Coastal Zones)
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