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Application of Remote Sensing Technology in Wetland Ecology

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

Deadline for manuscript submissions: 30 June 2025 | Viewed by 1030

Special Issue Editors


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Guest Editor
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
Interests: remote sensing of wetlands; landscape changes; ecological effects
Special Issues, Collections and Topics in MDPI journals
Institute of Forest Resource Information Techniques, Chinese Academy of Forestry, Beijing 100091, China
Interests: wetland classification; wetland landscape dynamics

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Guest Editor
Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
Interests: remote sensing of coastal wetlands and biodiversity
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
School of Environmental and Geographical Sciences, Shanghai Normal University, Shanghai 200234, China
Interests: wetland landscape ecology and sustainability assessments

Special Issue Information

Dear Colleagues,

Wetlands serve as one of the most important types of ecosystems on Earth due to their critical roles in delivering ecosystem functions and services, but they are sensitive to global climate change and human disturbance. Although ecological issues caused by wetland loss and degradation have been widely researched, the monitoring and assessment of wetlands are inadequate to support wetland conservation and sustainable management.

Remote sensing, as a crucial technology, has been widely used in wetland management, and studies on wetland remote sensing have been rapidly developing. In addition to wetland classification and mapping, the application of remote sensing on wetland ecology has been investigated for multiple aspects. With the development of remotely sensed big data and artificial intelligence, we need to gain a deeper understanding of wetland ecosystems. Remote sensing techniques have the distinctive advantages of broad spatial and temporal coverage, which can provide vital information for ecosystem monitoring and assessment. However, due to the size and fragmented distribution, as well as significant intra- and inter-annual variability, identifying and monitoring wetland ecosystems using remote sensing remains a considerable challenge.

Through this Special Issue, we aim to join interdisciplinary researchers to peer-review and communicate the latest studies on “Applications of Remote Sensing Technology in Wetland Ecology”. We welcome articles from the global research community that are actively engaged with this subject.

Potential topics include but are not limited to the following:

  • Wetland mapping using remotely sensed big data and multisource image data;
  • The remote sensing of wetland biodiversity and plant community classification;
  • The wetland ecological parameter inversion method;
  • Wetland soil mapping algorithms and remotely sensed covariates;
  • Landscape pattern and structure change assessments of wetlands;
  • Wetland ecosystem functions and services assessment;
  • Water quality monitoring and assessment;
  • Wetland responses to global change and ecosystem health assessments;
  • Wetland resilience and landscape sustainability assessments.

Prof. Dr. Dehua Mao
Dr. Yang Liu
Dr. Jianing Zhen
Dr. Jingwei Li
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

  • remotely sensed big data
  • wetland landscape patterns or processes
  • wetland functions and services
  • wetland resilience and sustainability
  • wetland biodiversity

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Published Papers (2 papers)

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Research

21 pages, 78307 KiB  
Article
Exploring the Vegetation Changes in Poyang Lake Wetlands: Succession and Key Drivers over Past 30 Years
by Haobei Zhen, Caihong Tang, Shanghong Zhang, Hao Wang, Chuansen Wu, Jiwan Sun and Wen Liu
Remote Sens. 2025, 17(8), 1370; https://doi.org/10.3390/rs17081370 - 11 Apr 2025
Viewed by 256
Abstract
Wetland vegetation is vital for ecological purification and climate mitigation. This study analyzes the spatiotemporal characteristics and influencing factors of water areas, fractional vegetation cover (FVC), and land use types in Poyang Lake wetland across wet and dry seasons (1990–2022) using remote sensing [...] Read more.
Wetland vegetation is vital for ecological purification and climate mitigation. This study analyzes the spatiotemporal characteristics and influencing factors of water areas, fractional vegetation cover (FVC), and land use types in Poyang Lake wetland across wet and dry seasons (1990–2022) using remote sensing technology. The results showed that the water area remained overall stable during the wet seasons but decreased significantly in the dry seasons (19.27 km2/a). FVC exhibited an overall increasing trend, with vegetation expanding from lake margins to central areas. The land use areas of shallow water, bare ground, and Phalaris arundinacea–Polygonum hydropiper (P. arundinacea–P. hydropiper) communities showed interannual fluctuating decreases, while other land use types areas increased. From 1990 to 2020, land use changes were mainly characterized by the transformation of shallow water into deep water and bare ground, other vegetation into Carex cinerascens (C. cinerascens) community and bare ground, bare ground into deep water, as well as P. arundinacea–P. hydropiper community to C. cinerascens community. Rising temperatures enhanced FVC in both seasons, stimulated the expansion of C. cinerascens community area and total vegetation area, and reduced the dry season water area. Decreasing accumulated precipitation exacerbated water area loss and the decline of P. arundinacea–P. hydropiper communities. These findings provide critical insights for wetland ecological conservation and sustainable management. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Wetland Ecology)
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34 pages, 32810 KiB  
Article
Projecting Future Wetland Dynamics Under Climate Change and Land Use Pressure: A Machine Learning Approach Using Remote Sensing and Markov Chain Modeling
by Penghao Ji, Rong Su, Guodong Wu, Lei Xue, Zhijie Zhang, Haitao Fang, Runhong Gao, Wanchang Zhang and Donghui Zhang
Remote Sens. 2025, 17(6), 1089; https://doi.org/10.3390/rs17061089 - 20 Mar 2025
Cited by 2 | Viewed by 553
Abstract
Wetlands in the Yellow River Watershed of Inner Mongolia face significant reductions under future climate and land use scenarios, threatening vital ecosystem services and water security. This study employs high-resolution projections from NASA’s Global Daily Downscaled Projections (GDDP) and the Intergovernmental Panel on [...] Read more.
Wetlands in the Yellow River Watershed of Inner Mongolia face significant reductions under future climate and land use scenarios, threatening vital ecosystem services and water security. This study employs high-resolution projections from NASA’s Global Daily Downscaled Projections (GDDP) and the Intergovernmental Panel on Climate Change Sixth Assessment Report (IPCC AR6), combined with a machine learning and Cellular Automata–Markov (CA–Markov) framework to forecast the land cover transitions to 2040. Statistically downscaled temperature and precipitation data for two Shared Socioeconomic Pathways (SSP2-4.5 and SSP5-8.5) are integrated with satellite-based land cover (Landsat, Sentinel-1) from 2007 and 2023, achieving a high classification accuracy (over 85% overall, Kappa > 0.8). A Maximum Entropy (MaxEnt) analysis indicates that rising temperatures, increased precipitation variability, and urban–agricultural expansion will exacerbate hydrological stress, driving substantial wetland contraction. Although certain areas may retain or slightly expand their wetlands, the dominant trend underscores the urgency of spatially targeted conservation. By synthesizing downscaled climate data, multi-temporal land cover transitions, and ecological modeling, this study provides high-resolution insights for adaptive water resource planning and wetland management in ecologically sensitive regions. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Wetland Ecology)
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