Intelligent Remote Sensing for Wetland Mapping and Monitoring

Dear Colleagues,

Wetlands are among the world’s most valuable and dynamic ecosystems, playing crucial roles in biodiversity conservation, water regulation, and climate mitigation. However, the rapid loss and transformation of wetlands due to climate change and human activities have heightened the need for timely and accurate monitoring. Remote sensing offers a unique opportunity to observe wetlands across extensive spatial and temporal scales. In recent years, the advent of artificial intelligence (AI), deep learning, and advanced computational methods has opened new possibilities for extracting detailed and reliable wetland information from increasingly diverse and complex remote sensing data.

This Special Issue aims to showcase cutting-edge advances in intelligent remote sensing techniques for wetland mapping and monitoring. By promoting the integration of AI-driven methods and advanced time-series analyses, this Special Issue aligns with the journal’s focus on remote sensing science, technology, and applications. We seek contributions that advance both the development of novel methodologies and the implementation of practical solutions, fostering interdisciplinary collaboration among researchers in remote sensing, ecology, computer vision, and environmental science.

We invite original research articles, technical notes, and review papers covering a broad range of topics including, but not limited to, the following:

1. Deep learning and machine learning approaches for wetland classification and change detection;
2. Time-series analysis and spatiotemporal modeling for wetland dynamics;
3. SAR, LiDAR, and novel remote sensing for wetland mapping and monitoring;
4. Data fusion and integration of multi-source remote sensing for wetlands;
5. AI-enabled techniques for high-resolution and large-scale wetland mapping;
6. Remote sensing of wetland functional traits and ecosystem services;
7. Monitoring of wetland hydrological, biogeochemical, and vegetation parameters;
8. Automatic delineation and inventory of wetlands through intelligent algorithms;
9. Assessment of wetland degradation, restoration, and connectivity with remote sensing.

Submissions introducing novel frameworks, demonstrating practical applications, or providing comprehensive reviews are especially encouraged.

Dr. Ming Wang
Dr. Weidong Man
Dr. Xiao Huang
Dr. Mingyue Liu
Dr. Huiying Li
Dr. Hengxing Xiang
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.