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Special Issue "Global Monitoring of Inland Water Using Remote Sensing and Artificial Intelligence"

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

Deadline for manuscript submissions: 29 March 2024 | Viewed by 366

Special Issue Editors

School of Earth Sciences and Engineering, Hohai University, Nanjing 210098, China
Interests: remote sensing for coastal and hydrology applications
Special Issues, Collections and Topics in MDPI journals
College of Computer and Information, Hohai University, Nanjing 210098, China
Interests: remote sensing image processing; pansharpening; multimodal data fusion
Special Issues, Collections and Topics in MDPI journals
Dr. Junfeng Xiong
E-Mail Website
Guest Editor
Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
Interests: remote sensing of inland waters; applications of machine learning for satellite monitoring
School of Geodesy and Geomatics, Wuhan University, Wuhan 430079, China
Interests: computer communications (networks); programming languages; databases; remote sensing
Ludwig-Franzius-Institute for Hydraulic, Estuarine and Coastal Engineering, Leibniz University Hannover, D-30167 Hannover, Germany
Interests: remote sensing; photogrammetry; registeration; classification; radiometric; normalization; radiometric correction; color consistency; random forest; iran; tehran; Sentinel 1; Sentinel 2; Landsat 8; Landsat 9; Landsat; IRS; UAV; wetland; change detection
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Inland water bodies around the world, such as lakes, reservoirs, rivers, canals, and ponds, play a crucial role in sustaining life, providing human well-being, supporting ecosystems, and ensuring water security for millions of people worldwide. However, in recent years, these valuable resources are under increasing pressure under the background of climate change, population growth, urbanization, and industrial activities. The ability to comprehensively monitor and assess the status and dynamics of inland water bodies (lakes, rivers, and reservoirs) from a local to global scale using remote sensing has become a critical challenge for hydrological, ecological, and environmental researchers, managers, and policy makers.

Remote sensing and artificial intelligence (AI) have emerged as powerful tools in addressing these above mentioned challenges. Remote sensing technologies, encompassing optical, thermal, radar, and lidar sensors aboard satellites and other platforms, offer the capability to acquire frequent, synoptic, and multidimensional data across large geographic areas over a long period with a given revisit frequency. When coupled with widely used AI techniques, such as machine learning and deep learning, these remote sensing datasets can be efficiently processed and analyzed to extract and invert valuable information (such as water area, water level, water storage, water quality, and wetland area) from inland water bodies across the globe. In addition, the obtained water-related information can further support water resource monitoring, assessment, management, and policy making.

  • Global-scale inland water body mapping and monitoring by remote sensing;
  • Artificial intelligence and machine learning approaches for water body detection and classification;
  • Estimation of water quality parameters from remote sensing data;
  • Remote sensing and AI in monitoring wetland ecosystems;
  • Monitoring changes in lake and river hydrology;
  • Synergistic use of multisource remote sensing data for water resource assessment;
  • Fusion of multisource remote sensing data for inland water studies;
  • Integration of remote sensing and GIS in water resource management.

Dr. Nan Xu
Dr. Xin Li
Dr. Junfeng Xiong
Dr. Linyang Li
Dr. Armin Moghimi
Dr. Arfan Arshad
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at 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.


  • remote sensing
  • inland water
  • artificial intelligence
  • water resource
  • hydrology
  • machine learning
  • global change and regional response

Published Papers

This special issue is now open for submission.
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