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Application of Multi-Sensor Remote Sensing to Investigate Water Energy Balance Process

A Special Issue of Remote Sensing (ISSN 2072-4292) belonging to the section "Environmental Remote Sensing".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 880

Editors


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Guest Editor
College of Geoscience and Surveying Engineering, China University of Mining and Technology (Beijing), Beijing 100083, China
Interests: remote sensing hydrology; lake changes under climate change; uncertainty analysis of hydrological data

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Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
Interests: remote sensing hydrology; water changes under climate change

Special Issue Information

Dear Colleagues,

Investigating the thermodynamics of water bodies, including both inland and marine systems, is important to understanding their ecological functions and responses to climate change. Water bodies exhibit distinct physical properties compared to their surrounding terrestrial environments, such as reduced albedo, lower surface roughness, and elevated heat capacity. Under a warming climate, global water thermodynamics are exhibiting significant variation that affects internal nutrient and oxygen transport and, in turn, alters aquatic ecosystems. Due to the high cost and difficulty of ground-based observations, our understanding of thermal processes within these waters remains limited. Satellite-based observations have shown considerable potential for providing continuous records of indices related to water energy  over large spatial extents, thereby overcoming the limitations inherent in traditional point-based in situ measurements. Therefore, satellite-based observations are increasingly used to monitor parameters related to water energy balance and to various inputs, parameters, or outputs for driving, calibrating, or validating numerical models.

This Special Issue aims to provide an international forum for sharing innovative theories, methodologies, and applications that could unlock the full potential of multi-source remote sensing data and thus provide a better understanding water energy balance processes.

We welcome original research articles and comprehensive review papers focusing on the applications of remote sensing in lake energy dynamics. Topics of interest include, but are not limited to, the following:

  • Remote sensing retrieval algorithms for parameters related to energy balance on the water surface;
  • Dynamic monitoring and analysis of water energy balance processes;
  • Assimilation and application of remote sensing data in energy balance modeling;
  • Uncertainty in remote sensing data or products for monitoring parameters related to water energy;
  • Monitoring the key drivers, feedback indicators, and parameters related to water energy processes;
  • Impact of water energy balance on the ecological environment and its relationship with the carbon cycle.

Dr. Linan Guo
Dr. Yanhong Wu
Dr. Junfeng Xiong
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 250 words) can be sent to the Editorial Office for assessment.

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-anonymized 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

  • water energy balance
  • thermodynamic processes
  • climate change
  • data assimilation
  • remote sensing in water environments
  • water resources

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Published Papers (1 paper)

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Research

24 pages, 6472 KB  
Article
SAR-Oriented and Physics-Guided Ocean Wave Spectrum Retrieval
by Yunxiao Li, Qi Wen, Xiu Zhu, Yuxin Liu, Lei Huang, Weifu Sun and Hao Zhang
Remote Sens. 2026, 18(17), 2892; https://doi.org/10.3390/rs18172892 - 26 Aug 2026
Viewed by 409
Abstract
Accurate retrieval of ocean wave spectra from Synthetic Aperture Radar (SAR) images is important for understanding wave energy distribution and supporting large-scale ocean-wave monitoring. However, existing SAR-based wave retrieval methods often focus on scalar wave parameters and pay limited attention to the physical [...] Read more.
Accurate retrieval of ocean wave spectra from Synthetic Aperture Radar (SAR) images is important for understanding wave energy distribution and supporting large-scale ocean-wave monitoring. However, existing SAR-based wave retrieval methods often focus on scalar wave parameters and pay limited attention to the physical consistency of spectral energy reconstruction. In this study, we propose a physics-guided texture-enhanced Swin Transformer, named PGT-Swin, for retrieving one-dimensional wave frequency spectra from SAR images. The proposed method first constructs multi-channel SAR representations by combining intensity-enhanced images with Gray-Level Co-Occurrence Matrix (GLCM)-based texture features. A Swin Transformer backbone is then used to capture both local wave textures and global periodic structures. In addition, physics-guided spectral constraints are introduced to preserve total spectral energy and frequency-distribution consistency. Experiments were conducted using collocated Sentinel-1 SAR images and one-dimensional frequency spectra derived from CFOSAT SWIM products. The results show that PGT-Swin can effectively reconstruct wave spectra and derive reliable integral wave parameters. For SWH retrieval, the model achieves an MSE of 0.0014 and an R2 of 0.9591. For MWP retrieval, it achieves an MSE of 0.0295 and an R2 of 0.6659. These results demonstrate the effectiveness of PGT-Swin for SAR-based one-dimensional wave frequency-spectrum retrieval within the evaluated SWIM-referenced setting. Full article
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