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Application of Remote Sensing Technology in Marine and Water Resources...
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Application of Remote Sensing Technology in Marine and Water Resources Observation

A special issue of Journal of Marine Science and Engineering (ISSN 2077-1312). This special issue belongs to the section "Marine Environmental Science".

Deadline for manuscript submissions: closed (25 March 2026) | Viewed by 4353

Special Issue Editors

Dr. Virginia Zamparelli

E-Mail Website
Guest Editor
Institute for Electromagnetic Sensing of the Environment (IREA), National Research Council of Italy (CNR), Naples, Italy
Interests: SAR; SAR processing; sea-surface parameters; sea-surface radial velocity; doppler centroid anomaly
Special Issues, Collections and Topics in MDPI journals
Dr. Simona Verde

E-Mail Website
Guest Editor
Institute for Electromagnetic Sensing of the Environment (IREA), National Research Council of Italy (CNR), Naples, Italy
Interests: remote sensing; synthetic aperture radar; SAR tomography; SAR interferometry
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

We are pleased to invite you to contribute a paper to the Special Issue titled “Application of Remote Sensing Technology in Marine and Water Resources Observation”.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:

  • Remote sensing concepts and advanced sensors for the marine/ocean environment and water resources;
  • Monitoring of marine/water litter and floating materials (such as sea ice, algal blooms, and oil-spill pollutions) achieved through the use of remote sensing methods;
  • Monitoring of parameters affecting the sea or lake surface, such as surface current, wind fields, wave height, sea/water level, ocean tide, sea/water surface temperature, and ocean surface salinity;
  • Innovative SAR concepts for optimal sensing of the marine and water environment;
  • Change detection techniques for marine and inland water observation;
  • PolSAR methods for maritime surveillance;
  • InSAR techniques for coastline changes, and river subsidence;
  • Applications in remote sensing for river water quality;
  • Remote sensing of the ocean water color;
  • Innovative applications using passive optical sensors in marine, coastal, and inland water environments;
  • Maritime surveillance case studies, including navigation in ice-infested waters, vessel detection, and ship traffic.

Dr. Virginia Zamparelli
Dr. Simona Verde
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Marine Science and Engineering 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 2600 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

  • ocean winds, wave, currents, and bathymetry
  • ecological applications: water quality, oil spill, and algal blooms
  • radar
  • remote sensing
  • ocean and coastal monitoring
  • coastal areas safety and protection
  • synthetic aperture radar
  • PolSAR, InSAR, and change detection techniques
  • optical data

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  • Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
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  • Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.

Further information on MDPI's Special Issue policies can be found here.

Published Papers (4 papers)

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Research

15 pages, 5038 KB  
Article
Phenological Patterns and Driving Mechanisms of Autumn Phytoplankton Blooms in the Yellow Sea Cold Water Mass (2000–2022)
by Mingxuan Liu, Botao Gu, Chunli Liu, Bei Su, Qicheng Meng, Yize Zhang and Min Li
J. Mar. Sci. Eng. 2026, 14(3), 313; https://doi.org/10.3390/jmse14030313 - 5 Feb 2026
Cited by 1 | Viewed by 427
Abstract
Phytoplankton blooms represent a typical ecological process in marine systems. Climate change drives shifts in its phenology, both directly via impacts on physiology and indirectly by modifying stratification intensity, nutrients, light availability, and grazing pressure. Using satellite remote sensing and reanalysis data from [...] Read more.
Phytoplankton blooms represent a typical ecological process in marine systems. Climate change drives shifts in its phenology, both directly via impacts on physiology and indirectly by modifying stratification intensity, nutrients, light availability, and grazing pressure. Using satellite remote sensing and reanalysis data from 2000 to 2022, this study partitions the Yellow Sea based on interannual variability in the Yellow Sea Cold Water Mass (YSCWM). Clear spatial differences in autumn bloom phenology are observed within the YSCWM. Earlier initiation dominates the Southern YSCWM (SYSCWM), while delayed later initiation concentrates in the Northern YSCWM (NYSCWM) and along the SYSCWM’s eastern margins. This pattern can be explained by the differences in regional hydrodynamics, i.e., the Yellow Sea Warm Current (YSWC) enhances upwelling and convergence in some YSCWM areas, boosting nutrient supply and earlier blooms, whereas weaker circulation-driven nutrient supply causes the bloom delay. Interannual variation analysis further reveals that the bloom timing is regulated by seasonal YSCWM dissipation since intensified autumn northerly winds accelerate dissipation and nutrient supply, thereby advancing blooms, while weaker northerly winds and stable circulation delay bloom progress by maintaining strong thermocline stability. These findings provide further insights into the underlying mechanisms driving autumn bloom dynamics and support ecosystem monitoring efforts in shelf seas. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Marine and Water Resources Observation)
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16 pages, 1782 KB  
Article
Evaluation of Different Approaches for Assessing Water Quality Using Sentinel-2/MSI: A Case Study in Coastal Ningde
by Binbin Jiang, Daidu Fan, Qinghui Huang, Xueding Li, Nguyen Dac Ve, Fahui Ren, Junyu Yu and Emmanuel Boss
J. Mar. Sci. Eng. 2026, 14(3), 267; https://doi.org/10.3390/jmse14030267 - 28 Jan 2026
Cited by 1 | Viewed by 419
Abstract
Water quality observations are vital for effectively managing coastal resources and influencing decisions from emergency beach closures to aquaculture leasing agreements. This study focuses on deriving two water quality parameters—Chlorophyll a (Chl-a) and suspended particulate matter (SPM)—through the high-resolution multispectral imager (MSI) onboard [...] Read more.
Water quality observations are vital for effectively managing coastal resources and influencing decisions from emergency beach closures to aquaculture leasing agreements. This study focuses on deriving two water quality parameters—Chlorophyll a (Chl-a) and suspended particulate matter (SPM)—through the high-resolution multispectral imager (MSI) onboard the Sentinel 2A&B satellites, specifically for the Ningde coastal region, which is a crucial aquaculture hub in China. Since more than 90% of the signals captured by satellites are affected by atmospheric interference, it is crucial to apply a process called “atmospheric correction” (AC) to isolate the water contribution, known as water leaving reflectance, from the radiance measured at the top of the atmosphere. Our research assesses five published AC models and various algorithms designed to accurately estimate Chl-a and SPM from water leaving reflectance. We determine the most effective combination by comparing these findings against in situ data gathered from eleven locations in the Ningde coastal region (POLYMER-SOLID with lowest metric RMSLE (0.29), and MAE (1.68) and POLYMER-MDN with the lowest metric RMSLE (0.59), and MAE (0.56)). Our study underscores the importance of selecting locally validated AC models and algorithms for generating water quality products, as this enhances the utility of remote sensing data in monitoring water quality. Moreover, we conduct a spatiotemporal analysis of the water quality parameters from 2016 to 2021, revealing significant interannual variability that underlines the need for continuous monitoring and robust data analysis in coastal management efforts. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Marine and Water Resources Observation)
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17 pages, 7213 KB  
Article
Deep Learning-Based Wind Speed Retrieval from Sentinel-1 SAR Wave Mode Data
by Ruixuan Sun, Chen Wang, Zhuhui Jiang and Xiaojuan Kong
J. Mar. Sci. Eng. 2025, 13(9), 1751; https://doi.org/10.3390/jmse13091751 - 11 Sep 2025
Cited by 1 | Viewed by 1586
Abstract
Sea surface wind has been listed as an essential climate variable, playing crucial roles in regulating the global and regional weather and climate. Spaceborne synthetic aperture radar (SAR) has demonstrated the advantages in observing the wind field given its all-weather measurement capability. In [...] Read more.
Sea surface wind has been listed as an essential climate variable, playing crucial roles in regulating the global and regional weather and climate. Spaceborne synthetic aperture radar (SAR) has demonstrated the advantages in observing the wind field given its all-weather measurement capability. In this study, we present a convolutional neural network (CNN)-based framework for retrieving 10 m wind speed (U10) from Sentinel-1 SAR wave mode (WV) imagery. The model is trained on SAR data acquired in 2017 using collocated ERA5 reanalysis wind vectors as the reference, with final performance evaluated against a temporally independent dataset from 2016 and in situ wind measurements. The CNN approach demonstrates improved retrieval accuracy compared to the conventional CMOD5.N-based result, achieving lower root mean square error (RMSE) and bias across both WV1 and WV2 incidence angle modes. Residual diagnostics show a systematic overestimation at low wind speeds and a slight underestimation at higher wind speeds. Spatial analyses of retrieval bias reveal regional variations, particularly in areas characterized by ocean swell or convective atmospheric activity, highlighting the importance of geophysical features in retrieval accuracy. These results support the viability of deep learning approaches for SAR-based ocean surface wind estimation and suggest a path forward for the development of more accurate, data-driven wind products suitable for both scientific research and operational marine forecasting. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Marine and Water Resources Observation)
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14 pages, 4107 KB  
Article
Spatiotemporal Evolution and Multi-Driver Dynamics of Sea-Level Changes in the Yellow–Bohai Seas (1993–2023)
by Lujie Xiong, Fengwei Wang, Yanping Jiao and Yunqi Zhou
J. Mar. Sci. Eng. 2025, 13(6), 1081; https://doi.org/10.3390/jmse13061081 - 29 May 2025
Viewed by 1150
Abstract
This study analyzes sea-level changes in the Yellow and Bohai Seas from 1993 to 2023 based on satellite altimetry data. After reconstructing the gridded sea-level data using local mean decomposition (LMD), the annual mean sea level was estimated at 28.86 mm, with an [...] Read more.
This study analyzes sea-level changes in the Yellow and Bohai Seas from 1993 to 2023 based on satellite altimetry data. After reconstructing the gridded sea-level data using local mean decomposition (LMD), the annual mean sea level was estimated at 28.86 mm, with an average rise rate of 2.21 mm per year (mm/a). Temporal and spatial variations were examined through nonlinear least squares fitting to capture interannual variability and decadal amplitude distributions. Empirical orthogonal function (EOF) analysis identified the first three modes, explaining 90.40%, 2.78%, and 1.47% of the total variance, respectively, and their spatial patterns and temporal coefficients were derived. The first mode was strongly correlated with sea surface temperature (SST) and precipitation, showing distinct spatial structures. Temperature and salinity profiles revealed a decadal-scale trend of increasing temperature and decreasing salinity with depth. Seasonal variations of sea-level anomaly (SLA) were evident, with mean values and trends of −11.47 mm (2.19 mm/a) in spring, 57.12 mm (2.29 mm/a) in summer, 75.68 mm (2.24 mm/a) in autumn, and −13.90 mm (2.11 mm/a) in winter. Seasonal correlations among SLA, SST, salinity, and precipitation were assessed, highlighting interannual amplitude variations. This integrated analysis provides a comprehensive understanding of the dynamics and drivers of sea-level fluctuations, offering insights for future research. Full article
(This article belongs to the Special Issue Application of Remote Sensing Technology in Marine and Water Resources Observation)
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