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Remote Sensing
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Applications of Satellite Altimetry in Ocean Observation
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Special Issue "Applications of Satellite Altimetry in Ocean Observation"

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

Deadline for manuscript submissions: 31 October 2023 | Viewed by 1715

Special Issue Editors

Dr. Antonio Sánchez-Román

E-Mail Website
Guest Editor
Mediterranean Institute for Advanced Studies (IMEDEA), C/ Miquel Marques 21, 07190 Esporles, Spain
Interests: ocean remote sensing; in situ observations; physical oceanography; mesoscale ocean dynamics
Dr. Bàrbara Barceló-Llull

E-Mail Website
Guest Editor
Mediterranean Institute for Advanced Studies (IMEDEA), C/ Miquel Marques 21, 07190 Esporles, Spain
Interests: mesoscale and submesoscale; ocean dynamics; in situ and remote sensing observations; biophysical interactions; machine-learning techniques; Lagrangian analysis
Special Issues, Collections and Topics in MDPI journals
Dr. Juan M. Sayol

E-Mail Website
Guest Editor
Department of Applied Mathematics, Polytechnic School, University of Alicante, 03690 Sant Vicent del Raspeig, Spain
Interests: ocean dynamics;air–sea interaction; extreme events; ocean state indicators; machine learning; Lagrangian dynamics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Over the last 30 years, satellite altimetry has provided global high-accuracy sea surface height measurements, enhancing our understanding of the upper ocean circulation from the (sub-) mesoscale to larger scales. The development of novel technologies, such as SAR Doppler altimetry, interferometric altimetry and swath instruments, together with new methods of reprocessing historical data, offers unique opportunities to study ocean dynamics from satellite altimetry data.

Satellite altimetry was initially designed to monitor the open ocean. However, new missions and efforts have aimed at extending the capabilities of current altimeters towards high latitudes and coastal zones. A common objective of recent altimetric missions, such as the Sentinel-3 series or the wide-swath SWOT mission, has been to resolve finer scales than previous altimeters. Altimetric observations are used to study the ocean circulation at the mesoscale and submesoscale (spatial scales > 15 km). These small scales drive the vertical transport of properties, and the two-dimensional data provided by altimeters are key to improving our understanding of the dynamics at play. In addition, synergies between satellite altimetry and in situ observations (e.g. the Argo system) allow for the assessment of the three-dimensional dynamics associated with these structures.

In this Special Issue, we invite high-quality scientific papers that use satellite altimetry observations to study the dynamics of the ocean. We welcome studies dealing with: (i) the assessment of global and regional sea level, (ii) surface currents and sea state at different spatiotemporal scales, (iii) multi-platform observations, (iv) the interaction between the open ocean and the coastal seas and (v) the evaluation of uncertainties related to altimetry data.

Dr. Antonio Sánchez-Román
Dr. Bàrbara Barceló-Llull
Dr. Juan M. Sayol
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 2500 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

  • radar altimetry
  • ocean circulation
  • sea level variability
  • mesoscale and sub-mesoscale features
  • large-scale processes
  • sea surface currents
  • coastal ocean monitoring
  • in situ observations
  • ocean waves
  • new altimeters

Published Papers (2 papers)

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Article
KaRIn Noise Reduction Using a Convolutional Neural Network for the SWOT Ocean Products
by
Anaëlle Tréboutte
,
Elisa Carli
,
Maxime Ballarotta
,
Benjamin Carpentier
,
Yannice Faugère
and
Gérald Dibarboure
Remote Sens. 2023, 15(8), 2183; https://doi.org/10.3390/rs15082183 - 20 Apr 2023
Viewed by 635
Abstract
The SWOT (Surface Water Ocean Topography) mission will provide high-resolution and two-dimensional measurements of sea surface height (SSH). However, despite its unprecedented precision, SWOT’s Ka-band Radar Interferometer (KaRIn) still exhibits a substantial amount of random noise. In turn, the random noise limits the [...] Read more.
The SWOT (Surface Water Ocean Topography) mission will provide high-resolution and two-dimensional measurements of sea surface height (SSH). However, despite its unprecedented precision, SWOT’s Ka-band Radar Interferometer (KaRIn) still exhibits a substantial amount of random noise. In turn, the random noise limits the ability of SWOT to capture the smallest scales of the ocean’s topography and its derivatives. In that context, this paper explores the feasibility, strengths and limits of a noise-reduction algorithm based on a convolutional neural network. The model is based on a U-Net architecture and is trained and tested with simulated data from the North Atlantic. Our results are compared to classical smoothing methods: a median filter, a Lanczos kernel smoother and the SWOT de-noising algorithm developed by Gomez-Navarro et al. Our U-Net model yields better results for all the evaluation metrics: 2 mm root mean square error, sub-millimetric bias, variance reduction by factor of 44 (16 dB) and an accurate power spectral density down to 10–20 km wavelengths. We also tested various scenarios to infer the robustness and the stability of the U-Net. The U-Net always exhibits good performance and can be further improved with retraining if necessary. This robustness in simulation is very encouraging: our findings show that the U-Net architecture is likely one of the best candidates to reduce the noise of flight data from KaRIn. Full article
(This article belongs to the Special Issue Applications of Satellite Altimetry in Ocean Observation)
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Article
A Robust Algorithm for Photon Denoising and Bathymetric Estimation Based on ICESat-2 Data
by
Junsheng Zhong
,
Xiuguo Liu
,
Xiang Shen
and
Liming Jiang
Remote Sens. 2023, 15(8), 2051; https://doi.org/10.3390/rs15082051 - 13 Apr 2023
Viewed by 833
Abstract
The Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) is equipped with an Advanced Terrain Laser Altimeter System (ATLAS) with the capability of penetrating water bodies, making it a widely utilized tool for the bathymetry of various aquatic environments. However, the laser sensor [...] Read more.
The Ice, Cloud, and Land Elevation Satellite 2 (ICESat-2) is equipped with an Advanced Terrain Laser Altimeter System (ATLAS) with the capability of penetrating water bodies, making it a widely utilized tool for the bathymetry of various aquatic environments. However, the laser sensor often encounters a significant number of noise photons due to various factors such as sunlight, water quality, and after-pulse effect. These noise photons significantly compromise the accuracy of bathymetry measurements. In an effort to address this issue, this study proposes a two-step method for photon denoising by utilizing a method combining the DBSCAN algorithm and a two-dimensional window filter, achieving an F1 score of 0.94. A robust M-estimation method was employed to estimate the water depth of the denoised and refraction-corrected bathymetric photons, achieving an RMSE of 0.30 m. The method proposed in this paper preserves as much information as possible about signal photons, increases the number of bathymetric points, enhances the resistance to gross error, and guarantees the accuracy of bathymetry measurements while outlining the underwater topography. While the method is not fully automated and requires setting parameters, the fixed parameter values allow for efficient batch denoising of underwater photon points in different environments. Full article
(This article belongs to the Special Issue Applications of Satellite Altimetry in Ocean Observation)
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