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Radar Based Water Level Estimation
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Radar Based Water Level Estimation

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 17351

Special Issue Editors

Dr. Frédéric Frappart

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Guest Editor
Interactions Sol Plante Atmosphère, UMR 1391 INRAE/Bordeaux Science Agro 71, Avenue Edouard Bourlaux, 33882 Villenave d'Ornon, France
Interests: remote sensing; water cycle; carbon cycle; wetlands
Special Issues, Collections and Topics in MDPI journals
Dr. Isabel Vigo

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Guest Editor
Departamento de Matemática Aplicada, University of Alicante, 03690 Alicante, Spain
Interests: space geodesy; earth observation; sea level, ocean geostrophy; satellite altimetry; satellite gravimetry
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Dr. Joana Fernandes

E-Mail Website
Guest Editor
Department of Geosciences, Environment and Spatial Planning, University of Porto, Rua do Campo Alegre, 687, 4169-007 Porto, Portugal
Interests: remote sensing; satellite altimetry; coastal and inland water altimetry; range and geophysical corrections; wet tropospheric correction; sea state bias
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Dr. David García-García

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Guest Editor
Departamento de Matemática Aplicada, University of Alicante, 03690 Alicante, Spain
Interests: space geodesy; water mass transport; time-variable gravity; ocean geostrophy
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Dr. José Darrozes

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Guest Editor
Géosciences Environnement Toulouse (GET), UMR CNRS5563, CNRS/IRD/UPS, Observatoire Midi-Pyrénées (OMP), 14 Avenue Edouard Belin, 31400 Toulouse, France
Interests: earth observation; river morphology; near surface geophysics; soil moisture; GNSS-R; water cycle; soil contamination; remote sensing
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Dr. Fabien Blarel

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Guest Editor
CNRS, 14 avenue Edouard BELIN, France
Interests: hydrology; land surface processes; remote sensing
Dr. Cassandra Normandin

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Guest Editor
Laboratory of Astrophysics, Bordeaux, France
Interests: radar altimetry; aquatic color radiometry; hydrology; sediment transport
Dr. Song Shu

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Guest Editor
Department of Geography and Planning, Appalachian State University, Boone, NC 28608, USA
Interests: remote sensing applications applied to Arctic snow, lake hydrology, water resources, cryospheric processes, and global climate change; using a variety of advanced remote sensing technologies and geospatial analysis methods to quantify and analyze rapid environmental changes in the hydrosphere and cryosphere within the context of global climate change
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Radar techniques have demonstrated a strong capacity for the measurement of water levels from in situ, airborne or spaceborne sensors. In situ tide gauges are now commonly equipped with radar sensors to accurately monitor sea surface heights. Global navigation satellite systems (GNSS) geodetic sensors deployed on buoys are more and more used for the same purpose, especially offshore, where they are part of tsunami and/or storm coastal surges detection systems, providing real-time information on sea level. GNSS reflectometry (GNSS-R) is also a promising technique to estimate water levels over open ocean, coastal areas, and inland water bodies (lakes, rivers) which can be deployed on the ground or in airborne and spaceborne platforms. Radar altimetry onboard satellite platforms is the unique technique which allows estimating sea level variations over the whole ocean. In spite of degraded accuracies in coastal areas and over land, these observations are increasingly used over these latter two surfaces to densify the existing in situ gauge networks or replace them when they stop operating. InSAR spaceborne measurements are also used for hydrological applications. As InSAR data are currently mostly acquired with a time delay, their major uses are the topography of floodplains and lake banks during low water periods and the changes in water levels over floodplains and wetlands. After the launch of the Surface Water and Ocean Topography (SWOT) mission in 2022, which will simultaneously acquire SAR images at different incidence angles, the InSAR technique will provide, for the first time, water levels over ocean and land in two swaths, opening a new era for radar altimetry. This Special Issue aims to present reviews and recent advances of general interest in the use of radar for water level estimates. We encourage the submission of manuscripts presenting new methodology and new applications of radar techniques including GNSS, GNSS-R, radar altimetry, and especially from recent altimetric technology (SAR, SARin and Ka band) and improvements expected from missions to be launched in the near future (i.e., SWOT), or analyzing the accuracy of radar techniques for water level estimates.

Dr. Frédéric Frappart
Dr. Isabel Vigo
Dr. Joana Fernandes
Dr. David García-García
Dr. José Darrozes
Dr. Fabien Blarel
Dr. Cassandra Normandin
Dr. Song Shu
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.

Keywords

  • water levels
  • ocean dynamic topography
  • surface water topography
  • radar
  • altimetry
  • InSAR
  • GNSS
  • GNSS-R
  • floodplain water volume
  • river bank topography changes

Published Papers (4 papers)

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Research

19 pages, 13893 KiB  
Article
Measuring Coastal Absolute Sea-Level Changes Using GNSS Interferometric Reflectometry
by Dongju Peng, Lujia Feng, Kristine M. Larson and Emma M. Hill
Remote Sens. 2021, 13(21), 4319; https://doi.org/10.3390/rs13214319 - 27 Oct 2021
Cited by 10 | Viewed by 3657
Abstract
Rising sea levels pose one of the greatest threats to coastal zones. However, sea-level changes near the coast, particularly absolute sea-level changes, have been less well monitored than those in the open ocean. In this study, we aim to investigate the potential of [...] Read more.
Rising sea levels pose one of the greatest threats to coastal zones. However, sea-level changes near the coast, particularly absolute sea-level changes, have been less well monitored than those in the open ocean. In this study, we aim to investigate the potential of Global Navigation Satellite Systems Interferometric Reflectometry (GNSS-IR) to measure coastal absolute sea-level changes and tie on-land (coastal GNSS) and offshore (satellite altimetry) observations into the same framework. We choose three coastal GNSS stations, one each in regions of subsidence, uplift and stable vertical land motions, to derive both relative sea levels and sea surface heights (SSH) above the satellite altimetry reference ellipsoid from 2008 to 2020. Our results show that the accuracy of daily mean sea levels from GNSS-IR is <1.5 cm compared with co-located tide-gauge records, and amplitudes of annual cycle and linear trends estimated from GNSS-IR measurements and tide-gauge data agree within uncertainty. We also find that the de-seasoned and de-trended SSH time series from GNSS-IR and collocated satellite altimetry are highly correlated and the estimated annual amplitudes and linear trends statistically agree well, indicating that GNSS-IR has the potential to monitor coastal absolute sea-level changes and provide valuable information for coastal sea-level and climate studies. Full article
(This article belongs to the Special Issue Radar Based Water Level Estimation)
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22 pages, 7977 KiB  
Article
Automatic Detection of Inland Water Bodies along Altimetry Tracks for Estimating Surface Water Storage Variations in the Congo Basin
by Frédéric Frappart, Pierre Zeiger, Julie Betbeder, Valéry Gond, Régis Bellot, Nicolas Baghdadi, Fabien Blarel, José Darrozes, Luc Bourrel and Frédérique Seyler
Remote Sens. 2021, 13(19), 3804; https://doi.org/10.3390/rs13193804 - 23 Sep 2021
Cited by 18 | Viewed by 4090
Abstract
Surface water storage in floodplains and wetlands is poorly known from regional to global scales, in spite of its importance in the hydrological and the carbon balances, as the wet areas are an important water compartment which delays water transfer, modifies the sediment [...] Read more.
Surface water storage in floodplains and wetlands is poorly known from regional to global scales, in spite of its importance in the hydrological and the carbon balances, as the wet areas are an important water compartment which delays water transfer, modifies the sediment transport through sedimentation and erosion processes, and are a source for greenhouse gases. Remote sensing is a powerful tool for monitoring temporal variations in both the extent, level, and volume, of water using the synergy between satellite images and radar altimetry. Estimating water levels over flooded area using radar altimetry observation is difficult. In this study, an unsupervised classification approach is applied on the radar altimetry backscattering coefficients to discriminate between flooded and non-flooded areas in the Cuvette Centrale of Congo. Good detection of water (open water, permanent and seasonal inundation) is above 0.9 using radar altimetry backscattering from ENVISAT and Jason-2. Based on these results, the time series of water levels were automatically produced. They exhibit temporal variations in good agreement with the hydrological regime of the Cuvette Centrale. Comparisons against a manually generated time series of water levels from the same missions at the same locations show a very good agreement between the two processes (i.e., RMSE ≤ 0.25 m in more than 80%/90% of the cases and R ≥ 0.95 in more than 95%/75% of the cases for ENVISAT and Jason-2, respectively). The use of the time series of water levels over rivers and wetlands improves the spatial pattern of the annual amplitude of water storage in the Cuvette Centrale. It also leads to a decrease by a factor of four for the surface water estimates in this area, compared with a case where only time series over rivers are considered. Full article
(This article belongs to the Special Issue Radar Based Water Level Estimation)
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28 pages, 6615 KiB  
Article
Evaluation of the Performances of Radar and Lidar Altimetry Missions for Water Level Retrievals in Mountainous Environment: The Case of the Swiss Lakes
by Frédéric Frappart, Fabien Blarel, Ibrahim Fayad, Muriel Bergé-Nguyen, Jean-François Crétaux, Song Shu, Joël Schregenberger and Nicolas Baghdadi
Remote Sens. 2021, 13(11), 2196; https://doi.org/10.3390/rs13112196 - 04 Jun 2021
Cited by 32 | Viewed by 5522
Abstract
Radar altimetry is now commonly used to provide long-term monitoring of inland water levels in complement to or for replacing disappearing in situ networks of gauge stations. Recent improvements in tracking and acquisition modes improved the quality the water retrievals. The newly implemented [...] Read more.
Radar altimetry is now commonly used to provide long-term monitoring of inland water levels in complement to or for replacing disappearing in situ networks of gauge stations. Recent improvements in tracking and acquisition modes improved the quality the water retrievals. The newly implemented Open Loop mode is likely to increase the number of monitored water bodies owing to the use of an a priori elevation, especially in hilly and mountainous areas. The novelty of this study is to provide a comprehensive evaluation of the performances of the past and current radar altimetry missions according to their acquisition (Low Resolution Mode or Synthetic Aperture Radar) and tracking (close or open loop) modes, and acquisition frequency (Ku or Ka) in a mountainous area where tracking losses of the signal are likely to occur, as well as of the recently launched ICESat-2 and GEDI lidar missions. To do so, we evaluate the quality of water level retrievals from most radar altimetry missions launched after 1995 over eight lakes in Switzerland, using the recently developed ALtimetry Time Series software, to compare the performances of the new tracking and acquisition modes and also the impact of the frequency used. The combination of the Open Loop tracking mode with the Synthetic Aperture Radar acquisition mode on SENTINEL-3A and B missions outperforms the classical Low Resolution Mode of the other missions with a lake observability greater than 95%, an almost constant bias of (−0.17 ± 0.04) m, a RMSE generally lower than 0.07 m and a R most of the times higher than 0.85 when compared to in situ gauge records. To increase the number of lakes that can be monitored and the temporal sampling of the water level retrievals, data acquired by lidar altimetry missions were also considered. Very accurate results were also obtained with ICESat-2 data with RMSE lower than 0.06 and R higher than 0.95 when compared to in situ water levels. An almost constant bias (0.42 ± 0.03) m was also observed. More contrasted results were obtained using GEDI. As these data were available on a shorter time period, more analyses are necessary to determine their potential for retrieving water levels. Full article
(This article belongs to the Special Issue Radar Based Water Level Estimation)
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18 pages, 9142 KiB  
Article
SNR-Based Water Height Retrieval in Rivers: Application to High Amplitude Asymmetric Tides in the Garonne River
by Pierre Zeiger, Frédéric Frappart, José Darrozes, Nicolas Roussel, Philippe Bonneton, Natalie Bonneton and Guillaume Detandt
Remote Sens. 2021, 13(9), 1856; https://doi.org/10.3390/rs13091856 - 10 May 2021
Cited by 10 | Viewed by 2368
Abstract
Signal-to-noise ratio (SNR) time series acquired by a geodetic antenna were analyzed to retrieve water heights during asymmetric tides on a narrow river using the Interference Pattern Technique (IPT) from Global Navigation Satellite System Reflectometry (GNSS-R). The dynamic SNR method was selected because [...] Read more.
Signal-to-noise ratio (SNR) time series acquired by a geodetic antenna were analyzed to retrieve water heights during asymmetric tides on a narrow river using the Interference Pattern Technique (IPT) from Global Navigation Satellite System Reflectometry (GNSS-R). The dynamic SNR method was selected because the elevation rate of the reflecting surface during rising tides is high in the Garonne River with macro tidal conditions. A new process was developed to filter out the noise introduced by the environmental conditions on the reflected signal due to the narrowness of the river compared to the size of the Fresnel areas, the presence of vegetation on the river banks, and the presence of boats causing multiple reflections. This process involved the removal of multipeaks in the Lomb-Scargle Periodogram (LSP) output and an iterative least square estimation (LSE) of the output heights. Evaluation of the results was performed against pressure-derived water heights. The best results were obtained using all GNSS bands (L1, L2, and L5) simultaneously: R = 0.99, ubRMSD = 0.31 m. We showed that the quality of the retrieved heights was consistent, whatever the vertical velocity of the reflecting surface, and was highly dependent on the number of satellites visible. The sampling period of our solution was 1 min with a 5-min moving window, and no tide models or fit were used in the inversion process. This highlights the potential of the dynamic SNR method to detect and monitor extreme events with GNSS-R, including those affecting inland waters such as flash floods. Full article
(This article belongs to the Special Issue Radar Based Water Level Estimation)
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