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SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications

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

Deadline for manuscript submissions: 20 June 2024 | Viewed by 4967

Special Issue Editors

Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
Interests: theories and applications of SoOP-R/GNSS-R, especially on land surface

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Guest Editor
School of Land Surveying, Geodesy and Mapping Engineering, Universidad Politécnica de Madrid, 28031 Madrid, Spain
Interests: monitoring earth’s environments through space geodesy and remote sensing
Special Issues, Collections and Topics in MDPI journals

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Guest Editor
1. Shanghai Astronomical Observatory, Chinese Academy of Sciences, Shanghai 200030, China
2. Department of Natural History Science, Hokkaido University, Sapporo 060-0809, Japan
Interests: gravity; crustal deformation; ionosphere/troposphere; plate tectonics; satellite positioning; lunar/planetary exploration; space geodetic techniques; earth rotation

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Guest Editor
National Time Service Center, Chinese Academy of Sciences, Xi’an 710600, China
Interests: GNSS-based time-varying gravity recovery; GNSS precise point positioning; stochastic model estimation for GNSS tropospheric delay

Special Issue Information

Dear Colleagues,

Signal of opportunity reflectometry has attracted increasing interest in the past three decades, especially with the invention of the GNSS reflectometry (GNSS-R), which employs the signals of GNSS constellations as the active source. With the launch of the first space-borne GNSS-R mission, i.e., the UK-DMC, a series of satellite missions were and are being launched for similar purposes, such as the TDS-1, the CYGNSS, the FY-3E GNOS-R, the HydroGNSS, etc. Meanwhile, signals from other satellites (communication, tv, etc.) could be also employed as an active source for this kind of remote sensing technique. The applications of this new and promising technique include monitoring in the microwave spectrum and the characterization of both ocean and land surfaces. Among others, the advantages of GNSS-R mainly center around its low costs, low power consumption, light weight, and small volume, being an efficient substitute or complement to traditional microwave remote sensing techniques. Thus, theory on scattering mechanisms and retrieval methods of physical variables for different application fields is very important.

The aim of this Special Issue is to focus on revealing theoretical mechanisms and solving the problems in current retrieval algorithms. Topics may cover the forward scattering models, including both ocean and land surface scenarios. Retrieval algorithms based on theoretical models are warmly welcome. Of course, new applications of SoO-R or GNSS-R are also accorded a very hearty welcome.

Articles may address, but are not limited, to the following topics:

  • Theoretical mechanism models for SoOP-R/GNSS-R, including ocean surface and land surface;
  • Retrieval algorithms based ontheoretical models of GNSS-R/IR for the ocean scenario;
  • Retrieval algorithms based ontheoretical models of GNSS-R/IR for the land surface scenario;
  • New and potential applications of SoOP-R/GNSS-R.

Dr. Xuerui Wu
Dr. Andrés Calabia
Prof. Dr. Kousuke Heki
Dr. Xinggang Zhang
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

  • global navigation satellite systems (GNSSs)
  • GNSS reflectometry
  • signal of opportunity reflectometry
  • ocean surface
  • land surface
  • scattering models

Published Papers (6 papers)

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Research

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20 pages, 10156 KiB  
Article
Characteristics Analysis of Influence of Multiple Parameters of Mixed Sea Waves on Delay–Doppler Map in Global Navigation Satellite System Reflectometry
by Jianan Yan, Ding Nie, Kaicheng Zhang and Min Zhang
Remote Sens. 2024, 16(8), 1395; https://doi.org/10.3390/rs16081395 - 15 Apr 2024
Viewed by 433
Abstract
Feature capture and recognition of sea wave components in radar systems especially in global navigation satellite system reflectometry (GNSS-R) using signal processing approaches or computer simulative methods has become a research hotspot in recent years. At the same time, parameter inversion of marine [...] Read more.
Feature capture and recognition of sea wave components in radar systems especially in global navigation satellite system reflectometry (GNSS-R) using signal processing approaches or computer simulative methods has become a research hotspot in recent years. At the same time, parameter inversion of marine phenomena from the discovered characteristics plays a significant role in monitoring and forewarning the different components of sea waves. This paper aims to investigate the impact of multiple parameters, such as the wind speed, directionality variable, wave amplitude, wave length, and directions of sea wave components, on the delay waveform of the delay–Doppler map (DDM). Two types of wind waves and the 2-D sinusoidal sea surface are chosen to be analyzed. By comparing and analyzing the discrepancy of delay waveforms under different conditions, it can be concluded that the increased MSS which arises from the increase in the roughness of the sea surface can lead to the difference in the peak value or trial edges exhibited in delay waveforms. The values of delay waveforms at zero chip along the increasing direction of long-crest wind waves exhibit the periodic spikes shape, which is the opposite of the short-crest wind waves, and the fluctuation of the periodic profiles decreases with the increase in the amplitude of waves. The results and conclusions can provide a foundation for the parameter inversion, tracking, and early warning of anomalous formations of waves in bistatic radar configuration. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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23 pages, 9516 KiB  
Article
GNSS-IR Soil Moisture Inversion Derived from Multi-GNSS and Multi-Frequency Data Accounting for Vegetation Effects
by Haohan Wei, Xiaofeng Yang, Yuwei Pan and Fei Shen
Remote Sens. 2023, 15(22), 5381; https://doi.org/10.3390/rs15225381 - 16 Nov 2023
Cited by 1 | Viewed by 868
Abstract
The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique provides a new remote sensing method that shows great potential for soil moisture detection and vegetation growth, as well as for climate research, water cycle management, and ecological environment monitoring. Considering that the land [...] Read more.
The Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique provides a new remote sensing method that shows great potential for soil moisture detection and vegetation growth, as well as for climate research, water cycle management, and ecological environment monitoring. Considering that the land surface is always covered by vegetation, it is essential to take into account the impacts of vegetation growth when detecting soil moisture (SM). In this paper, based on the GNSS-IR technique, the SM was retrieved from multi-GNSS and multi-frequency data using a machine learning model, accounting for the impact of the vegetation moisture content (VMC). Both the signal-to-noise ratio (SNR) data that was used to retrieve SM and the multipath data that was used to eliminate the vegetation influence were collected from a standard geodetic GNSS station located in Nanjing, China. The normalized microwave reflectance index (NMRI) calculated by multipath data was mapped to a normalized difference vegetation index (NDVI), which was derived from Sentinel-2 data on the Google Earth Engine platform to estimate and eliminate the influence of VMC. Based on the characteristic parameters of amplitude and phase extracted from detrended SNR signals and NDVI derived from multipath data, three machine learning methods, including random forest (RF), multiple linear regression (MLR), and multivariate adaptive regression spline (MARS), were employed for data fusion. The results show that the vegetation effect can be well eliminated using the NMRI method. Comparing MLR and MARS, RF is more suitable for GNSS-IR SM inversion. Furthermore, the SM reversed from amplitude and phase fusion is better than only those from either amplitude fusion or phase fusion. The results prove the feasibility of the proposed method based on a multipath approach to characterize the vegetation effect, as well as the RF model to fuse multi-GNSS and multi-frequency data to retrieve SM with vegetation error-correcting. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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18 pages, 6200 KiB  
Article
LAGRS-Soil: A Full-Polarization GNSS-Reflectometry Model for Bare Soil Applications in FY-3E GNOS-R Payload
by Xuerui Wu, Xinqiu Ouyang, Junming Xia, Zhe Yan and Fang Wang
Remote Sens. 2023, 15(22), 5296; https://doi.org/10.3390/rs15225296 - 9 Nov 2023
Viewed by 788
Abstract
The Land Surface GNSS Reflection Simulator (LAGRS)-Soil model represents a significant advancement in soil moisture detection with the aid of Global Navigation Satellite System (GNSS) Occultation Sounder-Reflectometry (GNOS-R) technology, which is one payload of the Fengyun-3E (FY-3E) satellite that was launched on 5 [...] Read more.
The Land Surface GNSS Reflection Simulator (LAGRS)-Soil model represents a significant advancement in soil moisture detection with the aid of Global Navigation Satellite System (GNSS) Occultation Sounder-Reflectometry (GNOS-R) technology, which is one payload of the Fengyun-3E (FY-3E) satellite that was launched on 5 July 2021. To fully exploit the properties of noncoherent scattering, the LAGRS-Soil model has the capability to calculate DDM information for different observational geometries, which relies on the random surface scattering models employed in LAGRS-Soil. This will provide a comprehensive understanding of soil moisture dynamics across diverse terrains and environments. One of the most notable features of LAGRS-Soil is its ability to obtain DDMs for full polarizations, which enhances soil moisture retrievals compared to current methods that only utilize the commonly used LR polarization (left-hand circular polarization received and right-hand circular polarization transmitted). Meanwhile, the model can also capture frozen soil DDMs which holds immense potential for near-surface Freezing/Thawing (F/T) detection, opening up new research and application opportunities in cold climate regions. LAGRS-Soil is built on microwave scattering models, making it a robust and efficient theoretical model for the FY-3E GNOS-R payload. This model can support ongoing soil moisture retrieval efforts by combining physical models with investigations of diffuse scattering and polarization capabilities for soil moisture detection. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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19 pages, 14814 KiB  
Article
Improved Geometric Optics with Topography (IGOT) Model for GNSS-R Delay-Doppler Maps Using Three-Scale Surface Roughness
by Amer Melebari, James D. Campbell, Erik Hodges and Mahta Moghaddam
Remote Sens. 2023, 15(7), 1880; https://doi.org/10.3390/rs15071880 - 31 Mar 2023
Cited by 4 | Viewed by 1441
Abstract
Although multiple efforts have been made to model global navigation satellite system (GNSS)-reflectometry (GNSS-R) delay-Doppler maps (DDMs) over land, there is still a need for models that better represent the signals over land and can enable reliable retrievals of the geophysical variables. Our [...] Read more.
Although multiple efforts have been made to model global navigation satellite system (GNSS)-reflectometry (GNSS-R) delay-Doppler maps (DDMs) over land, there is still a need for models that better represent the signals over land and can enable reliable retrievals of the geophysical variables. Our paper presents improvements to an existing GNSS-R DDM model by accounting for short-wave diffraction due to small-scale ground surface roughness and signal attenuation due to vegetation. This is a step forward in increasing the model fidelity. Our model, called the improved geometric optics with topography (IGOT), predicts GNSS-R DDM over land for the purpose of retrieving geophysical parameters, including soil moisture. Validation of the model is carried out using DDMs from the Cyclone GNSS (CYGNSS) mission over two validation sites with in situ soil moisture sensors: Walnut Gulch, AZ, USA, and the Jornada Experimental Range, NM, USA. Both the peak reflectivity and the DDM shape are studied. The results of the study show that the IGOT model is able to accurately predict CYGNSS DDMs at these two validation sites. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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Review

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17 pages, 5274 KiB  
Review
Reviewing Space-Borne GNSS-Reflectometry for Detecting Freeze/Thaw Conditions of Near-Surface Soils
by Haishan Liang and Xuerui Wu
Remote Sens. 2024, 16(11), 1828; https://doi.org/10.3390/rs16111828 - 21 May 2024
Viewed by 308
Abstract
GNSS-Reflectometry, a technique that harnesses the power of microwave remote sensing, is poised to revolutionize our ability to detect and monitor near-surface soil freeze/thaw processes. This technique’s theoretical underpinnings are deeply rooted in the comprehensive explanation of the Zhang–Zhao dielectric constant model, which [...] Read more.
GNSS-Reflectometry, a technique that harnesses the power of microwave remote sensing, is poised to revolutionize our ability to detect and monitor near-surface soil freeze/thaw processes. This technique’s theoretical underpinnings are deeply rooted in the comprehensive explanation of the Zhang–Zhao dielectric constant model, which provides crucial insights into the behavior of frozen and thawed soils. The model elucidates how the dielectric properties of soil change as it transitions between frozen and thawed states, offering a scientific basis for understanding reflectivity variations. Furthermore, the theoretical framework includes a set of formulas that are instrumental in calculating reflectivity at Lower Right (LR) polarization and in deriving Dual-Polarization Differential Observables (DDMs). These calculations are pivotal for interpreting the signals captured by GNSS-R sensors, allowing for the detection of subtle changes in the soil’s surface conditions. The evolution of GNSS-R as a tool for detecting freeze/thaw phenomena has been substantiated through qualitative analyses involving multiple satellite missions, such as SMAP-R, TDS-1, and CYGNSS. These analyses have provided empirical evidence of the technique’s effectiveness, illustrating its capacity to capture the dynamics of soil freezing and thawing processes. In addition to these qualitative assessments, the application of a discriminant retrieval algorithm using data from CYGNSS and F3E GNOS-R has further solidified the technique’s potential. This algorithm contributes to refining the accuracy of freeze/thaw detection by distinguishing between frozen and thawed soil states with greater precision. The deployment of space-borne GNSS-R for monitoring near-surface freeze/thaw cycles has yielded commendable results, exhibiting robust consistency and delivering relatively precise retrieval outcomes. These achievements stand as testaments to the technique’s viability and its growing significance in the field of remote sensing. However, it is imperative to recognize and actively address certain limitations that have been highlighted in this review. These limitations serve as critical focal points for future research endeavors, directing the efforts toward enhancing the technique’s overall performance and applicability. Addressing these challenges will be essential for leveraging the full potential of GNSS-R to advance our understanding and management of near-surface soil freeze/thaw processes. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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27 pages, 4669 KiB  
Review
GNSS Reflectometry-Based Ocean Altimetry: State of the Art and Future Trends
by Tianhe Xu, Nazi Wang, Yunqiao He, Yunwei Li, Xinyue Meng, Fan Gao and Ernesto Lopez-Baeza
Remote Sens. 2024, 16(10), 1754; https://doi.org/10.3390/rs16101754 - 15 May 2024
Viewed by 315
Abstract
For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth’s surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth’s [...] Read more.
For the past 20 years, Global Navigation Satellite System reflectometry (GNSS-R) technology has successfully shown its potential for remote sensing of the Earth’s surface, including ocean and land surfaces. It is a multistatic radar that uses the GNSS signals reflected from the Earth’s surface to extract land and ocean characteristics. Because of its numerous advantages such as low cost, multiple signal sources, and all-day/weather and high-spatiotemporal-resolution observations, this new technology has attracted the attention of many researchers. One of its most promising applications is GNSS-R ocean altimetry, which can complement existing techniques such as tide gauging and radar satellite altimetry. Since this technology for ocean altimetry was first proposed in 1993, increasing progress has been made including diverse methods for processing reflected signals (such as GNSS interferometric reflectometry, conventional GNSS-R, and interferometric GNSS-R), different instruments (such as an RHCP antenna with one geodetic receiver, a linearly polarized antenna, and a system of simultaneously used RHCP and LHCP antennas with a dedicated receiver), and different platform applications (such as ground-based, air-borne, or space-borne). The development of multi-mode and multi-frequency GNSS, especially for constructing the Chinese BeiDou Global Navigation Satellite System (BDS-3), has enabled more free signals to be used to further promote GNSS-R applications. The GNSS has evolved from its initial use of GPS L1 and L2 signals to include other GNSS bands and multi-GNSS signals. Using more advanced, multi-frequency, and multi-mode signals will bring new opportunities to develop GNSS-R technology. In this paper, studies of GNSS-R altimetry are reviewed from four perspectives: (1) classifications according to different data processing methods, (2) different platforms, (3) development of different receivers, and (4) our work. We overview the current status of GNSS-R altimetry and describe its fundamental principles, experiments, recent applications to ocean altimetry, and future directions. Full article
(This article belongs to the Special Issue SoOP-Reflectometry or GNSS-Reflectometry: Theory and Applications)
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