Inter-comparison of GNSS-Reflectometry measurements from CYGNSS and Spire’s satellites with SMAP soil moisture product

2021 ◽  
Author(s):  
Vahid Freeman ◽  
Philip Jales ◽  
Stephan Esterhuizen ◽  
Vladimir Irisov ◽  
Jessica Cartwright ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Satellite System ◽  
Earth Observation ◽  
Regular Grid ◽  
Statistical Parameters ◽  
Global Soil ◽  
Gnss Reflectometry ◽  
Level 1 ◽  
The Uk ◽  
Global Navigation Satellite

<p>The potential of space-borne GNSS-Reflectometry (GNSS-R) technique for soil moisture retrieval has been demonstrated in recent studies using observations from the NASA’s Cyclone Global Navigation Satellite System (CYGNSS) and the UK’s Technology Demonstration Satellite, TechDemoSat (TDS-1).</p><p>Spire Global operates a constellation of CubeSats performing GNSS based science and Earth observation. In December 2019, Spire launched two new satellites with GNSS-R payloads with plans to launch two more follow-on GNSS-R missions in January 2021. In this study, we highlight the capabilities of the Spire’s current and future GNSS-R missions compared to CYGNSS for global soil moisture monitoring and present the results of an inter-comparison between CYGNSS and Spire GNSS-R observables over land with NASA’s Soil Moisture Active Passive (SMAP) observations. The comparison of level-1 data and various statistical parameters was performed after data collocation both trackwise and also within a 6km regular grid. The results of the study were used for intercalibration of CYGNSS and Spire’s GNSS-R measurements for developing a combined GNSS-R soil moisture product.</p>

Earth Surface Monitoring with Spire’s New GNSS Reflectometry (GNSS-R) CubeSats

2020 ◽  
Author(s):  
Vahid Freeman ◽  
Dallas Masters ◽  
Philp Jales ◽  
Stephan Esterhuizen ◽  
Ellie Ebrahimi ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Spatial Resolution ◽  
Precise Orbit Determination ◽  
Satellite System ◽  
Detection Algorithm ◽  
Earth Surface ◽  
Wind Speeds ◽  
Gnss Reflectometry ◽  
The Uk ◽  
Global Navigation Satellite

<p>Spire Global operates the world’s largest and rapidly growing constellation of CubeSats performing GNSS based science and Earth observation. The Spire constellation, performs a variety of GNSS science, including radio occultation (GNSS-RO), ionosphere and space weather measurements, and precise orbit determination. In December 2019, Spire launched two new satellites to perform GNSS reflectometry (GNSS-R). GNSS-R is a relatively new technique based on a passive bistatic radar system. The potential of space-borne GNSS-R observations for ocean and land applications has been demonstrated by other GNSS-R missions, including the NASA Cyclone Global Navigation Satellite System (CYGNSS) and the UK’s Technology Demonstration Satellite, TechDemoSat (TDS-1). </p><p>We present initial results from these new Spire GNSS-R satellites that are primarily focused on retrieving soil moisture but also estimate other Earth surface properties such as ocean wind speeds and flood inundation/wetland mapping. Prior to the launch of Spire’s GNSS-R satellites and in preparation for Level-2 data production, we developed algorithms and processing chains for land applications. We will present Spire's Soil Moisture (SM) retrieval method using CYGNSS observations. We evaluated the implemented SM change detection algorithm by comparing the Spire’s daily SM product with NASA’s Soil Moisture Active Passive (SMAP) observations and in-situ SM measurements. The results of study indicate remarkable retrieval skills of the GNSS-R technique for soil moisture monitoring at a medium spatial resolution. Spire’s GNSS-R satellites are tuned for land applications with a series of hardware and software optimizations for better signal calibration and acquiring many more data per satellite compared to CYGNSS. A more robust GNSS-R SM retrieval at finer spatial resolution will be possible in the near future after having more Spire satellites in orbit.</p><p>Spire’s current and future GNSS-R satellites will provide unprecedented sub-daily global coverage with sub-kilometer spatial resolution. Such intensive data acquisition is of great importance for many land and ocean applications. </p>

scholarly journals First Assessment of Geophysical Sensitivities from Spaceborne Galileo and BeiDou GNSS-Reflectometry Data Collected by the UK TechDemoSat-1 Mission

2020 ◽  
Vol 12 (18) ◽  
pp. 2927
Author(s):  
Matthew L. Hammond ◽  
Giuseppe Foti ◽  
Jonathan Rawlinson ◽  
Christine Gommenginger ◽  
Meric Srokosz ◽  
...  
Keyword(s):  
Sea Ice ◽  
Signal To Noise Ratio ◽  
Satellite System ◽  
Open Ocean ◽  
Multiple Systems ◽  
Ocean Winds ◽  
Gnss Reflectometry ◽  
The Uk ◽  
Global Navigation Satellite ◽  
Data Collections

The UK’s TechDemoSat-1 (TDS-1), launched 2014, has demonstrated the use of global positioning system (GPS) signals for monitoring ocean winds and sea ice. Here it is shown, for the first time, that Galileo and BeiDou signals detected by TDS-1 show similar promise. TDS-1 made seven raw data collections, recovering returns from Galileo and BeiDou, between November 2015 and March 2019. The retrieved open ocean delay Doppler maps (DDMs) are similar to those from GPS. Over sea ice, the Galileo DDMs show a distinctive triple peak. Analysis, adapted from that for GPS DDMs, gives Galileo’s signal-to-noise ratio (SNR), which is found to be inversely sensitive to wind speed, as for GPS. A Galileo track transiting from open ocean to sea ice shows a strong instantaneous SNR response. These results demonstrate the potential of future spaceborne constellations of GNSS-R (global navigation satellite system–reflectometry) instruments for exploiting signals from multiple systems: GPS, Galileo, and BeiDou.

scholarly journals From GPS Receiver to GNSS Reflectometry Payload Development for the Triton Satellite Mission

2021 ◽  
Vol 13 (5) ◽  
pp. 999
Author(s):  
Yung-Fu Tsai ◽  
Wen-Hao Yeh ◽  
Jyh-Ching Juang ◽  
Dian-Syuan Yang ◽  
Chen-Tsung Lin
Keyword(s):  
Satellite System ◽  
Low Earth Orbit ◽  
Export Control ◽  
Navigation Systems ◽  
Gps Receiver ◽  
Design Development ◽  
Satellite Mission ◽  
Essential Components ◽  
Gnss Reflectometry ◽  
Global Navigation Satellite

The global positioning system (GPS) receiver has been one of the most important navigation systems for more than two decades. Although the GPS system was originally designed for near-Earth navigation, currently it is widely used in highly dynamic environments (such as low Earth orbit (LEO)). A space-capable GPS receiver (GPSR) is capable of providing timing and navigation information for spacecraft to determine the orbit and synchronize the onboard timing; therefore, it is one of the essential components of modern spacecraft. However, a space-grade GPSR is technology-sensitive and under export control. In order to overcome export control, the National Space Organization (NSPO) in Taiwan completed the development of a self-reliant space-grade GPSR in 2014. The NSPO GPSR, built in-house, has passed its qualification tests and is ready to fly onboard the Triton satellite. In addition to providing navigation, the GPS/global navigation satellite system (GNSS) is facilitated to many remote sensing missions, such as GNSS radio occultation (GNSS-RO) and GNSS reflectometry (GNSS-R). Based on the design of the NSPO GPSR, the NSPO is actively engaged in the development of the Triton program (a GNSS reflectometry mission). In a GNSS-R mission, the reflected signals are processed to form delay Doppler maps (DDMs) so that various properties (including ocean surface roughness, vegetation, soil moisture, and so on) can be retrieved. This paper describes not only the development of the NSPO GPSR but also the design, development, and special features of the Triton’s GNSS-R mission. Moreover, in order to verify the NSPO GNSS-R receiver, ground/flight tests are deemed essential. Then, data analyses of the airborne GNSS-R tests are presented in this paper.

scholarly journals Computation Approach for Quantitative Dielectric Constant from Time Sequential Data Observed by CYGNSS Satellites

2021 ◽  
Vol 13 (11) ◽  
pp. 2032
Author(s):  
Junchan Lee ◽  
Sunil Bisnath ◽  
Regina S.K. Lee ◽  
Narin Gavili Kilane
Keyword(s):  
Dielectric Constant ◽  
Soil Moisture ◽  
Global Navigation Satellite System ◽  
Measurement Data ◽  
Satellite System ◽  
Computation Method ◽  
Navigation Satellite ◽  
Local Soil ◽  
Global Navigation ◽  
Global Navigation Satellite

This paper describes a computation method for obtaining dielectric constant using Global Navigation Satellite System reflectometry (GNSS-R) products. Dielectric constant is a crucial component in the soil moisture retrieval process using reflected GNSS signals. The reflectivity for circular polarized signals is combined with the dielectric constant equation that is used for radiometer observations. Data from the Cyclone Global Navigation Satellite System (CYGNSS) mission, an eight-nanosatellite constellation for GNSS-R, are used for computing dielectric constant. Data from the Soil Moisture Active Passive (SMAP) mission are used to measure the soil moisture through its radiometer, and they are considered as a reference to confirm the accuracy of the new dielectric constant calculation method. The analyzed locations have been chosen that correspond to sites used for the calibration and validation of the SMAP soil moisture product using in-situ measurement data. The retrieved results, especially in the case of a specular point around Yanco, Australia, show that the estimated results track closely to the soil moisture results, and the Root Mean Square Error (RMSE) in the estimated dielectric constant is approximately 5.73. Similar results can be obtained when the specular point is located near the Texas Soil Moisture Network (TxSON), USA. These results indicate that the analysis procedure is well-defined, and it lays the foundation for obtaining quantitative soil moisture content using the GNSS reflectometry results. Future work will include applying the computation product to determine the characteristics that will allow for the separation of coherent and incoherent signals in delay Doppler maps, as well as to develop local soil moisture models.

scholarly journals Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

2018 ◽  
Vol 10 (8) ◽  
pp. 1245 ◽  
Author(s):  
Mehrez Zribi ◽  
Erwan Motte ◽  
Nicolas Baghdadi ◽  
Frédéric Baup ◽  
Sylvia Dayau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Satellite System ◽  
Area Index ◽  
Vegetation Height ◽  
Study Sites ◽  
Global Navigation Satellite ◽  
Vegetation Characteristic ◽  
Agricultural Areas

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

scholarly journals Deriving surface soil moisture from reflected GNSS signal observations from a grassland site in southwestern France

2017 ◽  
Author(s):  
Sibo Zhang ◽  
Jean-Christophe Calvet ◽  
José Darrozes ◽  
Nicolas Roussel ◽  
Frédéric Frappart ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Land Surface ◽  
Land Surface Model ◽  
Ground Surface ◽  
Satellite System ◽  
Surface Model ◽  
Global Navigation Satellite ◽  
Grassland Site

Abstract. This work aims to assess the estimation of surface volumetric soil moisture (VSM) using the Global Navigation Satellite System Interferometric Reflectometry (GNSS-IR) technique. Year-round observations were acquired from a grassland site in southwestern France using an antenna consecutively placed at two contrasting heights above the ground surface (3.3 or 29.4 m). The VSM retrievals are compared with two independent reference datasets: in situ observations of soil moisture, and numerical simulations of soil moisture and vegetation biomass from the ISBA (Interactions between Soil, Biosphere and Atmosphere) land surface model. Scaled VSM estimates can be retrieved throughout the year removing vegetation effects by the separation of growth and senescence periods and by the filtering of the GNSS-IR observations that are most affected by vegetation. Antenna height has no significant impact on the quality of VSM estimates. Comparisons between the VSM GNSS-IR retrievals and the in situ VSM observations at a depth of 5 cm show a good agreement (R2 = 0.86 and RMSE = 0.04 m3 m−3). It is shown that the signal is sensitive to the grass litter water content and that this effect triggers differences between VSM retrievals and in situ VSM observations at depths of 1 cm and 5 cm, especially during light rainfall events.

Spaceborne GNSS Reflectometry for soil moisture using data from CYGNSS mission: results in the Contiguous United States

2021 ◽  
Author(s):  
Paulo de Tarso Setti Junior ◽  
Tonie van Dam
Keyword(s):  
United States ◽  
Soil Moisture ◽  
Optical Depth ◽  
Roughness Coefficient ◽  
Navigation Satellite ◽  
Gnss Reflectometry ◽  
Surface Reflectivity ◽  
Global Navigation ◽  
Global Navigation Satellite

<p>Soil moisture is an essential climate variable, influencing geophysical and hydrological processes such as vegetation and agriculture, land-atmosphere circulation, and drought development. It is possible to remotely sense soil moisture based on the dielectric constant of soil at microwave frequencies. Low earth orbit (LEO) satellites are capable of receiving Global Navigation Satellite Systems (GNSS) signals reflected off the surface of the Earth to infer properties of the reflecting surface itself, in a technique known as GNSS-Reflectometry (GNSS-R). However, converting surface reflectivity derived from GNSS-R into soil moisture is not straightforward. Reflectivity is influenced by other factors such as the vegetation optical depth and the soil roughness around the specular reflection. The Cyclone Global Navigation Satellite System (CYGNSS) is a mission from the National Aeronautics and Space Administration (NASA) consisting of eight small GNSS-R satellites with the primary objective of measuring wind speed in hurricanes and tropical cyclones. The satellites were launched in December 2016 in a 35° inclination orbit, and the measurements are made of reflected Global Positioning System (GPS) L1 (1.575 GHz) navigation signals. Reflections over land can be used to estimate soil moisture in the upper 5 cm of soil surface if they are correctly treated and modelled. In this work, we use three years of observations from CYGNSS mission (March 2017 - March 2020) to compute surface reflectivity over land assuming coherent reflections. Using linear regression models and ancillary information from Soil Moisture Active Passive (SMAP) mission (soil moisture, vegetation optical depth, and roughness coefficient), these reflectivity observations are then used to estimate soil moisture. Retrievals are compared with observations from 44 in-situ soil moisture stations from the International Soil Moisture Network (ISMN) in the Contiguous United States (CONUS), presenting in most of the cases a good agreement. Results are also correlated with vegetation optical depth, surface roughness, and topographic relief around the in-situ stations. In addition, some challenges regarding soil moisture estimation using spaceborne GNSS-R data are presented and discussed.</p>

scholarly journals Quality Improvement of Satellite Soil Moisture Products by Fusing with In-Situ Measurements and GNSS-R Estimates in the Western Continental U.S.

2018 ◽  
Vol 10 (9) ◽  
pp. 1351 ◽  
Author(s):  
Hongzhang Xu ◽  
Qiangqiang Yuan ◽  
Tongwen Li ◽  
Huanfeng Shen ◽  
Liangpei Zhang ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Water Cycle ◽  
Satellite System ◽  
Global Scale ◽  
Generalized Regression Neural Network ◽  
Level 3 ◽  
Global Navigation Satellite ◽  
Microwave Sensors ◽  
Surface Fusion

Soil moisture is a key component of the water cycle budget. Sensing soil moisture using microwave sensors onboard satellites is an effective way to retrieve surface soil moisture (SSM) at a global scale, but the retrieval accuracy in some regions is inadequate due to the complicated factors influencing the general retrieval process. On the other hand, monitoring soil moisture directly through in-situ devices is capable of providing high-accuracy SSM measurements, but the distribution of such stations is sparse. Recently, the Global Navigation Satellite System interferometric Reflectometry (GNSS-R) method was used to derive field-scale SSM, which can serve as a supplement to contemporary sparse in-situ soil moisture networks. On this basis, it is of great research significance to explore the fusion of these different kinds of SSM data, so as to improve the present satellite SSM products with regard to their data accuracy. In this paper, a multi-source point-surface fusion method based on the generalized regression neural network (GRNN) model is applied to fuse the Soil Moisture Active Passive (SMAP) Level 3 radiometer SSM daily product with in-situ measured and GNSS-R estimated SSM data from five soil moisture networks in the western continental U.S. The results show that the GRNN model obtains a fairly good performance, with a cross-validation R value of approximately 0.9 and a ubRMSE of 0.044 cm3 cm−3. Furthermore, the fused SSM product agrees well with the site-specific SSM data in terms of time and space, which demonstrates that the proposed GRNN model is able to construct the non-linear relationship between the point- and surface-scale SSM.

scholarly journals Detecting Targets above the Earth’s Surface Using GNSS-R Delay Doppler Maps: Results from TDS-1

2019 ◽  
Vol 11 (19) ◽  
pp. 2327 ◽  
Author(s):  
Changjiang Hu ◽  
Craig Benson ◽  
Hyuk Park ◽  
Adriano Camps ◽  
Li Qiao ◽  
...  
Keyword(s):  
Specular Reflection ◽  
Satellite System ◽  
Low Earth Orbit ◽  
Earth Orbit ◽  
Navigation Satellite ◽  
Reflection Point ◽  
Leo Satellites ◽  
Gnss Reflectometry ◽  
Global Navigation Satellite ◽  
Remotely Sense

Global Navigation Satellite System (GNSS) reflected signals can be used to remotely sense the Earth’s surface, known as GNSS reflectometry (GNSS-R). The GNSS-R technique has been applied to numerous areas, such as the retrieval of wind speed, and the detection of Earth surface objects. This work proposes a new application of GNSS-R, namely to detect objects above the Earth’s surface, such as low Earth orbit (LEO) satellites. To discuss its feasibility, 14 delay Doppler maps (DDMs) are first presented which contain unusually bright reflected signals as delays shorter than the specular reflection point over the Earth’s surface. Then, seven possible causes of these anomalies are analysed, reaching the conclusion that the anomalies are likely due to the signals being reflected from objects above the Earth’s surface. Next, the positions of the objects are calculated using the delay and Doppler information, and an appropriate geometry assumption. After that, suspect satellite objects are searched in the satellite database from Union of Concerned Scientists (UCS). Finally, three objects have been found to match the delay and Doppler conditions. In the absence of other reasons for these anomalies, GNSS-R could potentially be used to detect some objects above the Earth’s surface.

scholarly journals Derivation of global ionospheric Sporadic E critical frequency ( f o Es) data from the amplitude variations in GPS/GNSS radio occultations

2020 ◽  
Vol 7 (7) ◽  
pp. 200320 ◽  
Author(s):  
Bingkun Yu ◽  
Christopher J. Scott ◽  
Xianghui Xue ◽  
Xinan Yue ◽  
Xiankang Dou
Keyword(s):  
Critical Frequency ◽  
Detection Threshold ◽  
Low Frequency ◽  
Satellite System ◽  
Global Scale ◽  
Satellite Mission ◽  
Frequency Detection ◽  
Sporadic E ◽  
The Uk ◽  
Global Navigation Satellite

The ionospheric sporadic E (Es) layer has a significant impact on the global positioning system (GPS)/global navigation satellite system (GNSS) signals. These influences on the GPS/GNSS signals can also be used to study the occurrence and characteristics of the Es layer on a global scale. In this paper, 5.8 million radio occultation (RO) profiles from the FORMOSAT-3/COSMIC satellite mission and ground-based observations of Es layers recorded by 25 ionospheric monitoring stations and held at the UK Solar System Data Centre at the Rutherford Appleton Laboratory and the Chinese Meridian Project were used to derive the hourly Es critical frequency ( f o Es) data. The global distribution of f o Es with a high spatial resolution shows a strong seasonal variation in f o Es with a summer maximum exceeding 4.0 MHz and a winter minimum between 2.0 and 2.5 MHz. The GPS/GNSS RO technique is an important tool that can provide global estimates of Es layers, augmenting the limited coverage and low-frequency detection threshold of ground-based instruments. Attention should be paid to small f o Es values from ionosondes near the instrumental detection limits corresponding to minimum frequencies in the range 1.28–1.60 MHz.

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