Xuerui Wu

Validating the Variability of Snow Accumulation and Melting From GPS-Reflected Signals: Forward Modeling

The variability of snow accumulation and melting is one of the most important interactions of the Earths surface with atmosphere through energy transmission and mass balance. In this paper, the effects of snow accumulation and melting together with bare soil and fixed snow depth on the reflected global positioning system (GPS) signals are investigated using GPS antenna gains and multipath signal. The reflected GPS signals are modeled and employed to analyze the interactions of snow accumulation, snow melting, bare soil, and fixed snow depth at BAKE and KUUJ GPS stations in Northern Canada. The results show the clear independency of the snow accumulation and melting variations with bare soil and fixed snow depth, which are validated from GPS-reflected signals as well. The modeled reflected GPS signals indicate the higher frequency of snow accumulation and snow melting than that of bare soil and fixed snow depth, while the estimated power spectral density of the GPS-reflected signals shows the higher signal power of coherence function difference. Furthermore, the GPS observations at BAKE and KUUJ sites confirm such variations with a good agreement during the snow accumulation, melting, bare soil, and fixed snow depth on the ground.

Can we monitor the bare soil freeze-thaw process using GNSS-R?: a simulation study

GNSS-R has recently emerged as a new prosperous remote sensing tool in ocean surface, snow/ice surface and land surface. In this paper, the possible application in sensing the bare soil freeze-thaw process is investigated with GNSS-R. The Fresnel reflectivity from the wave synthesis technique is used to get the circular polarization reflectivity. Large differences are found for the Fresnel reflectivities at V, H, RR polarizations during bare soil freeze-thaw process, but there are almost no differences as for LR polarization. Therefore if a special GNSS-R receiver is designed, the reflected signals of RR polarization should be efficiently used. For GPS multipath reflectometry, the improved Fresnel reflectivity is inserted into the fully polarimetric forward multipath model to get the simulated GPS L1 observables: SNR, carrier phase multipath error and pseudorange code multipath error, which are used to estimate the bare soil freeze-thaw process. Compared to the thawed soil, the amplitudes of GPS observables are smaller for the frozen soil. Therefore, it is possible to monitor bare soil freeze-thaw process with ground geodetic GPS receivers.

A multipath forward scattering model of GNSS-Reflectometry from bare soil and vegetation

In the past two decades, GNSS-R (Global Navigation Satellite System-Reflectometry) has been emerged as a new kind of microwave remote sensing technique. The reflected signals of the GNSS constellations and the direct ones form the typical bistatic or multi-static radar working mode. While, for one side, a new kind of special GNSS-R receivers should be developed to enhance the reflected signals. For the other side, the traditional off-the-shelf geodetic GPS receivers can be used. For the latter ones, their observations contain the interference signals of the direct and reflected signals. The reflected signals as multipath can be used for the detections of the interested geophysical parameters after removing or eliminating the direct signals. However, nowadays, the popular multipath estimations are either empirical ones or focusing on the code modulations, which are not adequate for the physical explanations of the multipath interactions, especially for GNSS-R applications. This paper focuses on developing the physical forward multipath single-scattering model, which is a fully polarimetric forward model. Since the scattering properties of the reflected surface are one of the most important factors for the multipath, it is necessary to develop the surface scattering model for the forward multipath model. However, for the circular polarization properties, the calculation of the original Fresnel coefficient is substituted by the specular reflectivity model, so not only the magnitudes are changed, but also the phase differences are changed. Here, the wave synthesis technique is used to calculate the circular polarization. Dielectric constants of soil are calculated using the semi-empirical model. The surface coherent scattering model is added into the forward multipath model. The default input parameters of the antenna and receivers are used. As for low vegetation, the bistatic scattering model based on the first-order radiative transfer equation model is replaced with the original Fresnel reflectivity and inserted into the forward multipath simulator. Comparisons of GPS observables for bare soil and wheat are also done. The oscillations and the final simulated multipath signals and their dynamic ranges are all acceptable. The amplitudes of GPS observables for wheat-covered surface are lower than bare soil for smaller elevation angles(<;30°) and they become larger while the elevation angles are larger(>30°). Theoretical modeling of the GPS multipath signals shows that it can be an efficient tool for the interpretation of GNSS-R measurements.

Theoretical study on GNSS-R vegetation biomass

GNSS-R(Global Navigation Satellite System-Reflectometry) remote sensing has been attracted much more attention during the past decade. As for land scenario, soil moisture and vegetation properties are the research priorities. This paper focuses on the initial study of GNSSR vegetation biomass using the already developed microwave scattering model Bi-mimics (Bistatic-Michigan Microwave Canopy Scattering). After some modifications, forest and crop specular simulations indicate that as for GNSS-R configuration, vegetation biomass monitoring is feasible, RL and RV polarization scattering properties are influenced by vegetation types, scattering angles and polarizations. It is a complex process and theoretical simulations provide some suggestions for GNSS-R vegetation remote sensing.

GNSS-R reflected signals polarization characteristics: Theoretical study on vegetation remote sensing

GNSS-R remote sensing has been attracted much attention during the past few years due to its unique advantages. Meanwhile, its receivers and signal processors have been improved. However, some ambiguities still exit. Receivers elevation angles and antenna polarizations are the important effects for geophysical parameters monitoring and retrievals. This paper uses the microwave scattering model to do some research on GNSS-R vegetation polarizations. The already developed bistatic scattering model Bi-mimics is used as the study tool. After some modifications, any polarization combination is able to be calculated. As for GNSS-R, RHCP signal is transmitted and linear or circular polarization signals are received. Aspen is used as model input. Theoretical analysis indicates that antenna polarization should be paid more attention as for different applications. Further study need to be done in the future.

A Forward GPS Multipath Simulator Based on the Vegetation Radiative Transfer Equation Model

Global Navigation Satellite Systems (GNSS) have been widely used in navigation, positioning and timing. Nowadays, the multipath errors may be re-utilized for the remote sensing of geophysical parameters (soil moisture, vegetation and snow depth), i.e., GPS-Multipath Reflectometry (GPS-MR). However, bistatic scattering properties and the relation between GPS observables and geophysical parameters are not clear, e.g., vegetation. In this paper, a new element on bistatic scattering properties of vegetation is incorporated into the traditional GPS-MR model. This new element is the first-order radiative transfer equation model. The new forward GPS multipath simulator is able to explicitly link the vegetation parameters with GPS multipath observables (signal-to-noise-ratio (SNR), code pseudorange and carrier phase observables). The trunk layer and its corresponding scattering mechanisms are ignored since GPS-MR is not suitable for high forest monitoring due to the coherence of direct and reflected signals. Based on this new model, the developed simulator can present how the GPS signals (L1 and L2 carrier frequencies, C/A, P(Y) and L2C modulations) are transmitted (scattered and absorbed) through vegetation medium and received by GPS receivers. Simulation results show that the wheat will decrease the amplitudes of GPS multipath observables (SNR, phase and code), if we increase the vegetation moisture contents or the scatters sizes (stem or leaf). Although the Specular-Ground component dominates the total specular scattering, vegetation covered ground soil moisture has almost no effects on the final multipath signatures. Our simulated results are consistent with previous results for environmental parameter detections by GPS-MR.

Monitoring Bare Soil Freeze–Thaw Process Using GPS-Interferometric Reflectometry: Simulation and Validation

Frozen soil and permafrost affect ecosystem diversity and productivity as well as global energy and water cycles. Although some space-based Radar techniques or ground-based sensors can monitor frozen soil and permafrost variations, there are some shortcomings and challenges. For the first time, we use GPS-Interferometric Reflectometry (GPS-IR) to monitor and investigate the bare soil freeze–thaw process as a new remote sensing tool. The mixed-texture permittivity models are employed to calculate the frozen and thawed soil permittivities. When the soil freeze/thaw process occurs, there is an abrupt change in the soil permittivity, which will result in soil scattering variations. The corresponding theoretical simulation results from the forward GPS multipath simulator show variations of GPS multipath observables. As for the in-situ measurements, virtual bistatic radar is employed to simplify the analysis. Within the GPS-IR spatial resolution, one SNOTEL site (ID 958) and one corresponding PBO (plate boundary observatory) GPS site (AB33) are used for analysis. In 2011, two representative days (frozen soil on Doy of Year (DOY) 318 and thawed soil on DOY 322) show the SNR changes of phase and amplitude. The GPS site and the corresponding SNOTEL site in four different years are analyzed for comparisons. When the soil freeze/thaw process occurred and no confounding snow depth and soil moisture effects existed, it exhibited a good absolute correlation (|R| = 0.72 in 2009, |R| = 0.902 in 2012, |R| = 0.646 in 2013, and |R| = 0.7017 in 2014) with the average detrended SNR data. Our theoretical simulation and experimental results demonstrate that GPS-IR has potential for monitoring the bare soil temperature during the soil freeze–thaw process, while more test works should be done in the future. GNSS-R polarimetry is also discussed as an option for detection. More retrieval work about elevation and polarization combinations are the focus of future development.

Theoretical Study for Bare Soil Freeze/Thaw Process Detection Using GNSS-R/MR

GNSS-R remote sensing has emerged as a new promising remote sensing technique in the past two decades. It has gained wide attention at home and abroad. In essential, GNSS-R is a bistatic radar, the signals got by the GNSS-R receiver is delay Doppler map. Different from the specially designed receivers, the geodetic quality GPS receiver can be used to remotely sense the near surface soil moisture, vegetation growth and snow depth, i.e. GNSS-Multipath reflectometry (GNSS-MR). Three metrics, i.e. effective reflector height, phase and amplitude, are employed for retrieval. As for the applications of space-borne/air-borne GNSS-R or ground based GNSS-IR techniques, they include soil moisture, vegetation growth and snow depth retrieval. This paper has extended the bare soil freeze/thaw process detection, the theoretical fundamentals is that when the soil frozen/thawn process occurs, there is a big difference for the soil permittivity, which will result in the difference of reflectivities. The dielectric mixing models are employed for the calculations of the frozen/thawn soil permittivities, which are the inputs for the reflectivity models, the coherent scattering model and the random surface scattering models are employed for the calculation of specular scattering reflectivities and the diffuse scattering reflectivities, respectively. When the soil freeze/thaw process has occurred, the corresponding GPS multipath changes and the variations of delay Doppler map are simulated. The theoretical simulations indicate that the big difference of permittivity will result in the apparent changes of GPS multipath observables and delay Doppler map. It has been demonstrated in theory that the bare soil freeze/thaw process can be detected by the GNSS-R or GNSS-MR techniques.

Initial results for near surface soil freeze-thaw process detection using GPS-Interferometric Reflectometry

The geodetic-quality GPS receivers can be used for geophysical parameters retrieval, i.e. soil moisture, vegetation growth and snow depth, and it is called GPS-Interferometric Reflectometry (GPS-IR) remote sensing. In this paper, to detect the near surface soil freeze-thaw process using GPS-IR is evaluated for the first time. When the soil changes from frozen state to thawn state, the corresponding permittivities and reflectivities at RR, LR, VR and HR pol are changed. Triple-frequency effects are evaluated, for different frequencies, the modulations for SNR data are not the same, but within L-band, the observed surface has almost the same reflected properties (e.g. GPS L1 band, L2band and L5band). A GPS site in the EarthScope Plate Boundary Observatory (PBO) and a corresponding soil climate site in SCAN (Soil Climate Analysis Network) is used to examine the potential for near surface soil freeze-thaw process detection. Two representative days and a time series of SNR data show strong correlation with near surface soil temperature. Our initial results demonstrate that GPS-IR has the potential for bare soil freeze-thaw detection. Therefore, the new low-cost bare soil freeze-thaw monitoring networks are expected from geodetic GNSS network.

Snow depth variations estimated from three-frequency GPS interferometric reflectometry

Nowadays, GPS multipath can be used to estimate snow depth, soil moisture and vegetation growth using signal-noise to radio (SNR) data. Particularly with the modernization of GPS, one new signal, called L5, has been broadcasted by Block IIF satellites, the combination of three-frequency (L1, L2 and L5) observations may help remove the ionospheric delay errors and obtain better multipath signals. In this paper, the pseudorange and phase multipath are extracted from three-frequency GPS pseudorange and phase combinations at GANP station in Slovakia with available co-located snow data, which are used to estimate snow depth variations based on the GPS Multipath Refletometry (GPS-MR) theory. Snow depth estimations from three-frequency GPS pseudorange combinations are compared with in-situ observations, which shows a correlation of 0.83 and RMSE of 0.11m, while results from three-frequency GPS phase combinations have a little better correlation of 0.86 and RMSE of 0.08m. However, the results from dual-frequency (L1 and L2) combinations have a much lower correlation of 0.64 and larger RMSE of 0.16m. Therefore, it is better to estimate snow depth using three-frequency combinations than double-frequency measurements.