Abstract
Soil moisture is the most active part of the terrestrial water cycle, and it is a key variable that affects hydrological, bio-ecological, and bio-geochemical processes. Microwave remote sensing is an effective means of monitoring soil moisture, but the existing conventional radiometers and single-station radars cannot meet the scientific needs in terms of temporal and spatial resolution. The emergence of GNSS-R (Global Navigation Satellite Systems Reflectometry) technology provides an alternative method with high temporal and spatial resolution. An important application field of GNSS-R is soil moisture monitoring, but it is still in the initial stage of research, and there are many uncertainties and open issues. Based on a review of the current state-of-the-art of soil moisture retrieval using GNSS-R, this paper points out the limitations of existing research in observation geometry, polarization, and coherent and non-coherent scattering. The smooth surface reflectivity model, the random rough surface scattering model, and the first-order radiation transfer equation model of the vegetation, which are in the form of bistatic and full polarization, are employed. Simulations and analyses of polarization, observation geometry (scattering zenith angle and scattering azimuth angle), Brewster angle, coherent and non-coherent component, surface roughness, and vegetation effects are carried out. The influence of the EIRP (Effective Isotropic Radiated Power) and the RFI (Radio Frequency Interference) on soil moisture retrieval is briefly discussed. Several important development directions for space-borne GNSS-R soil moisture retrieval are pointed out in detail based on the microwave scattering model.
Highlights
Introduction affiliationsSoil moisture refers to the water content of the unsaturated layer of soil
There is a linear correlation between CYGNSS reflectivity and SMAP soil moisture
VR polarization scattering grooves will appear at the Brewster angle, making full use of its information that can effectively remove the influence of roughness and vegetation effects
Summary
The available spaceborne GNSS-R programs for soil moisture detection mainly include. UK-DMC, TDS-1, and CYGNSS. The parameter of interest is the peak energy of the Delay-Doppler Map (DDM), which is affected by the nature of the reflecting surface, and by the antenna gain, the transmitter and receiver ranges, and the incidence angle, as shown in [26] as: Pr,e f f ∝ PrdB − NdB + ( Rsr + Rts )2dB − GrdB + cos θdB (1). In this equation, Pr,e f f is the effective reflected energy, i.e., the signal-to-noise ratio (SNR) of the DDM. Soil roughness and vegetation strongly affect the accuracy of the soil moisture estimates but, if these effects can be effectively solved, the resulting products can become a very valuable data-set at a high temporal and spatial resolution
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