# Recent Progress on Vegetation Remote Sensing Using Spaceborne GNSS-Reflectometry
## 2 Research Status
### Theoretical Model Research
Three main contributions of the received complex field can be calculated,the first one is the direct term, which is the shortest path between antennas, while the second one is the scattering properties along the specular direction. The last term is the diffuse scattered wave and it can account for both antenna and scene characteristics. This model can be oriented to the P-band SoOP-R and L-band GNSS-R. However, experiment validations are not carried out during their work. In order to illustrate the usefulness of this mode for interpretation of field data, they employed tree canopies at P-band and presented an analysis of polarimetric specular and diffuse contributions to bistatic scattering in detail. Empirical results over boreal forests from a stratospheric balloon suggested that the coherent scattering term is roughly independent of the platform's height [30]. The EMISVEG simulator further analyzed this hypothesis [47; 48]. Lindenmayer systems were used to generate fractal geometry and the Foldy's approximation was used to account for attenuation and phase change of the coherent wave propagating in the forest media. EMISVEG uses signals at RHCP and LHCP. In the model, the tree components are located above the dielectric rough plane, which is assumed to be illuminated by the electromagnetic field. Branches and tree trunks are modeled by stratified dielectric cylinders, while the leaves are modeled by dielectric needles [47; 48]. In [PERSON] et al. 's work, they have employed the EMISVEG simulator to discuss their experiment results [49]. The article has presented a spaceborne GNSS-R end-to-end simulator that is oriented to land surface [50]. The simulator is an extension of the previous ocean simulator. However, the new land surface simulator is very generic and it includes the detail observation geometry, arbitrary GPS, and Galileo transmitted signals and frequencies, GNSS-R instrument antenna, and receiver errors. Meanwhile, more detailed information of the surface parameters, such as topography, surface roughness, soil moisture, vegetation cover, have also been included in the new developed simulator. Their results are compared with the TDS-1 DDMs for four different cases. The peak values of the simulated DDM are consistent with the TDS-1 DDMs. [PERSON] et al. focused on using the vegetation first-order radiation transfer equation model to study the polarization characteristics of different canopies [51; 52; 53]. It is worth noting that the traditional first-order radiation transfer equation model mainly focuses on the linear polarization of monostatic-radar or radiometers to study the backscattering or radiation characteristics [54]. [PERSON] et al. have employed its bistatic scattering and full-polarization characteristics to describe in more detail the bistatic scattering characteristics of different vegetation when the observation geometry and polarization characteristics change [51]. In their work, the polarization synthesis method is employed to calculate the scattering characteristics of various polarizations including circular polarization. When the transmitted signals are RHCP, the received signals are circular polarization (RHCP and LHCP) and linear polarization (horizontal polarization and vertical polarization), and the corresponding scattering characteristics are simulated. At the same time, the article also compares and analyzes the linear polarization scattering characteristics and the circular polarization scattering. The scattering difference in polarization puts forward a new direction of using polarization characteristics for GNSS-R land surface remote sensing monitoring. This is because the backscattering model has been verified by measured data, and the in-situ measurement data of bistatic radar limit the feasibility of its data verification. Therefore, the author verified the reliability of the developed model in the bistatic and full-polarization scattering characteristics through the method of \"model verification model\" [51; 52; 53].