The strong attenuation and scattering of vegetation make the inversion of soil moisture difficult. However, the vegetation biomass plays an important role in carbon cycling and greenhouse effect monitoring. Compared with traditional active and passive remote sensing technologies, such as SAR and radiometric measurement technology, GNSS-R technology has unique advantages such as small size, light weight, low energy consumption, and high spatiotemporal resolution, which provides a new technology for environmental remote sensing. Currently, a number of institutions and researchers are conducting studies on GNSS-R vegetation remote sensing using qualitative analysis methods. Rodriguez-Alvarez et al. [1, 2] have been using ground-based SMIGOL-reflectometer (Soil Moisture Interference Pattern GNSS Observations at L-band) for geophysical parameter inversion. Interference Pattern Technique (IPT) was developed to measure the changes in direct signals caused by multipath effects generated by reflected interference signals. The minimum amplitude is called a notch, and its number and position are functions of soil moisture and vegetation height [1, 2]. Small et al. [3] have been using GNSS multipath to qualitatively estimate the growth status of vegetation from the Plate Boundary Observatory (PBO) GNSS network and found that NDVI (Normalized Vegetation Index) was negatively correlated with multipath effect amplitude. Since the fewer GNSS observation stations are set up in forest areas, this method is only applicable to farmland, grassland, and shrubland.