Abstract: Objectives： The Normalized Difference Vegetation Index (NDVI) is one of the important parameters for monitoring vegetation changes. With the continuous development of the Global Navigation Satellite System (GNSS), GNSS interferometry reflectometry (GNSS-IR) technology has been proven to have the potential for monitoring vegetation changes. This paper aims to explore the correlation between NDVI and the normalized amplitude (A_norm) and normalized microwave reflectance index (NMRI) obtained from GNSS interferometry reflectometry to assess the application potential of GNSS signals in vegetation monitoring. Methods: The study used GNSS signal-to-noise ratio (SNR) data to calculate A_norm and NMRI, analyzing their correlation with NDVI and change trends. In addition, total precipitation data from the fifth generation reanalysis dataset (ERA5) released by the European Centre for Medium-Range Weather Forecasts (ECMWF) and drought severity data were utilized to explore the relationship between precipitation/drought and A_norm and NMRI. Further analysis was conducted on the correlation between NMRI parameters at different frequency points under the GPS, GLONASS, and Galileo systems and NDVI. Results: Analysis of experimental data from three Plate Boundary Observatory (PBO) sites (P042, P052, and P675) revealed strong linear correlations between A_norm and NDVI, as well as between NMRI and NDVI, with correlation coefficients ranging from 0.58 to 0.86. When the surrounding vegetation types were grassland and crops, NMRI at different frequency points across all three GNSS systems demonstrated good correspondence with NDVI. Notably, among the three frequency bands, the L1-band NMRI exhibited the strongest correlation with NDVI, with coefficients ranging from 0.46 to 0.89, which may be attributed to the shortest wavelength of the L1 signal. Conclusions: The study demonstrates that multi-constellation and multi-frequency GNSS signals can effectively monitor vegetation indices, validating the application potential of GNSS interferometry reflectometry technology in monitoring vegetation changes and providing important data support for future research.