Vegetation Growth Monitoring Based on BDS Interferometry Reflectometry With Triple-Frequency SNR Data

An emerging microwave remote sensing technology, global navigation satellite system interferometry reflectometry (GNSS-IR) shows the excellent application potential in vegetation remote sensing due to its all-weather and high temporal resolution characteristics. Previous studies for GNSS-IR have mainly concentrated on the global positioning system (GPS) signal-to-noise ratio (SNR) data. Because of the similarity between GPS and Beidou Navigation Satellite System (BDS), the signal of BDS can also be impacted by vegetation, which, however, has not been comprehensively researched. Therefore, this letter acquires the normalized amplitude of the BDS SNR data based on triple-frequency SNR observations collected by two stations with different vegetation types. To reveal the impact of different vegetation growth conditions on the BDS multifrequency signals, we conduct a comparative analysis with normalized difference vegetation index (NDVI) data obtained by Sentinel-2 and Moderate-Resolution Imaging Spectroradiometer (MODIS) imagery. The outcomes demonstrate that the normalized amplitude of the BDS signal exhibits a strong association with Sentinel-2 NDVI, with correlation coefficients varying from 0.69 to 0.83 and 0.78 to 0.84 at P041 and P105, respectively. In addition, it is the first time discovered that harvesting vegetation around the stations leads to a cliff-like decrease in normalized amplitude. Compared with optical remote sensing vegetation monitoring methods, BDS-IR shows significant temporal resolution and sensitivity advantages. This finding may promote vegetation monitoring, vegetation protection, and other related research fields.