Abstract. Recently, GNSS Reflectometry (GNSS-R) has gained increasing attention for remote sensing and hydrological applications, particularly in monitoring soil moisture and vegetation status. As a novel bi-static radar technique, GNSS-R utilizes GNSS signals (e.g., GPS) reflected off the Earth’s surface, which carry valuable information about surface conditions. However, applying this technique to remote sensing is not straightforward, as GNSS-R observations are influenced by several factors, including instrumental and geometrical parameters. This paper aims to demonstrate the sensitivity of NASA’s GNSS-R mission, Cyclone GNSS (CYGNSS), to soil moisture variations and to investigate the influence of vegetation status—using vegetation water content (VWC), Leaf Area Index (LAI) and canopy height as indicators—soil surface roughness, and incidence angle on these observations. Our results show good agreement between CYGNSS observations and SMAP soil moisture, with sensitivity decreasing at larger incidence angles (60–70°) and higher VWC (dense vegetation). Additionally, CYGNSS reflectivity exhibits a strong negative correlation with vegetation indicators, including VWC (R ≈ –0.8), LAI (R = –0.9346), and canopy height (R = –0.9795), highlighting its effectiveness in monitoring vegetation status. This negative correlation, along with the observed strong negative correlation coefficients (≤ –0.8) between CYGNSS reflectivity and the SMAP-provided surface roughness parameter (Hr), confirms the attenuation of microwave signals caused by dense vegetation and soil surface roughness.
Rahmani et al. (Fri,) studied this question.