This paper presents an assessment of the correlation between CyGNSS-derived global navigation satellite systems reflectometry (GNSS-R) bistatic reflectivity, ${\Gamma _{rl}}$ , and soil moisture active passive (SMAP) derived brightness temperature, $T{}_I/2$ , over land surfaces. This parametric study is performed as a function of soil moisture content (SMC), vegetation opacity $\tau $ , and albedo $\omega $ . Several target areas, classified according to the International Geosphere-Biosphere Program (IGBP) land cover types, are selected to evaluate potential differentiated geophysical effects on “active” (as many transmitters as navigation satellites are in view) and passive approaches. Although microwave radiometry has potentially a better sensitivity to SMC, the spatial resolution achievable from a spaceborne platform is poor, ∼40 km. On the other hand, GNSS-R bistatic coherent radar pixel-size is limited by half of the first Fresnel zone, which provides about ∼150 m of spatial resolution (depending on the geometry). The main objective of this “active”/passive combination is twofold: a) downscaling the SMC, b) complement the information of microwave radiometry with GNSS-R data to improve the accuracy in SMC determination. The Pearson linear correlation coefficient of ${\Gamma _{rl}}$ and $T{}_I/2$ obtained over Thailand, Argentinian Pampas, and Amazon is ∼−0.87, ∼−0.7, and ∼−0.26, respectively, while the so-called tau–omega model is used to fit the data. Results over croplands are quite promising and deserve special attention since the use of GNSS-R could benefit agricultural and hydrological applications because of: a) the high spatio-temporal sampling properties, b) the high spatial resolution, and c) the potential combination with microwave radiometry to improve the accuracy of the measurements.