AbstractGlobal navigation satellite system interferometric reflectometry (GNSS-IR) is a new remote sensing method that has shown great potential for estimating soil moisture variation and vegetation growth in the vicinity of GNSS sites. Various retrieval methods have been proposed, and the accuracy of the retrieval results are continually improving. However, few experiments have comprehensively evaluated the potential of the BeiDou Navigation Satellite System (BDS) to retrieve soil moisture and vegetation growth in a farmland environment, especially the vegetation height. In this study, volumetric soil moisture (VSM) variation and wheat growth were retrieved from BDS B1/B2/B3 and Global Positioning System (GPS) L1/L2 signal-to-noise ratio (SNR) data collected from a wheat farm in Zhangxizhuang, Beijing, and evaluated by comparison with in situ observations. VSM was retrieved before significant wheat growth and after wheat harvest, wheat growth was retrieved in the remaining period, and traditional, empirical mode decomposition (EMD), and wavelet algorithms were used to estimate the optimal wheat height change process. The experimental results show that the root-mean-square error (RMSE) between GPS L1/L2 and BDS B1/B2/B3 frequencies in VSM retrieval and in situ VSM is 0.039 and 0.035 and 0.027, 0.022, and 0.021 m3·m−3, respectively. Moreover, the negative normalized amplitude exhibits a good correlation with the normalized difference vegetation index (NDVI) during high wheat coverage (R=0.67). The GNSS-derived wheat height is consistent with the in situ wheat height change, and the retrieval value perfectly reflects the process of the wheat crop height changing rapidly to relatively stable and then to harvest. Thus, GNSS-IR technology has excellent capability and potential for monitoring farmland VSM and vegetation growth.