The canopy bidirectional reflectance distribution function (BRDF) plays a pivotal role in estimating the biophysical parameters of plants, whereas soil background anisotropy creates challenges for their retrieval. Soil optical properties affect canopy anisotropic characteristics, especially in open-canopy areas. However, the remote sensing of background anisotropy is challenging due to the difficulties of information extraction in complex forest ecosystems and varying illumination conditions. This study develops an efficient photogrammetric technique to extract the background soil bidirectional reflectance factor (BRF) from unmanned aerial vehicle (UAV)-based multiangular images and to verify the need for accurate soil anisotropy information in canopy radiative transfer modeling. Soil BRF profiles were measured over three open-canopy sample plots from multiangular remotely sensed multispectral images collected with a hexacopter. As validation, reference soil BRF profiles were synchronously acquired by a ground-based multiangular imaging system. A high level of consistency between the ground- and UAV-measured soil BRF was observed with an RMSE of less than 0.012. Uncertainty analysis of the measured soil BRF showed that multiple scattering between sunlit soil in large sunflecks and foliage elements contributed less than 5%. Both results demonstrated that soil anisotropy can be accurately extracted from UAV multiangular measurements. To explicitly demonstrate that the use of soil anisotropy can reduce uncertainties in canopy radiative transfer simulations, we simulated the canopy BRF with Lambertian soil and with anisotropic soil using a three-dimensional (3D) radiative transfer model under different soil moisture content (SMC) levels, canopy cover (CC) levels and solar zenith angles (SZAs) with simulated realistic forest scenes. We found that less CC, lower SZAs and less SMC lead to a more significant influence of soil anisotropy on canopy reflectance; e.g., the reflectance bias reaches up to 0.3 in the hotspot direction. This illustrates that neglecting soil anisotropy can cause considerable errors in the modeling of the canopy BRF of open forests (i.e., CC levels of less than 0.5). The proposed technique facilitates the characterization of anisotropic forest background soil, which is important for advancing canopy radiative transfer modeling and validation and for the retrieval of vegetation parameters.