Challenges in remote sensing, including remote sensing of vegetation, include the spectral characterization of objects over space and time. One key aspect for this characterization involves the geometry of data acquisition and positional relationships between light source, the target and the remote sensor. Several configurations of goniometers have been used to acquire spectral data as a function of this geometry and this strategy has been particularly efficient when applied to the study of short canopies (e.g., grasses). Tall canopies present logistical challenges when conducting these analyses, which can be resolved by replacing physical structures (rails) with flying systems capable to conform to different canopy geometries and data acquisition requirements. This work (the Droniometer Experiment) investigates anisotropies of a forest using radiometrically calibrated images from a multispectral camera (MicaSense RedEdge) mounted on a rotary-wing unmanned aerial system programmed to follow a planned flight that simulates data acquisition by a goniometer assembled over tall canopy. The experiment used multiple planned flights, conducted to represent changes in illumination, considering sun azimuth and elevation (multiple flights per day and over the course of months). Multi-angle data acquisition was addressed by controlling aircraft position and camera pitch at regular intervals. This work presents the integration of the droniometer system, including platform and camera requirements and control, data acquisition and processing, and analyses of results for target/vegetation characterization and to support information extraction and multi-angle remote sensing. A radiative transfer model, the Soil Canopy Observation, Photochemistry and Energy fluxes (SCOPE) was used for comparative analysis and to further describe anisotropies in spectral responses of tall canopies.