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The acquisition of synchronous EO imagery and gamma radiation data in aerial overflights of an unmanned aircraft can provide valuable spatial context for radioactive source mapping. Using image-based 3D reconstruction methods, a terrain map can be generated and used to reason about more likely radiation source locations. For instance, vehicles may be likely hiding places for nuclear materials, so a source model with assigned probability is used at the vehicle to reduce the overall uncertainty in position estimation. Environment reconstructions based on EO imagery with a mapped gamma radiation overlay provide intrinsic correlations between the datasets. Using radioactive material dispersion models or point source models, the derived correlations serve to enhance coarse gamma radiation data. The use of autonomous unmanned aircraft provide a valuable tool in acquiring these data as they are capable of accurate and repeatable position control while eliminating exposure danger to the operators. In this experiment, two sources (.084 Ci 137Ce and .00048 Ci 133Ba) were distributed in a field with varying terrain and a scan was conducted using the Virginia Tech Yamaha RMAX autonomous helicopter equipped with a two-camera imaging system and a NaI scintillation-type spectrometer. Terrain reconstruction was conducted using both structure from motion (SfM) and stereo vision techniques, and radiation data synchronized to the imagery was overlaid.