Small rotorcraft unmanned air vehicles (sUAVs) are valuable tools in solving geospatial inspection challenges. One area where this is being widely explored is disaster reconnaissance [ 1 ]. Using sUAVs to collect images provides engineers and government officials critical information about the conditions before and after a disaster [ 2 ]. This is accomplished by creating high- fidelity 3D models from the sUAV’s imagery. However, using an sUAV to perform inspections is a challenging task due to constraints on the vehicle’s flight time, computational power, and data storage capabilities [ 3 ]. The approach presented in this article illustrates a method for utilizing multiple sUAVs to inspect a disaster region and merge the separate data into a single high-resolution 3D model.