Abstract. We demonstrate a method for unmanned aerial vehicle based structure from motion mapping and show it to be a viable option for large scale, high resolution terrain modeling. Current methods of large scale terrain modeling can be cost and time prohibitive. We present a method for integrating low cost cameras and unmanned aerial vehicles for the purpose of 3D terrain mapping. Using structure from motion, aerial images taken of the landscape can be reconstructed into 3D models of the terrain. This process is well suited for use on unmanned aerial vehicles due to the light weight and low cost of equipment. We discuss issues of ight path planning and propose an algorithm to assist in the generation of these paths. The structure from motion mapping process is experimentally evaluated in three distinct environments: ground based testing on man-made environments, ground based testing on natural environments, and airborne testing on natural environments. Ground based testing on natural environments was shown to be extremely useful for camera calibration, and the resulting models were found to have a maximum error of 4.26 cm and standard deviation of 1.50 cm. During airborne testing, several areas of approximately 30,000 m2 were mapped. These areas were mapped with acceptable accuracy and a resolution of 1.24 cm.