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Because of the sub-meter spatial resolution of very high resolution (VHR) optical satellite imagery, vehicles can be identified in this type of imagery. Further, because there is a time lag in image collection between the Panchromatic (Pan) and multispectral (MS) sensors onboard VHR satellites, a moving vehicle is observed by the satellite at slightly different times. Consequently, its velocity information including speed and direction can be determined. The higher spatial resolution and more spectral bands of WorldView-2 (WV2) imagery, compared to those of previous VHR satellites such as QuickBird and GeoEye-1, together with the new sensors' configuration of WV2, i.e., 4 bands on each side of the Pan sensor (MS1 and MS2), adds an opportunity to improve both moving vehicles extraction and the velocity estimation. In this paper, a novel processing framework is proposed for the automatic extraction of moving vehicles and determination of their velocities using single-pass WV2 imagery. The approach contains three major components: a) object-based road extraction, b) moving vehicle extraction from MS1 and MS2, and c) velocity estimation. The method was tested on two different areas of a WV2 image, a high speed and a low speed traffic zone. The method resulted in a correctness of 92% and a completeness of 77% for the extraction of moving vehicles. Furthermore, the estimated speeds and directions are very realistic and are consistent with the speed limits posted on the roads. The results demonstrate a promising potential for automatic and accurate traffic monitoring using a single image of WV2.