This paper describes the investigations carried out at ETH Zurich on the very-high resolution optical satellite sensor WorldView-1. The dataset includes a stereopair acquired in November 2007 over Morrison, Colorado, USA, consisting of a quasi-nadir scene with mean GSD close to 51cm and an off-nadir scene, with GSD up to 73cm. The radiometry of the images was evaluated through the estimation of the noise level (standard deviation of the digital number) in non-homogeneous areas. For the orientation of the scenes, we used ground control points to estimate the parameters of an affine transformation and improve the orientation related to the Rational Polynomial Coefficients (RPC) provided in the metadata files. The next step included the automatic DSM generation with quality assessment. In all our tests the matching and the final DSM generation was realized with our in-house software package SAT-PP (Satellite Image Precision Processing) which has already been successfully used for other satellite sensors like IKONOS, ALOS/PRISM, Cartosat-1 and airborne linear and frame cameras. For the evaluation of the potential of a WorldView-1 stereo image pair for DSM generation, reference data are fundamental. As no DSM with a suitable resolution was available in this dataset, we generated the reference DSM from 1:15¿000 scale infrared aerial images purchased from USGS. The aerial images were acquired in April 2002 with an analogue camera and scanned with a resolution of 14µm. No GCPs were available for the area covered by the aerial images. Therefore we defined a sufficient number of well-defined texture points in the oriented stereo pair of WorldView-1 as GCPs and determined their 3D coordinates using the orientation parameter of the satellite stereo pair. These points were used for the image orientation of the aerial images, which leads to a good relative orientation between the two different image sets. By this we investigated the quality of the matching process with WorldView-1 stereo image data mostly independent of the exterior orientation parameters. We will present here our accuracy assessment by visual and quantitative analysis (3D residuals distribution and statistics). The difference between the acquisition times of the two data sets (about 2.5 years) caused changes in the land cover, e.g. in correspondence of vegetation and buildings. In order to avoid the influence of temporal differences in our analysis, we compared the surface models in areas where no significant time depending changes could be expected. In addition, we evaluated the potential of the scenes for 3D building model extraction. The results are presented and discussed. ; JRC.G.2-Global security and crisis management