Advancements in the geometric resolution of space images have improved the conditions for generations of large-scale topographic maps. Using WorldView-1, WorldView-2, and GeoEye-1, images can now be captured from space with a 0.5 m ground sampling distance (GSD). Geometric accuracy and information content are the most significant components of mapping from space images. Depending on the resolution, image quality, and shadows, the identification and classification of ground objects may prove challenging. In this research, the geometric accuracy and information content, of panchromatic WorldView-1 images, were analyzed by covering parts of Istanbul and Zonguldak in Turkey. Each of these locations has various topographic characteristics. For the orientation and investigation of the geometric accuracies of images, a number of ground control points (GCPs) were developed as independent checkpoints. Based on bias-corrected rational polynomial coefficients with one GCP, a standard deviation of independent checkpoints on the range of one GSD was obtained. The information content of images was analyzed by mapping all buildings, in both test areas, and comparing the results with reference 1/5000 scaled topographic maps. The results verified that the WorldView-1 images can be utilized for generating and updating 1/5000 scaled topographic maps of urban areas.