The location-aware Internet is inspiring intensive work addressing the automated assembly of three-dimensional models of urban spaces with their buildings, circulation spaces, vegetation, signs, even their above-ground and underground utility lines. Two-dimensional geographic information systems (GISs) and municipal utility information exist and can serve to guide the creation of models being built with aerial, sometimes satellite imagery, streetside images, indoor imaging, and alternatively with light detection and ranging systems (LiDARs) carried on airplanes, cars, or mounted on tripods. We review the results of current research to automate the information extraction from sensor data. We show that aerial photography at ground sampling distances (GSD) of 1 to 10 cm is well suited to provide geometry data about building facades and roofs, that streetside imagery at 0.5 to 2 cm is particularly interesting when it is collected within community photo collections (CPCs) by the general public, and that the transition to digital imaging has opened the no-cost option of highly overlapping images in support of a more complete and thus more economical automation. LiDAR-systems are a widely used source of three-dimensional data, but they deliver information not really superior to digital photography.