Semiautomatic reconstruction of building height and footprints from single satellite images

Extraction of man-made structures from satellite images is one of the essential issues in remote sensing and many techniques were proposed for building extraction from high resolution satellite images. However, most of them rely stereo analysis or additional data sources such as LIDAR for retrieval of 3D building information. This paper proposes a semiautomatic approach that extracts 3D building information from single satellite images. In this approach, after measuring boundaries of a building roof we determine the building height by projecting building shadow onto the image space until the projected shadow matches the actual shadow. Then we extract building footprints by translating roof boundaries along the direction of vertical edges to the amount determined by the building height. To increase the level of automation, we devised a technique that adjusts the height so that the projected shadow matches the actual shadow and determine building height automatically. We also devised a technique to extract roof boundaries by clicking only two corner points. A panchromatic IKONOS image and Quickbird image over Deajeon area were used to test proposed algorithms and a IKONO stereo pair was used to get reference building heights. While building heights determined manually showed the accuracy of an RMS error of 1.66 m, the heights determined automatically showed an RMS error of 1.86 m. The results show that 3D building information can be extracted from single satellite images and that the automation approaches proposed in this paper worked.