Extraction and Utilization of Geometrical and Contextual Information in very High Resolution IKONOS Satellite Imagery
classification result of the image of Figure 3(a). Areas belonging to the "road" class are shown in white. All other classes are in black. The network of the roads shows up prominently after classification. However, holes may occur within a road region and sometimes the road can be hidden behind vegetation or other classes.
4. Estimating building height from Shadows
In conventional stereo processing techniques, heights of buildings can be estimated using two images of the same area acquired at different viewing directions. Building height can also be derived from a single image using a simple geometric method if shadows of the buildings can be located in the image. For example, in Figure 4, the height of the building (H) can be calculated from the length of its shadow (Ls) on the ground and the sun elevation angle (qs) using a simple trigonometric relation: H = Ls tan(qs). Very often, the base of a building in a satellite image is blocked by other surrounding structure such that the shadow length cannot be determined. In this case, it is still possible to determine the building height if both the top of the building (such as point P in Fig. 4) and its shadow (point Q in Fig. 4) can be located in the image. The building height can be obtained by using a geometric relation between the length of the line joining PQ on the image and the building height H.
Figure 4: Geometry for estimating building from shadow
For example, Figure 5 shows the Chairman Mao Memorial Hall in Beijing. The top left corner of the roof top and its shadow can be seen clearly. The height of the building can be determined to be about 35 m with one or two meters error.
Figure 5: (left) Ikonos image of the Chairman Mao Memorial Hall in Beijing, China;
(right) Photograph of the building..
5. Conclusion
In this paper, we have presented three potential new applications of the 1-meter IKONOS images. These applications demand the "common sense" type of knowledge that is relatively easy for human. However, due to the tediousness and extensiveness of the tasks, the automation of these tasks is invaluable. We have also shown that the automation of some of these tasks can be easily made possible using some existing tools.
References
- Brandtberg T., and Walter F., 1998. Automated delineation of individual tree crowns in high spatial resolution aerial images by multiple-scale analysis, Machine Vision and Applications (1998) 11:64-73.
- Coxeter, H.S.M., 1969. Introduction to geometry, 2nd Ed, New York, Wiley.
