The first of the automatic reconstruction of buildings from aerial images is to find where the buildings are. Many methods can be used for this work, but if the aerial photo is color, it is a very useful information for finding the houses because usually the color of one single roof is uniform and is different from the color of adjacent objects likes grass,roads,etc. Two aspects are researched here to study the possible usage of color information. First, we try to use color information to enhance linear feature extraction. Second, we try to omit the step of linear feature extraction and use the color information to extract building regions directly. In order to test the feasibility of the thought, we choose three different types of building images for experiment. The first type includes isolated buildings, the second type includes aggregation of buildings, and in the third type there are high apartment buildings. The results of the experiment show that in one hand color information do help to extract more complete linear features, and in the other hand，color information can very effectively be used to extract building regions, presumed the color of each individual roof is uniform. It proves that color information is indeed helpful for feature extraction.

In this paper we study the positioning technologies which have high efficiency and precision, therefore our objects of study include both rapid static positioning and kinematic positioning. We analyze the rapid static positioning by various baseline length from about 50m to 26km, and evaluate the kinematic positioning with respect to its repeatability and feasibility by a baseline of about 10km. These technologies are applied to satellite leveling and experimentally verified. For 25 check points in a 6km × 5km flat test area, the rapid state and kinematic satellite surveying technologies can yield ± 1.1cm and ± 1.3cm height accuracy. Besides, a technique of the decorrelation method to improve the accuracy by calibration the receiver clock bias is offered in this paper, and using Ashtech 3DF data to prove it. From experiment we know the height component is improved about 300%.

Aerial photograph is a very useful tool for forest landscape studies. Interpretation of aerial photograph is very helpful for studying the distribution of landscape units. In this research, a modified fractal dimension was used as an index to study the effects on landscape resulted from various management activities using simulated data. In addition, the Luku experimental forest was selected as the study site to understand the fractal dimension in real landscape. The results indicate that： (1) When harvesting timber, the effect on landscape diversity can be reduced if the harvesting sites, with irregular shapes, are selected along the boundary between two patches. (2) Road development is a disturbance to the forest landscape, and it will reduce the modified fractal dimension. Therefore the roads should not pass through the landscape, in order to preserve the integrity of the landscape.

Viewshed is a useful operation for terrain analysis. Due to the plausibility of the line­ of-sight definition, the application of different computational algorithm and coding techniques, the viewsheds computed from different implementations are different. In this study, the differences of viewshed resulting from ARC/INFO (visibility), GRASS (r.los) are compared with a self-developed program ViewShed with real terrain data sets. The evaluation is performed with visual inspection, pixel count for the differences, and correlation coefficients.