A method was proposed for the estimation of ground surface elevation in forested hills and mountains using helicopter-borne laser scanner data. In the process of deriving ground surface by the subtraction of tree heights from canopy surface, we considered the spatial distribution of tree heights. Tree heights varied with the topographic variable: horizontal distance from stream, and a logistic curve were applied in the regression analysis. The validation with field-surveyed elevation data indicated that our method showed better estimation than the method of using mean tree height.
3D city modeling from airborne imagery includes mainly two parts: (1) image processing procedures and (2) 3D modeling for man-made objects such as buildings, roads and other objects. Line or feature extraction and stereo matching are usually utilized as an image processing procedures, and geometrical data acquisition for man-made objects are performed. However, there are some issues for automatic or semi-automatic man-made object modeling. These problems include uncertainty within matching, extraction of man-made objects and spatial data acquisition. In particular, spatial data acquisition of buildings are important for reliable city modeling. With this objective, this paper focuses especially on efficient and robust line matching method using optical flow, which enable an automatic building extraction since line gives important information for building extraction and satisfied results are depend on rigorous line extraction and matching. Furthermore, building extraction using morphological opening and 3D city modeling are also investigated in this paper.