DISTANCE-VALUE-ADDED PANORAMIC IMAGES AS THE BASE DATA MODEL FOR 3D-GIS

Abstract

Panoramic images portray a surround view of the real world in one image. This kind of presentation however does, alike regular pictures, not give any real depth information. Depth related relationships are only to be detected (within one image) by psychological cues like relative size, linear perspective and shadow. The relative distance between two features can only be retrieved by 1) stereoscopic measurement within two pictures or 2) by the integration of terrestrial laser scanning systems. In the second approach the photo is enhanced with information about the distance between each pixel and the location of image recording. If we visualize this cloud of ‘distance pixels ’ from a point of view chosen at the recording place through a panoramic perspective it will give us the impression of the original panoramic picture, but now with the added value of depth-related queries. This kind of ‘distance-valueadded’ panoramic pictures can be used as a base data model for 3D-GIS visualizations. This paper concentrates on the database organization of RGB laser scan point clouds, the creation of virtual ‘distance-value-added ’ panoramic images from these clouds, and the visualization and spatial analysis based on this kind of perception rich images. 1