Adaptation of Roads to Als Data by Means of Network Snakes

In the Authoritative Topographic Cartographic Information System (ATKIS), which is the main public topographic data base in Germany, the heights and the 2D positions of objects such as roads are stored separately in the digital terrain model (DTM) and digital landscape model (DLM). However, for many applications a combined visualization and processing of these two data sets is useful, leading to the demand for a 3D representation of the objects. For this purpose an integration of the height and position is essential. However, discrepancies exist between the DLM and the DTM due to different kinds of acquisition, processing, and modeling. This inconsistency has to be solved within the integration algorithm. Airborne Laserscanning (ALS) is used to acquire the height information for the DTM. Therefore, intensity values of the ALS echoes, which contain the reflectance properties of the illuminated objects, as well as object heights can be exploited in addition to the terrain height. However, the ALS data contain the information related to the DLM-objects only implicitly. Usually, features, for example edges or distinctive points, have to be extracted which can be connected to DLM-objects to realize the integration process. In this paper the matching of the data sets is realized by network snakes which are able to use the implicit ALS information about the position of the DLM-objects without the feature extraction step. The initialization of the contour with the vector data enables the use of ALS data as image energy for an iterative optimization process. Examples are given which apply the concept of network-snakes for the adaptation of a road network to ALS data taking advantage of the prior known topology.