Combining Multiple Data Sources for Urban Data Acquisition

One of the most promising approaches to solve the challenging task of thematic mapping in urban environments is the integration of multiple data sources to benefit from the complementary types of available information. Within the paper the combination of Digital Surface Models (DSM) resulting from airborne laser scanning and colour aerial imagery for landuse classification in urban environments is described. The laser DSM is used to obtain information on the local height above the terrain surface for each pixel. This information can be applied in order to separate objects higher than the terrain like buildings and trees from objects at the terrain level like streets and grass-covered areas. The basic idea of the proposed algorithm is to combine the geometric information with additional multispectral information provided from colour aerial imagery. Both types of information are integrated in a pixel-based classification, where the information on the local height above the terrain is applied as an additional channel together with the spectral channels. It is demonstrated that by this approach the classification of urban scenes can be improved considerably compared to a scene labelling, where only one type of data is applied.