Abstract
A Digital Terrain Model (DTM) is typically used in applications such as environment planning, flood risk evaluation and building detection. A Digital Surface Model (DSM) is usually acquired by LASER scanning or from stereoscopic pairs of aerial or satellite images. By contrast, a direct DTM acquisition traditionally requires more effort on the terrain or for scene object classification and the automatic derivation of a DTM from a DSM still faces difficulties.

The proposed algorithm developed for urban areas has been applied to the Vaihingen dataset of the ISPRS benchmark and qualitatively validated by the results of its independent evaluation procedure for building detection. In the context of change detection for database revision, this new DTM extraction was applied to an area in Brussels for which digital aerial imagery and LIDAR measurements are available. This reference data allowed for some quantitative evaluation of the DTM errors.