Extraction of Buildings and Trees Using Images and LIDAR Data

Abstract

The automatic detection and 3D modeling of objects at airports is an important issue for the EU FP6 project PEGASE. PEGASE is a feasibility study of a new 24/7 navigation system, which could either replace or complement existing systems and would allow a three-dimensional truly autonomous aircraft landing and take-off primarily for airplanes and secondary for helicopters. In this work, we focus on the extraction of man-made structures, especially buildings, by combining information from aerial images and Lidar data. We applied four different methods on a dataset located at Zurich Airport, Switzerland. The first method is based on DSM/DTM comparison in combination with NDVI analysis; the second one is a supervised multispectral classification refined with height information from Lidar data. The third approach uses voids in Lidar DTM and NDVI classification, while the last method is basedon the analysis of the vertical density of the raw Lidar DSM data. The accuracy of the building extraction process was evaluated by comparing the results with reference data and computing the percentage of data correctly extracted and the percentage of missing reference data. The results are reported and commented.