Evaluation of Automatically Generated 2D Footprints from Urban LiDAR Data

Over the last decade, several automatic approaches have been proposed to extract and reconstruct 2D building footprints and 2D road profiles from ALS data, satellite images, and/or aerial imagery. Since these methods have to date been applied to various data sets and assessed through a variety of different quality indicators and ground truths, comparing the relative effectiveness of the techniques and identifying their strengths and short-comings has not been possible in a systematic way. This open contest was designed to overcoming this shortcoming. Specifically, participants were asked to submit 2D footprints (building outlines and road profiles) derived from ALS data from a highly dense data (approximately 225 points/m2) across a 1km2 of central Dublin, Ireland. The proposed evaluation strategies were designed to measure not only the capacity of each method to detect and reconstruct 2D buildings and roads but also the quality of the reconstructed building and road models in terms of shape similarity and positional accuracy. The evaluated methods will represent those submitted as part of IQPC15.