Building height extraction from overlapping airborne images in urban environment using computer vision approach

摘要

Estimating and measuring building height has become one of the significant factors in urban planning, legal and illegal construction inspection, urban disaster warning and assessing, as well as providing initial mapping data for creating three dimensional (3D) digital city models. In this paper we examine the feasibility of extracting building height information using computer vision algorithms with Structure from Motion procedures (SfM) from overlapping airborne images in urban environment. 3D land surface models can be generated from airborne images, and then DTM is subtracted from the DSM to form the nDSM layer. Using object-based image analysis, building height can be differentiated from bush, trees, and others by rulesets of spectral features, geometric features and contextual information. The accuracy of the building height based on orthorectified images and nDSM from airborne imagery was at a similar level to those based on airborne LiDAR data from the same study area.