Data fusion of high-resolution satellite imagery and LiDAR data for automatic building extraction

Abstract

This paper aims to present a new approach for automatic extraction of building footprints in a combination of the IKONOS imagery with pan-sharpened multi-spectral bands and the low-sampled (∼ 0.1 points/m 2) airborne laser scanning data acquired from the Optech's 1020 ALTM (Airborne Laser Terrain Mapper). Initially, a laser point cluster in 3D object space was recognized as an isolated building object if all the member points were similarly attributed as building points by investigating the height property of laser points and the normalized difference vegetation indices (NDVI) driven from IKONOS imagery. As modelling cues, rectilinear lines around building outlines collected by either data-driven or model-driven manner were integrated in order to compensate the weakness of both methods. Finally, a full description of building outlines was accomplished by merging convex polygons, which were obtained as a building region was hierarchically divided by the extracted lines using the Binary Space Partitioning (BSP) tree. The system performance was evaluated by objective evaluation metrics in comparison to the Ordnance Survey's MasterMap®. This evaluation showed the delineation performance of up to 0.11 (the branching factor) and the detection percentage of 90.1% (the correctness) and the overall quality of 80.5%.