Abstract
3D city models support many government agencies for development planning as well as climate, fire propagation, and public safety studies. Commercial building modeling software tools require a high degree of interpersonal communication, which is always time-consuming. However, a reliable and highly accurate city model approach is still a challenging task that requires several processing steps of the workflow. This research proposes an automated approach for building reconstruction from airborne laser scanning data. We use a reliable segmentation algorithm to separate roads, trees and meadows from buildings. The parameters for segmentation are of crucial importance for the outline detection and the 3D modeling approach. We describe the theoretical background, the segmentation algorithm, the outline detection, the modeling approach and methods to determine the parameters. We validate the approach by a sub dataset of point cloud data captured by airborne LiDAR system.
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Wang, C., Hu, X., Ji, M., Li, T. (2013). An Automated 3D Approach for Buildings Reconstruction from Airborne Laser Scanning Data. In: Bian, F., Xie, Y., Cui, X., Zeng, Y. (eds) Geo-Informatics in Resource Management and Sustainable Ecosystem. Communications in Computer and Information Science, vol 398. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-45025-9_69
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DOI: https://doi.org/10.1007/978-3-642-45025-9_69
Publisher Name: Springer, Berlin, Heidelberg
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