Automated 3D Scene Reconstruction from Open Geospatial Data Sources: Airborne Laser Scanning and a 2D Topographic Database

Remote Sensing

Lingli Zhu³  Matti Lehtomäki³  Juha Hyyppä³  Eetu Puttonen³  Anssi Krooks¹  Hannu Hyyppä²  Randolph H. Wynne⁴ 

[1] National Land Survey of Finland, Topographic Data Production. Opastinsilta 12 C, PL 84, FI-00521 Helsinki, Finland; E-mail:;School of Engineering, Aalto University, P.O. Box 15800, FI-00076 Aalto, Finland E-Mail:;Finnish Geospatial Research Institute FGI, Centre of Excellence in Laser Scanning Research, Geodeetinrinne 2, FI-02430 Masala, Finland; E-mails:;Finnish Geospatial Research Institute FGI, Centre of Excellence in Laser Scanning Research, Geodeetinrinne 2, FI-02430 Masala, Finland; E-mails

关键词: open geospatial data;    airborne laser scanning;    topographic database;    building reconstruction;    road reconstruction;    road network;   

DOI  :  10.3390/rs70606710

来源: mdpi

【 摘 要 】

Open geospatial data sources provide opportunities for low cost 3D scene reconstruction. In this study, based on a sparse airborne laser scanning (ALS) point cloud (0.8 points/m²) obtained from open source databases, a building reconstruction pipeline for CAD building models was developed. The pipeline includes voxel-based roof patch segmentation, extraction of the key-points representing the roof patch outline, step edge identification and adjustment, and CAD building model generation. The advantages of our method lie in generating CAD building models without the step of enforcing the edges to be parallel or building regularization. Furthermore, although it has been challenging to use sparse datasets for 3D building reconstruction, our result demonstrates the great potential in such applications. In this paper, we also investigated the applicability of open geospatial datasets for 3D road detection and reconstruction. Road central lines were acquired from an open source 2D topographic database. ALS data were utilized to obtain the height and width of the road. A constrained search method (CSM) was developed for road width detection. The CSM method was conducted by splitting a given road into patches according to height and direction criteria. The road edges were detected patch by patch. The road width was determined by the average distance from the edge points to the central line. As a result, 3D roads were reconstructed from ALS and a topographic database.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.