Unsupervised Roofline Extraction from True Orthophotos for LoD2 Building Model Reconstruction

Weixiao Gao*, Ravi Peters, Jantien Stoter

*Corresponding author for this work

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientificpeer-review


This paper discusses the reconstruction of LoD2 building models from 2D and 3D data for large-scale urban environments. Traditional methods involve the use of LiDAR point clouds, but due to high costs and long intervals associated with acquiring such data for rapidly developing areas, researchers have started exploring the use of point clouds generated from (oblique) aerial images. However, using such point clouds for traditional plane detection-based methods can result in significant errors and introduce noise into the reconstructed building models. To address this, this paper presents a method for extracting rooflines from true orthophotos using line detection for the reconstruction of building models at the LoD2 level. The approach is able to extract relatively complete rooflines without the need for pre-labeled training data or pre-trained models. These lines can directly be used in the LoD2 building model reconstruction process. The method is superior to existing plane detection-based methods and state-of-the-art deep learning methods in terms of the accuracy and completeness of the reconstructed building. Our source code is available at https://github.com/tudelft3d/Roofline-extraction-from-orthophotos.
Original languageEnglish
Title of host publicationRecent Advances in 3D Geoinformation Science
Subtitle of host publicationProceedings of the 18th 3D GeoInfo Conference
EditorsThomas H. Kolbe, Andreas Donaubauer, Christof Beil
Place of PublicationCham
Number of pages12
ISBN (Electronic)978-3-031-43699-4
ISBN (Print)978-3-031-43698-7, 978-3-031-43701-4
Publication statusPublished - 2024
Event18th 3D Geoinfo Conference - Technical University of Munich, Munich, Germany
Duration: 12 Sept 202314 Sept 2023

Publication series

NameLecture Notes in Geoinformation and Cartography
ISSN (Print)1863-2246
ISSN (Electronic)1863-2351


Conference18th 3D Geoinfo Conference
Internet address

Bibliographical note

Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care
Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.


  • Building rooflines extraction
  • 3D building models
  • True orthophotos
  • Raytracing


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