Next Article in Journal / Special Issue
A Classification-Segmentation Framework for the Detection of Individual Trees in Dense MMS Point Cloud Data Acquired in Urban Areas
Previous Article in Journal
Glacier Mass Loss during the 1960s and 1970s in the Ak-Shirak Range (Kyrgyzstan) from Multiple Stereoscopic Corona and Hexagon Imagery
Previous Article in Special Issue
Fast Segmentation and Classification of Very High Resolution Remote Sensing Data Using SLIC Superpixels
Article Menu
Issue 3 (March) cover image

Export Article

Open AccessArticle
Remote Sens. 2017, 9(3), 282; doi:10.3390/rs9030282

Geometric Refinement of ALS-Data Derived Building Models Using Monoscopic Aerial Images

1
Institute of Geodesy and Geoinformatics, Wroclaw University of Environental and Life Science, 50-375 Wrocław, Poland
2
Institute of Photogrammetry and Remote Sensing, Technische Universität Dresden, 01069 Dresden, Germany
3
Institute of Geodesy and Geoinformation Science, Technische Universität Berlin, 10623 Berlin, Germany
*
Author to whom correspondence should be addressed.
Received: 28 December 2016 / Revised: 9 March 2017 / Accepted: 12 March 2017 / Published: 16 March 2017
View Full-Text   |   Download PDF [5806 KB, uploaded 17 March 2017]   |  

Abstract

Airborne laser scanning (ALS) has proven to be a strong basis for 3D building reconstruction. While ALS data allows for a highly automated processing workflow, a major drawback is often in the point spacing. As a consequence, the precision of roof plane and ridge line parameters is usually significantly better than the precision of gutter lines. To cope with this problem, the paper presents an approach for geometric refinement of building models reconstructed from ALS data using monoscopic aerial images. The core idea of the proposed modeling method is to obtain refined roof edges by intersecting roof planes accurately and reliably extracted from 3D point clouds with viewing planes assigned with building edges detected in a high resolution aerial image. In order to minimize ambiguities that may arise during the integration of modeling cues, the ALS data is used as the master providing initial information about building shape and topology. We evaluate the performance of our algorithm by comparing the results of 3D reconstruction executed using only laser scanning data and reconstruction enhanced by image information. The assessment performed within a framework of the International Society for Photogrammetry and Remote Sensing (ISPRS) benchmark shows an increase in the final quality indicator up to 8.7%. View Full-Text
Keywords: building reconstruction; 3D modeling; laser scanning; aerial imagery; edge matching building reconstruction; 3D modeling; laser scanning; aerial imagery; edge matching
Figures

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Jarząbek-Rychard, M.; Maas, H.-G. Geometric Refinement of ALS-Data Derived Building Models Using Monoscopic Aerial Images. Remote Sens. 2017, 9, 282.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top