Automatic detection of road edges from aerial laser scanning data

L. Truong-Hong, D. F. Laefer*, R. C. Lindenbergh

*Corresponding author for this work

Research output: Contribution to journalConference articleScientificpeer-review

5 Citations (Scopus)
149 Downloads (Pure)


When aerial laser scanning (ALS) is deployed with targeted flight path planning, urban scenes can be captured in points clouds with both high vertical and horizontal densities to support a new generation of urban analysis and applications. As an example, this paper proposes a hierarchical method to automatically extract data points describing road edges, which are then used for reconstructing road edges and identifying accessible passage areas. The proposed approach is a cell-based method consisting of 3 main steps: (1) filtering rough ground points, (2) extracting cells containing data points of the road curb, and (3) eliminating incorrect road curb segments. The method was tested on a pair of 100 m × 100 m tiles of ALS data of Dublin Ireland's city center with a horizontal point density of about 325 points/m2. Results showed the data points of the road edges to be extracted properly for locations appearing as the road edges with the average distance errors of 0.07 m and the ratio between the extracted road edges and the ground truth by 73.2%.

Original languageEnglish
Pages (from-to)1135-1140
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Issue number2/W13
Publication statusPublished - 2019
Event4th ISPRS Geospatial Week 2019 - Enschede, Netherlands
Duration: 10 Jun 201914 Jun 2019


  • Aerial Laser Scanning
  • Cell Decomposition
  • Cell-based Region Growing
  • Road Curb
  • Road Extraction


Dive into the research topics of 'Automatic detection of road edges from aerial laser scanning data'. Together they form a unique fingerprint.

Cite this