Automatic detection of road edges from aerial laser scanning data

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

Research output: Contribution to journalConference articlepeer-review


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 (US)
Pages (from-to)1135-1140
Number of pages6
JournalInternational Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives
Issue number2/W13
StatePublished - Jun 4 2019
Event4th ISPRS Geospatial Week 2019 - Enschede, Netherlands
Duration: Jun 10 2019Jun 14 2019


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

ASJC Scopus subject areas

  • Information Systems
  • Geography, Planning and Development


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