Automatic detection of road edges from aerial laser scanning data

Automatic detection of road edges from aerial laser scanning data

Truong-Hong, Linh (TU Delft Optical and Laser Remote Sensing)
Laefer, D. F. (New York University)
Lindenbergh, R.C. (TU Delft Optical and Laser Remote Sensing)

2019

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%.

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

http://resolver.tudelft.nl/uuid:7398b300-ae41-4d04-9ef6-50f0b02078c3

https://doi.org/10.5194/isprs-archives-XLII-2-W13-1135-2019

1682-1750

International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII (2/W13), 1135-1140

4th ISPRS Geospatial Week 2019, 2019-06-10 → 2019-06-14, Enschede, Netherlands

Institutional Repository

journal article

© 2019 Linh Truong-Hong, D. F. Laefer, R.C. Lindenbergh