AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA

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

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%.

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Truong-Hong, L. / Laefer, D. F. / Lindenbergh, R. C.: AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA. 2019. Copernicus Publications.

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Rechteinhaber: L. Truong-Hong et al.

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