AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA
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...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2019-06-01
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| Series: | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| Online Access: | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1135/2019/isprs-archives-XLII-2-W13-1135-2019.pdf |
| _version_ | 1818197864546828288 |
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| author | L. Truong-Hong D. F. Laefer R. C. Lindenbergh |
| author_facet | L. Truong-Hong D. F. Laefer R. C. Lindenbergh |
| author_sort | L. Truong-Hong |
| collection | DOAJ |
| description | 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/m<sup>2</sup>. 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%. |
| first_indexed | 2024-12-12T01:56:45Z |
| format | Article |
| id | doaj.art-6e3dc7d8f13b4e37865af1d8db9f28d6 |
| institution | Directory Open Access Journal |
| issn | 1682-1750 2194-9034 |
| language | English |
| last_indexed | 2024-12-12T01:56:45Z |
| publishDate | 2019-06-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| spelling | doaj.art-6e3dc7d8f13b4e37865af1d8db9f28d62022-12-22T00:42:19ZengCopernicus PublicationsThe International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences1682-17502194-90342019-06-01XLII-2-W131135114010.5194/isprs-archives-XLII-2-W13-1135-2019AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATAL. Truong-Hong0D. F. Laefer1R. C. Lindenbergh2Dept. of Geoscience & Remote Sensing, Delft University of Technology, Delft, The NetherlandCenter for Urban Science and Progress, New York University, New York, USADept. of Geoscience & Remote Sensing, Delft University of Technology, Delft, The NetherlandWhen 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/m<sup>2</sup>. 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%.https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1135/2019/isprs-archives-XLII-2-W13-1135-2019.pdf |
| spellingShingle | L. Truong-Hong D. F. Laefer R. C. Lindenbergh AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences |
| title | AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA |
| title_full | AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA |
| title_fullStr | AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA |
| title_full_unstemmed | AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA |
| title_short | AUTOMATIC DETECTION OF ROAD EDGES FROM AERIAL LASER SCANNING DATA |
| title_sort | automatic detection of road edges from aerial laser scanning data |
| url | https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-2-W13/1135/2019/isprs-archives-XLII-2-W13-1135-2019.pdf |
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