Extraction of power-transmission lines from vehicle-borne lidar data

This paper presents a step-wise method for extracting power-transmission lines and towers from vehicle-borne light detection and ranging (lidar) data. First, this method estimates road ranges with regard to incidence angles and separates off-road points from road-surface points by applying elevation...

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Bibliographic Details
Published in:International journal of remote sensing 2016-01, Vol.37 (1), p.229-247
Main Authors: Guan, Haiyan, Yu, Yongtao, Li, Jonathan, Ji, Zheng, Zhang, Qi
Format: Article
Language:English
Subjects:
Accuracy
Catenary
Clustering
Data
Data acquisition
Datasets
Detection
Error correction
Euclidean geometry
Extraction
Hough transformation
Hyperbolic functions
Incidence angle
Lidar
Lines
Methods
Planes
Roads
Three dimensional
Three dimensional models
Transmission lines
Trigonometric functions
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Summary:This paper presents a step-wise method for extracting power-transmission lines and towers from vehicle-borne light detection and ranging (lidar) data. First, this method estimates road ranges with regard to incidence angles and separates off-road points from road-surface points by applying elevation-difference and slope criteria to the road ranges scan-line by scan-line. Then, three filters, in terms of height, spatial density, and a combination of size and shape, are proposed to extract power-transmission line/power tower points from the identified off-road points, followed by the extraction of individual power-transmission lines via Hough transform and Euclidean distance clustering. Finally, a three-dimensional (3D) power-transmission line is modelled as a horizontal line in the x – y plane and a vertical catenary curve defined by a hyperbolic cosine function in the x – z plane. We evaluated the method using two data sets acquired by the RIEGL VMX-450 system. The average completeness, correctness, and quality of the extracted power-lines on two data sets are 0.92, 0.99, and 0.91, respectively, and the positional accuracies including root mean square error and maximum error averaged 0.07 and 0.05 m, respectively. The results show that the proposed method extracts power-transmission lines from large-scale, vehicle-borne lidar data with good thematic and positional accuracy.
ISSN:1366-5901
0143-1161
1366-5901
DOI:10.1080/01431161.2015.1125549