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Remote Sens. 2014, 6(11), 11267-11282; doi:10.3390/rs61111267

Fully-Automated Power Line Extraction from Airborne Laser Scanning Point Clouds in Forest Areas

Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland
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Received: 11 August 2014 / Revised: 27 October 2014 / Accepted: 29 October 2014 / Published: 13 November 2014
(This article belongs to the Special Issue Lidar/Laser Scanning in Urban Environments)
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Abstract

High-voltage power lines can be quite easily mapped using laser scanning data, because vegetation close to high-voltage lines is typically removed and also because the power lines are located higher off the ground in contrast to regional networks and lower voltage networks. On the contrary, lower voltage power lines are located in the middle of dense forests, and it is difficult to classify power lines in such an environment. This paper proposes an automated power line detection method for forest environments. Our method was developed based on statistical analysis and 2D image-based processing technology. During the process of statistical analysis, a set of criteria (e.g., height criteria, density criteria and histogram thresholds) is applied for selecting the candidates for power lines. After transforming the candidates to a binary image, image-based processing technology is employed. Object geometric properties are considered as criteria for power line detection. This method was conducted in six sets of airborne laser scanning (ALS) data from different forest environments. By comparison with reference data, 93.26% of power line points were correctly classified. The advantages and disadvantages of the methods were analyzed and discussed. View Full-Text
Keywords: airborne laser scanning; power line classification; forest environment modelling; image processing technology; statistical methodology airborne laser scanning; power line classification; forest environment modelling; image processing technology; statistical methodology
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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MDPI and ACS Style

Zhu, L.; Hyyppä, J. Fully-Automated Power Line Extraction from Airborne Laser Scanning Point Clouds in Forest Areas. Remote Sens. 2014, 6, 11267-11282.

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