Voxel-Based Extraction of Individual Pylons and Wires From Lidar Point Cloud Data

Munir, Nosheen; Awrangjeb, Mohammad; Stantić, Bela; Lu, Guojun; Islam, Syed

doi:10.5194/isprs-annals-iv-4-w8-91-2019

Cited by 12 publications

(12 citation statements)

References 9 publications

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“…On the other hand, rule-based classification is on hierarchical rules to achieve classification [28,60]. These rules may include statistical analysis [50,51] or hierarchical filtering procedures [21,28].…”

Section: Methodsmentioning

confidence: 99%

“…For extraction of single or multi-conductor power lines, some methods transform the point cloud into a 2D grid [19,69] or to a 3D voxel grid [28,51,77]. The 2D grid-based methods have limitations, as they interpolate the 3D point cloud into a 2D grid, which causes the overlapping of multiple objects [51,73]. Among these grids, a voxel grid is considered as more efficient and reliable [29].…”

Section: Grid Transformationmentioning

confidence: 99%

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Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review

2023

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Electricity has become an indispensable source of energy, and power lines play a crucial role in the functioning of modern societies. It is essential to inspect power lines promptly and precisely in order to ensure the safe and secure delivery of electricity. In steep and mountainous terrain, traditional surveying methods cannot inspect power lines precisely due to their nature. Remote sensing platforms, such as satellite and aerial images, thermal images, and light detection and ranging (LiDAR) points, were utilised for the detection and inspection of power lines. Nevertheless, with the advancements of remote sensing technologies, in recent years, LiDAR surveying has been favoured for power line corridor (PLC) inspection due to active and weather-independent nature of laser scanning. Laser ranging data and the precise location of the LiDAR can be used to generate a three-dimensional (3D) image of the PLC. The resulting 3D point cloud enables accurate extraction of power lines and measurement of their distances from the forest below. In the literature, there have been many proposals for power line extraction and reconstruction for PLC modelling. This article examines the pros and cons of each domain method, providing researchers involved in three-dimensional modelling of power lines using innovative LiDAR scanning systems with useful guidelines. To achieve these objectives, research papers were analysed, focusing primarily on geoscience-related journals and conferences for the extraction and reconstruction of power lines. There has been a growing interest in examining the extraction and reconstruction of power line spans with single and multi-conductor configurations using different image and point-based techniques. Our study provides a comprehensive overview of the methodologies offered by various approaches using laser scanning data from the perspective of power line extraction applications, as well as to discuss the benefits and drawbacks of each approach. The comparison revealed that, despite the tremendous potential of aerial and mobile laser scanning systems, human intervention and post-processing actions are still required to achieve the desired results. In addition, the majority of the methods have been evaluated on the small datasets, and very few methods have been focused on multi-conductor extraction and reconstruction for power lines modelling. These barriers hinder the automated extraction and reconstruction of power line using LiDAR data and point to unexplored areas for further research and serve as useful guidelines for future research directions. Several promising directions for future LiDAR experiments using deep learning methods are outlined in the hope that they will pave the way for applications of PLC modelling and assessment at a finer scale and on a larger scale.

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Section: Methodsmentioning

confidence: 99%

Section: Grid Transformationmentioning

confidence: 99%

Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review

2023

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“…The proposed approach first extracts the PL candidate regions in the form of spans by adopting the technique mentioned in Munir et al [37]. Once the spans are determined, the main contribution of this paper comes, which is the extraction of subconductors from each bundle located in the span.…”

Section: Methodsmentioning

confidence: 99%

“…Munir et al [37] proposed a semiautomated hierarchical method where the SVM was first used to separate the PL points from other objects. Then, by exploiting the spatial distribution property of power lines, a voxel-based technique was applied to separate individual conductors.…”

Section: Related Workmentioning

confidence: 99%

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Automatic Extraction of High-Voltage Bundle Subconductors Using Airborne LiDAR Data

2020

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Overhead high-voltage conductors are the chief components of power lines and their safety has a strong influence on social and daily life. In the recent decade, the airborne laser scanning (ALS) technique has been widely used to capture the three-dimensional (3D) information of power lines and surrounding objects. Most of the existing methods focused on extraction of single conductors or extracted all conductors as one object class by applying machine learning techniques. Nevertheless, power line corridors (PLCs) are built with multi-loop, multi-phase structures (bundle conductors) and exist in intricate environments (e.g., mountains and forests), and thus raise challenges to process ALS data for extraction of individual conductors. This paper proposes an automated method to extract individual subconductors in bundles from complex structure of PLCs using a combined image- and point-based approach. First, the input point cloud data are grouped into 3D voxel grid and PL points and separated from pylon and tree points using the fact that pylons and trees are vertical objects while power lines are non-vertical objects. These pylons are further separated from trees by employing a statistical analysis technique and used to extract span points between two consecutive pylons; then, by using the distribution properties of power lines in each individual span, the bundles located at different height levels are extracted using image-based processing; finally, subconductors in each bundle are detected and extracted by introducing a window that slides over the individual bundle. The orthogonal plane transformation and recursive clustering procedures are exploited in each window position and a point-based processing is conducted iteratively for extraction of complete individual subconductors in each bundle. The feasibility and validity of the proposed method are verified on two Australian sites having bundle conductors in high-voltage transmission lines. Our experiments show that the proposed method achieves a reliable result by extracting the real structure of bundle conductors in power lines with correctness of 100% and 90% in the two test sites, respectively.

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An Outlier Removal Method from UAV Point Cloud Data for Transmission Lines

2021

2021 Computing, Communications and IoT Applications (ComComAp)

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Voxel-Based Extraction of Individual Pylons and Wires From Lidar Point Cloud Data

Cited by 12 publications

References 9 publications

Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review

Power Line Extraction and Reconstruction Methods from Laser Scanning Data: A Literature Review

Automatic Extraction of High-Voltage Bundle Subconductors Using Airborne LiDAR Data

An Outlier Removal Method from UAV Point Cloud Data for Transmission Lines

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