Next Article in Journal
Accounting for Wood, Foliage Properties, and Laser Effective Footprint in Estimations of Leaf Area Density from Multiview-LiDAR Data
Previous Article in Journal
Anomaly Detection in Hyperspectral Imagery Based on Low-Rank Representation Incorporating a Spatial Constraint
Article Menu
Issue 13 (July-1) cover image

Export Article

Open AccessArticle

Power Pylon Reconstruction Based on Abstract Template Structures Using Airborne LiDAR Data

College of Geoscience and Surveying Engineering, China University of Mining & Technology (Beijing), Beijing 100083, China
Key Laboratory of Digital Earth Science, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
University of Chinese Academy of Science, Beijing 100049, China
School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, Henan, China
Department of Geography and the Environment, University of North Texas, Denton, TX 76203, USA
Kazakh National Research Technical University named after K.I.Satpayev, Almaty 050013, Kazakhstan
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(13), 1579;
Received: 15 May 2019 / Revised: 20 June 2019 / Accepted: 2 July 2019 / Published: 3 July 2019


As an important power facility for transmission corridors, automatic three-dimensional (3D) reconstruction of the pylon plays an important role in the development of smart grid. In this study, a novel three-dimensional reconstruction method using airborne LiDAR (Light Detection And Ranging) point cloud is developed and tested. First, a principal component analysis (PCA) algorithm is performed for pylon redirection based on the structural feature of the upper part of a pylon. Then, based on the structural similarity of a pylon, a pylon is divided into three parts that are inverted triangular pyramid lower structures, quadrangular frustum pyramid middle structures, and complex upper or lateral structures. The reconstruction of the inverted triangular pyramid structures and quadrangular frustum pyramid structures is based on prior knowledge and a data-driven strategy, where the 2D alpha shape algorithm is used to obtain contour points and 2D linear fitting is carried out based on the random sample consensus (RANSAC) method. Complex structures’ reconstruction is based on the priori abstract template structure and a data-driven strategy, where the abstract template structure is used to determine the topological relationship among corner points and the image processing method is used to extract corner points of the abstract template structure. The main advantages in the proposed method include: (1) Improving the accuracy of the pylon decomposition method through introducing a new feature to identify segmentation positions; (2) performing the internal structure of quadrangular frustum pyramids reconstruction; (3) establishing the abstract template structure and using image processing methods to improve computational efficiency of pylon reconstruction. Eight types of pylons are tested in this study, and the average error of pylon reconstruction is 0.32 m and the average of computational time is 0.8 s. These results provide evidence that the pylon reconstruction method developed in this study has high accuracy, efficiency, and applicability. View Full-Text
Keywords: airborne LiDAR; 3D reconstruction; power pylon; abstract template structure; linear fitting; image processing; data-driven airborne LiDAR; 3D reconstruction; power pylon; abstract template structure; linear fitting; image processing; data-driven

Figure 1

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).

Share & Cite This Article

MDPI and ACS Style

Chen, S.; Wang, C.; Dai, H.; Zhang, H.; Pan, F.; Xi, X.; Yan, Y.; Wang, P.; Yang, X.; Zhu, X.; Aben, A. Power Pylon Reconstruction Based on Abstract Template Structures Using Airborne LiDAR Data. Remote Sens. 2019, 11, 1579.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top