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

• Published in: Remote sensing (Basel, Switzerland) Vol. 11; no. 13; p. 1579
• Main Authors: Chen, Shichao, Wang, Cheng, Dai, Huayang, Zhang, Hebing, Pan, Feifei, Xi, Xiaohuan, Yan, Yueguan, Wang, Pu, Yang, Xuebo, Zhu, Xiaoxiao, Aben, Ardana
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-07-2019
• Subjects: 3D reconstruction; abstract template structure; airborne LiDAR; Algorithms; data-driven; Decomposition; Efficiency; Electricity distribution; Horizontal orientation; Image processing; Lidar; linear fitting; Methods; Model accuracy; Neural networks; power pylon; Pylons; Reconstruction; Remote sensing; Software; Beijing China; China
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs11131579

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.