{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,27]],"date-time":"2026-03-27T16:55:18Z","timestamp":1774630518741,"version":"3.50.1"},"reference-count":31,"publisher":"MDPI AG","issue":"8","license":[{"start":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T00:00:00Z","timestamp":1618272000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministry of Education Joint Fund; National Natural Science Foundation of China; National Key Research and Development Program","award":["No. 6141A02011907; Nos. 41674017; Nos. 2016YFB0501803 and 2016YFB0502202"],"award-info":[{"award-number":["No. 6141A02011907; Nos. 41674017; Nos. 2016YFB0501803 and 2016YFB0502202"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Powerline detection is becoming a significant issue for powerline monitoring and maintenance, which further ensures transmission security. As an efficient method, laser scanning has attracted considerable attention in powerline detection for its high precision and robustness during the night period. However, due to occlusion and varying point density, gaps will appear in scans and greatly influence powerline detection by over\u2013clustering, insufficient extraction, or misclassification in existing methods. Moreover, this situation will be worse in terrestrial laser scanning (TLS), because TLS suffers more from gaps due to its unique ground\u2013based scanning mode compared to other laser scanning systems. Thereby, this paper explores a robust method to repair gaps for extracting powerlines from TLS data. Firstly, a hierarchical clustering method is used to extract the powerlines. During the clustering, gaps are repaired based on neighborhood relations of powerline candidates, and repaired gaps can create continuous neighborhood relations that ensure the execution of the clustering method in return. Test results show that the hierarchical clustering method is robust in powerline extraction with repaired gaps. Secondly, reconstruction is performed for further detection. Pylon\u2013powerline connections are found by the slope change method, and powerlines with multi\u2013span are successfully fitted using these connections. Experiment shows that it is feasible to find connections for multi\u2013span reconstruction.<\/jats:p>","DOI":"10.3390\/rs13081502","type":"journal-article","created":{"date-parts":[[2021,4,13]],"date-time":"2021-04-13T22:55:09Z","timestamp":1618354509000},"page":"1502","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A Hierarchical Clustering Method to Repair Gaps in Point Clouds of Powerline Corridor for Powerline Extraction"],"prefix":"10.3390","volume":"13","author":[{"given":"Yongzhao","family":"Fan","sequence":"first","affiliation":[{"name":"Hubei Subsurface Multi\u2013Scale Imaging Key Laboratory, Institute of Geophysics &amp; Geomatics, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Rong","family":"Zou","sequence":"additional","affiliation":[{"name":"Hubei Subsurface Multi\u2013Scale Imaging Key Laboratory, Institute of Geophysics &amp; Geomatics, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Xiaoyun","family":"Fan","sequence":"additional","affiliation":[{"name":"GNSS Research Center, Wuhan University, Wuhan 430079, China"}]},{"given":"Rendong","family":"Dong","sequence":"additional","affiliation":[{"name":"Hubei Subsurface Multi\u2013Scale Imaging Key Laboratory, Institute of Geophysics &amp; Geomatics, China University of Geosciences, Wuhan 430074, China"}]},{"given":"Mengyou","family":"Xie","sequence":"additional","affiliation":[{"name":"Hubei Subsurface Multi\u2013Scale Imaging Key Laboratory, Institute of Geophysics &amp; Geomatics, China University of Geosciences, Wuhan 430074, China"}]}],"member":"1968","published-online":{"date-parts":[[2021,4,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Zou, R., Fan, X., Qian, C., Ye, W., Zhao, P., Tang, J., and Liu, H. (2019). An Efficient and Accurate Method for Different Configurations Railway Extraction Based on Mobile Laser Scanning. Remote Sens., 11.","DOI":"10.3390\/rs11242929"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1002\/rob.20424","article-title":"Toward automated power line corridor monitoring using advanced aircraft control and multisource feature fusion","volume":"29","author":"Li","year":"2011","journal-title":"J. Field Robot."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"3892","DOI":"10.1109\/JSTARS.2018.2869542","article-title":"Voxel-Based Extraction of Transmission Lines from Airborne LiDAR Point Cloud Data","volume":"11","author":"Yang","year":"2018","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_4","first-page":"258","article-title":"Extraction of power lines using mobile LiDAR data of roadway environment","volume":"8","author":"Yadav","year":"2017","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"343","DOI":"10.1016\/j.isprsjprs.2020.03.018","article-title":"Automated and efficient powerline extraction from laser scanning data using a voxel-based subsampling with hierarchical approach","volume":"163","author":"Jung","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Ye, W., Qian, C., Tang, J., Liu, H., Fan, X., Liang, X., and Zhang, H. (2020). Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data. Remote Sens., 12.","DOI":"10.3390\/rs12030352"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"042011","DOI":"10.1088\/1755-1315\/446\/4\/042011","article-title":"Research on High Voltage Power Line extraction based on Transmission Line Point Cloud characteristics and Model fitting","volume":"446","author":"Yang","year":"2020","journal-title":"IOP Conf. Ser. Earth Environ. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"2043","DOI":"10.3906\/elk-1801-23","article-title":"An automatic extraction algorithm of high voltage transmission lines from airborne LIDAR point cloud data","volume":"26","author":"Shen","year":"2018","journal-title":"Turk. J. Electr. Eng. Comput. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"11267","DOI":"10.3390\/rs61111267","article-title":"Fully-Automated Power Line Extraction from Airborne Laser Scanning Point Clouds in Forest Areas","volume":"6","author":"Zhu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"46","DOI":"10.18005\/JRST0304001","article-title":"Automatic Extraction of Power Transmission Lines Using Laser Scanner Data","volume":"3","author":"Valente","year":"2015","journal-title":"J. Remote Sens. Technol."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"229","DOI":"10.1080\/01431161.2015.1125549","article-title":"Extraction of power-transmission lines from vehicle-borne lidar data","volume":"37","author":"Guan","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1080\/17538947.2018.1503740","article-title":"A Hierarchical unsupervised method for power line classification from airborne LiDAR data","volume":"12","author":"Wang","year":"2019","journal-title":"Int. J. Digit. Earth"},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Wang, Y., Chen, Q., Liu, L., Zheng, D., Li, C., and Li, K. (2017). Supervised Classification of Power Lines from Airborne LiDAR Data in Urban Areas. Remote Sens., 9.","DOI":"10.3390\/rs9080771"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3302","DOI":"10.3390\/rs6043302","article-title":"Extraction of Urban Power Lines from Vehicle-Borne LiDAR Data","volume":"6","author":"Cheng","year":"2014","journal-title":"Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"734","DOI":"10.1109\/JSTARS.2019.2893967","article-title":"Power Line Extraction from Mobile LiDAR Point Clouds","volume":"12","author":"Xu","year":"2019","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_16","first-page":"105","article-title":"Automatic 3D powerline reconstruction using airborne lidar data","volume":"38","author":"Jwa","year":"2009","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/j.isprsjprs.2014.04.015","article-title":"Classification of airborne laser scanning data using Joint Boost","volume":"100","author":"Guo","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Liu, Y., Li, Z., Hayward, R., Walker, R., and Jin, H. (2009, January 1\u20133). Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors. Proceedings of the 2009 Digital Image Computing: Techniques and Applications, Melbourne, VIC, Australia.","DOI":"10.1109\/DICTA.2009.83"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"246","DOI":"10.15292\/geodetski-vestnik.2015.02.246-261","article-title":"Extraction of Power Lines from Airborne and Terrestrial Laser Scanning Data Using the Hough Transform","volume":"59","author":"Grigillo","year":"2015","journal-title":"Geod. Vestn."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Nasseri, M.H., Moradi, H., Nasiri, S., and Hosseini, R. (2018, January 23\u201325). Power Line Detection and Tracking Using Hough Transform and Particle Filter. Proceedings of the 2018 6th RSI International Conference on Robotics and Mechatronics (IcRoM), Tehran, Iran.","DOI":"10.1109\/ICRoM.2018.8657568"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tilawat, J., Theera-Umpon, N., and Auephanwiriyakul, S. (2010, January 1\u20133). Automatic detection of electricity pylons in aerial video sequences. Proceedings of the 2010 International Conference on Electronics and Information Engineering, Kyoto, Japan.","DOI":"10.1109\/ICEIE.2010.5559863"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, R., Yang, B., Xiao, W., Liang, F., Liu, Y., and Wang, Z. (2019). Automatic Extraction of High-Voltage Power Transmission Objects from UAV Lidar Point Clouds. Remote Sens., 11.","DOI":"10.3390\/rs11222600"},{"key":"ref_23","first-page":"61","article-title":"Power lines extraction from airborne lidar data using spatial domain segmentation","volume":"18","author":"Liu","year":"2014","journal-title":"J. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Awrangjeb, M. (2019). Extraction of Power Line Pylons and Wires Using Airborne LiDAR Data at Different Height Levels. Remote Sens., 11.","DOI":"10.3390\/rs11151798"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"McCulloch, J., and Green, R. (2018, January 19\u201321). Density Based Recovery of Urban Power Lines Using Vehicle-Mounted LiDAR. Proceedings of the 2018 International Conference on Image and Vision Computing New Zealand (IVCNZ), Auckland, New Zealand.","DOI":"10.1109\/IVCNZ.2018.8634646"},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Liang, J., Zhang, J., Deng, K., Liu, Z., and Shi, Q. (2011, January 9\u201311). A New Power-Line Extraction Method Based on Airborne LiDAR Point Cloud Data. Proceedings of the 2011 International Symposium on Image and Data Fusion, Tengchong, China.","DOI":"10.1109\/ISIDF.2011.6024293"},{"key":"ref_27","unstructured":"Awrangjeb, M., Gao, Y., and Lu, G. (December, January 30). Point cloud data. Proceedings of the 2018 Digital Image Computing: Techniques and Applications, International Conference on Digital Image Computing: Techniques and Applications (DICTA), Canberra, Australia."},{"key":"ref_28","first-page":"1223","article-title":"Powerline three-dimensional reconstruction for lidar point cloud data","volume":"18","author":"Lai","year":"2014","journal-title":"J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2019.03.021","article-title":"Characterization and modeling of power line corridor elements from LiDAR point clouds","volume":"152","author":"Ortega","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","first-page":"30","article-title":"An automated extraction algorithm of power lines based on airborne laser scanning data","volume":"28","author":"Yin","year":"2012","journal-title":"Geogr. Geo-Inf. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. (2016). An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sens., 8.","DOI":"10.3390\/rs8060501"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1502\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:47:43Z","timestamp":1760161663000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/8\/1502"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,4,13]]},"references-count":31,"journal-issue":{"issue":"8","published-online":{"date-parts":[[2021,4]]}},"alternative-id":["rs13081502"],"URL":"https:\/\/doi.org\/10.3390\/rs13081502","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,4,13]]}}}