{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,28]],"date-time":"2026-01-28T05:27:09Z","timestamp":1769578029943,"version":"3.49.0"},"reference-count":22,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2014,11,13]],"date-time":"2014-11-13T00:00:00Z","timestamp":1415836800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>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.<\/jats:p>","DOI":"10.3390\/rs61111267","type":"journal-article","created":{"date-parts":[[2014,11,13]],"date-time":"2014-11-13T11:22:30Z","timestamp":1415877750000},"page":"11267-11282","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":86,"title":["Fully-Automated Power Line Extraction from Airborne Laser Scanning Point Clouds in Forest Areas"],"prefix":"10.3390","volume":"6","author":[{"given":"Lingli","family":"Zhu","sequence":"first","affiliation":[{"name":"Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland"}]},{"given":"Juha","family":"Hyypp\u00e4","sequence":"additional","affiliation":[{"name":"Finnish Geodetic Institute, P.O. Box 15, FI-02431 Masala, Finland"}]}],"member":"1968","published-online":{"date-parts":[[2014,11,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"387","DOI":"10.1109\/LGRS.2007.895714","article-title":"Automatic extraction of power lines from aerial images","volume":"4","author":"Yan","year":"2007","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/S0924-2716(99)00008-8","article-title":"Processing of laser scanner data\u2014Algorithms and applications","volume":"54","author":"Axelsson","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_3","unstructured":"Melzer, T., and Briese, C. (2004, January 17\u201318). Extraction and modeling of power lines from ALS point clouds. Proceedings of the 28th Workshop of the Austrian Association for Pattern Recognition, Hagenberg, Austria."},{"key":"ref_4","unstructured":"Vosselman, G., and Maas, H.G. (2010). Airborne and Terrestrial Laser Scanning, Whittles."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"821","DOI":"10.14358\/PERS.79.9.821","article-title":"Power-line scene classification with point-based feature from airborne LiDAR data","volume":"79","author":"Kim","year":"2013","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_6","unstructured":"Clode, S., and Rottensteiner, F. (2005, January 21). Classification of trees and power lines from medium resolution airborne lasers canner data in urban environments. Proceedings of the APRS Workshop on Digital Image Computing (WDIC), Brisbane, Australia."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"222","DOI":"10.1109\/LGRS.2005.863390","article-title":"Extracting transmission lines from airborne LIDAR data","volume":"3","author":"McLaughlin","year":"2006","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_8","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 IEEE Digital Image Computing: Techniques and Applications, 2009, DICTA\u201909, Melbourne, Australia.","DOI":"10.1109\/DICTA.2009.83"},{"key":"ref_9","first-page":"105","article-title":"Automatic 3D Powerline reconstruction using airborne lidar data","volume":"XXXVIII","author":"Jwa","year":"2009","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_10","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 IEEE 2011 International Symposium on Image and Data Fusion (ISIDF), Tengchong, China.","DOI":"10.1109\/ISIDF.2011.6024293"},{"key":"ref_11","first-page":"253","article-title":"Random forests based multiple classifier system for power-line scene classification","volume":"XXXVIII-5\/W12","author":"Kim","year":"2011","journal-title":"ISPRS Int. Arch. Photogramm., Remote Sens. Spat. Inf. Sci."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"167","DOI":"10.5194\/isprsannals-I-3-167-2012","article-title":"Automatic powerline scene classification and reconstruction using airborne lidar data","volume":"1\u20133","author":"Sohn","year":"2012","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"677","DOI":"10.1007\/s00138-009-0206-y","article-title":"Toward automatic power line detection for a UAV surveillance system using pulse coupled neural filter and an improved hough transform","volume":"21","author":"Li","year":"2010","journal-title":"Mach. Vis. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1227","DOI":"10.14358\/PERS.78.11.1227","article-title":"A piece-wise catenary curve model growing for 3D power line reconstruction","volume":"78","author":"Jwa","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.3390\/rs3071406","article-title":"Photorealistic building reconstruction from mobile laser scanning data","volume":"3","author":"Zhu","year":"2011","journal-title":"Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"641","DOI":"10.3390\/rs2030641","article-title":"Detection of vertical pole-like objects in a road environment using vehicle-based laser scanning data","volume":"2","author":"Jaakkola","year":"2010","journal-title":"Remote Sens."},{"key":"ref_17","unstructured":"Kukko, A. (2009). Road Environment Mapper\u20143D Data Capturing with Mobile Mapping. [Licentiate\u2019s Thesis, Helsinki University of Technology]."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"5238","DOI":"10.3390\/s8095238","article-title":"Retrieval algorithms for road surface modelling using laser-based mobile mapping","volume":"8","author":"Jaakkola","year":"2008","journal-title":"Sensors"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"5839","DOI":"10.1080\/01431161.2012.674229","article-title":"Automated extraction of street-scene objects from mobile lidar point clouds","volume":"33","author":"Yang","year":"2012","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"3075","DOI":"10.3390\/rs6043075","article-title":"The use of airborne and mobile laser scanning for modelling railway environments in 3D","volume":"6","author":"Zhu","year":"2014","journal-title":"Remote Sens."},{"key":"ref_22","unstructured":"Electricity for Europe. Available online:http:\/\/ www.eurelectric.org."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/11\/11267\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T21:09:18Z","timestamp":1760216958000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/11\/11267"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,11,13]]},"references-count":22,"journal-issue":{"issue":"11","published-online":{"date-parts":[[2014,11]]}},"alternative-id":["rs61111267"],"URL":"https:\/\/doi.org\/10.3390\/rs61111267","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,11,13]]}}}