{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,20]],"date-time":"2026-03-20T15:25:43Z","timestamp":1774020343887,"version":"3.50.1"},"reference-count":49,"publisher":"MDPI AG","issue":"10","license":[{"start":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T00:00:00Z","timestamp":1620691200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Ministerstvo \u0161kolstva, vedy v\u00fdskumu a \u0161portu Slovenskej republiky","award":["ITMS 26220220156"],"award-info":[{"award-number":["ITMS 26220220156"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The advance in remote sensing techniques, especially the development of LiDAR scanning systems, allowed the development of new methods for power line corridor surveys using a digital model of the powerline and its surroundings. The advanced diagnostic techniques based on the acquired conductor geometry recalculation to extreme operating and climatic conditions were proposed using this digital model. Although the recalculation process is relatively easy and straightforward, the uncertainties of input parameters used for the recalculation can significantly compromise such recalculation accuracy. This paper presents a systematic analysis of the accuracy of the recalculation affected by the inaccuracies of the conductor state equation input variables. The sensitivity of the recalculation to the inaccuracy of five basic input parameters was tested (initial temperature and mechanical tension, elasticity modulus, specific gravity load and tower span) by comparing the conductor sag values when input parameters were affected by a specific inaccuracy with an ideal sag-tension table. The presented tests clearly showed that the sag recalculation inaccuracy must be taken into account during the safety assessment process, as the sag deviation can, in some cases, reach values comparable to the minimal clearance distances specified in the technical standards.<\/jats:p>","DOI":"10.3390\/rs13101880","type":"journal-article","created":{"date-parts":[[2021,5,11]],"date-time":"2021-05-11T11:30:16Z","timestamp":1620732616000},"page":"1880","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Advanced Power Line Diagnostics Using Point Cloud Data\u2014Possible Applications and Limits"],"prefix":"10.3390","volume":"13","author":[{"given":"Marek","family":"Siranec","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Information Technology, University of \u017dilina, Univerzitn\u00e1 1, 010 26 \u017dilina, Slovakia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0325-5397","authenticated-orcid":false,"given":"Marek","family":"H\u00f6ger","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Information Technology, University of \u017dilina, Univerzitn\u00e1 1, 010 26 \u017dilina, Slovakia"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0337-3879","authenticated-orcid":false,"given":"Alena","family":"Otcenasova","sequence":"additional","affiliation":[{"name":"Faculty of Electrical Engineering and Information Technology, University of \u017dilina, Univerzitn\u00e1 1, 010 26 \u017dilina, Slovakia"}]}],"member":"1968","published-online":{"date-parts":[[2021,5,11]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"052025","DOI":"10.1088\/1757-899X\/382\/5\/052025","article-title":"Application of LiDAR technology in power line inspection","volume":"382","author":"Li","year":"2018","journal-title":"IOP Conf. Ser. Mater. Sci. Eng."},{"key":"ref_2","first-page":"119","article-title":"Cloud-based solution for nationwide power line mapping","volume":"XLII-2\/W13","author":"Toschi","year":"2019","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1016\/j.isprsjprs.2016.04.011","article-title":"Remote sensing methods for power line corridor surveys","volume":"119","author":"Matikainen","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"You, A., Wang, X., Han, X., and Tang, D. (2013, January 9\u201311). Applications of LiDAR in patrolling electric-power lines. Proceedings of the 2013 The International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), Konya, Turkey.","DOI":"10.1109\/TAEECE.2013.6557205"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.epsr.2012.07.015","article-title":"Vegetation encroachment monitoring for transmission lines right-of-ways: A survey","volume":"95","author":"Ahmad","year":"2013","journal-title":"Electr. Power Syst. Res."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"102802","DOI":"10.1016\/j.autcon.2019.03.023","article-title":"Power line mapping technique using all-terrain mobile laser scanning","volume":"105","author":"Kukko","year":"2019","journal-title":"Autom. Constr."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Wang, Y., Chen, Q., Liu, L., Li, X., Sangaiah, A.K., and Li, K. (2018). Systematic Comparison of Power Line Classification Methods from ALS and MLS Point Cloud Data. Remote. Sens., 10.","DOI":"10.3390\/rs10081222"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"227","DOI":"10.5194\/isprs-annals-IV-2-W7-227-2019","article-title":"Automatic extraction of power lines from UAV lidar point clouds using a novel spatial feature","volume":"IV-2\/W7","author":"Zhou","year":"2019","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_9","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":"I-3","author":"Sohn","year":"2012","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","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_11","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, Yunnan, China.","DOI":"10.1109\/ISIDF.2011.6024293"},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Liu, Y., Li, Z., Hayward, R., Walker, R., and Jin, H. (2009). Classification of Airborne LIDAR Intensity Data Using Statistical Analysis and Hough Transform with Application to Power Line Corridors. Digit. Image Comput. Tech. Appl., 462\u2013467.","DOI":"10.1109\/DICTA.2009.83"},{"key":"ref_13","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_14","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_15","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_16","doi-asserted-by":"crossref","unstructured":"Guo, B., Li, Q., Huang, X., and Wang, C. (2016). An Improved Method for Power-Line Reconstruction from Point Cloud Data. Remote Sens., 8.","DOI":"10.3390\/rs8010036"},{"key":"ref_17","first-page":"407","article-title":"Hough-transform and extended RANSAC algorithms for automatic detection of 3d building roof planes from Lidar data","volume":"XXXVI","author":"Kurdi","year":"2007","journal-title":"ISPRS Int. Arch. Photogramm. Remote Sens. Spat. Inf. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1111\/phor.12296","article-title":"An improved RANSAC algorithm for extracting roof planes from airborne lidar data","volume":"35","author":"Sevgen","year":"2020","journal-title":"Photogramm. Rec."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"821","DOI":"10.14358\/PERS.79.9.821","article-title":"Point-based Classification of Power Line Corridor Scene Using Random Forests","volume":"79","author":"Kim","year":"2013","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"165","DOI":"10.5194\/isprs-annals-IV-2-W4-165-2017","article-title":"Airborne lidar power line classification based on spatial topological structure characteristics","volume":"IV-2\/W4","author":"Wang","year":"2017","journal-title":"ISPRS Ann. Photogramm. Remote. Sens. Spat. Inf. Sci."},{"key":"ref_22","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_23","doi-asserted-by":"crossref","unstructured":"Guo, B., Huang, X., Li, Q., Zhang, F., Zhu, J., and Wang, C. (2016). A Stochastic Geometry Method for Pylon Reconstruction from Airborne LiDAR Data. Remote Sens., 8.","DOI":"10.3390\/rs8030243"},{"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","first-page":"3379","DOI":"10.1109\/TGRS.2010.2046905","article-title":"Evaluation of Aerial Remote Sensing Techniques for Vegetation Management in Power-Line Corridors","volume":"48","author":"Mills","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Jardini, M.G.M., Jardini, J.A., Crispino, F., Sim\u00f5es, A.J.M., De Souza, J.M.S., and Dos Santos, W.L. (2018, January 16\u201317). Vegetation detection close to transmission lines using cloud data points from lidar in Brazil. Proceedings of the Modelling, Simulation and Identification\/858: Intelligent Systems and Control, Calgary, AB, Canada.","DOI":"10.2316\/P.2018.857-003"},{"key":"ref_27","unstructured":"Clode, S., and Rottensteiner, F. (2005, January 21). Classification of trees and powerlines from medium resolution airborne laserscanner data in urban environments. Proceedings of the Workshop on Digital Image Computing 2005 (WDIC2005), Brisbane, Australia."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Frank, M., Pan, Z., Raber, B., and Lenart, C. (2010, January 14\u201316). Vegetation management of utility corridors using high-resolution hyperspectral imaging and LiDAR. Proceedings of the 2010 2nd Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing, Reykjavik, Iceland.","DOI":"10.1109\/WHISPERS.2010.5594887"},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Chen, C., Yang, B., Song, S., Peng, X., and Huang, R. (2018). Automatic Clearance Anomaly Detection for Transmission Line Corridors Utilizing UAV-Borne LIDAR Data. Remote Sens., 10.","DOI":"10.3390\/rs10040613"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"165409","DOI":"10.1109\/ACCESS.2020.3022670","article-title":"Power Line Simulation for Safety Distance Detection Using Point Clouds","volume":"8","author":"Zhang","year":"2020","journal-title":"IEEE Access"},{"key":"ref_31","unstructured":"CIGRE (2016). Sag-Tension Calculation Methods for Overhead Lines, CIGRE."},{"key":"ref_32","unstructured":"Lindberg, E. (2011). The Overhead Line Sag Dependence on Weather Parameters and Line Current. [Master\u2019s Thesis, Uppsala University]."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"2040","DOI":"10.1109\/TPWRD.2014.2325862","article-title":"Impact of Data Errors on Sag Calculation Accuracy for Overhead Transmission Line","volume":"29","author":"Polevoy","year":"2014","journal-title":"IEEE Trans. Power Deliv."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"2236","DOI":"10.1109\/TPWRD.2018.2831080","article-title":"Conductor Temperature Estimation and Prediction at Thermal Transient State in Dynamic Line Rating Application","volume":"33","author":"Alvarez","year":"2018","journal-title":"IEEE Trans. Power Deliv."},{"key":"ref_35","unstructured":"\u0160iranec, M., H\u00f6ger, M., and Ot\u010den\u00e1\u0161ov\u00e1, A. (2019, January 16\u201318). Evaluation of power line parameter estimation accuracy based on data from airborne LiDAR. Proceedings of the 10th International Scientific Symposium on Electrical Power Engineering, Elektroener-Getika 2019, Star\u00e1 Lesn\u00e1, Slovakia."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Michael, M., Stephan, P., and Stefan, J. (2008, January 21\u201324). Elongation of overhead line conductors under combined mechanical and thermal Stress. Proceedings of the 2008 International Conference on Condition Monitoring and Diagnosis, Beijing, China.","DOI":"10.1109\/CMD.2008.4580375"},{"key":"ref_37","first-page":"1380","article-title":"A method for the sag-tension calculation in electrical overhead lines","volume":"6","author":"Albizu","year":"2011","journal-title":"Int. Rev. Electr. Eng."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"64","DOI":"10.1016\/j.culher.2017.01.010","article-title":"Survey and seismic vulnerability assessment of the Baptistery of San Giovanni in Tumba (Italy)","volume":"26","author":"Fortunato","year":"2017","journal-title":"J. Cult. Heritage"},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Stepinac, M., and Ga\u0161parovi\u0107, M. (2020). A Review of Emerging Technologies for an Assessment of Safety and Seismic Vulnerability and Damage Detection of Existing Masonry Structures. Appl. Sci., 10.","DOI":"10.3390\/app10155060"},{"key":"ref_40","unstructured":"Nakajima, T., Hirata, Y., Hiroshima, T., Furuya, N., Satoshi, T., Tsuyuki, S., and Shiraishi, N. (2009). A Growth Prediction System for Regional Forest Resources Derived from LiDAR Data, Silvilaser."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Rybansky, M., Brenova, M., Cermak, J., Van Genderen, J., and Sivertun, \u00c5. (2016, January 13\u201314). Vegetation structure determination using LIDAR data and the forest growth parameters. Proceedings of the IOP Conference Series: Earth and Environmental Science, Kuala Lumpur, Malaysia.","DOI":"10.1088\/1755-1315\/37\/1\/012031"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"162","DOI":"10.1016\/j.geomorph.2010.03.016","article-title":"Detection and spatial prediction of rockfalls by means of terrestrial laser scanner monitoring","volume":"119","author":"Calvet","year":"2010","journal-title":"Geomorphology"},{"key":"ref_43","unstructured":"Ot\u010den\u00e1\u0161ov\u00e1, A. (2005). Mechanics of Overhead Power Lines, EDIS, University of \u017dilina. University Textbook."},{"key":"ref_44","unstructured":"Varga, L., Le\u0161\u010dinsk\u00fd, P., and Be\u0148a, \u013d. (2019). Calculation of Mechanical Conditions of Overhead Power Lines, Technical University of Ko\u0161ice. University Textbook, Mercury-Sm\u00e9kal."},{"key":"ref_45","first-page":"134","article-title":"Direct monitoring methods of overhead line conductor temperature","volume":"37","author":"Pavlinic","year":"2017","journal-title":"Eng. Rev."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"921","DOI":"10.1007\/s00202-019-00831-8","article-title":"Temperature calculation of overhead power line conductors based on CIGRE Technical Brochure 601 in Slovakia","volume":"101","year":"2019","journal-title":"Electr. Eng."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Bockarjova, M., and Andersson, G. (2007, January 1\u20135). Transmission Line Conductor Temperature Impact on State Estimation Accuracy. Proceedings of the 2007 IEEE Lausanne Power Tech, Lausanne, Switzerland.","DOI":"10.1109\/PCT.2007.4538401"},{"key":"ref_48","unstructured":"Taylor, J.R. (1997). An Introduction to Error Analysis, University Science Books. [2nd ed.]."},{"key":"ref_49","unstructured":"EN 50341-1:2012 (2012). Overhead Electrical Lines Exceeding AC 1 kV\u2014Part 1: General Requirements\u2014Common Specifications, CENELEC."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1880\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T05:59:23Z","timestamp":1760162363000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/13\/10\/1880"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,5,11]]},"references-count":49,"journal-issue":{"issue":"10","published-online":{"date-parts":[[2021,5]]}},"alternative-id":["rs13101880"],"URL":"https:\/\/doi.org\/10.3390\/rs13101880","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2021,5,11]]}}}