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dc.contributor.authorMunir, N
dc.contributor.authorAwrangjeb, M
dc.contributor.authorStantic, B
dc.date.accessioned2021-05-13T23:09:04Z
dc.date.available2021-05-13T23:09:04Z
dc.date.issued2020
dc.identifier.isbn9781728191089
dc.identifier.doi10.1109/DICTA51227.2020.9363391
dc.identifier.urihttp://hdl.handle.net/10072/404359
dc.description.abstractThe maintenance of high-voltage power lines rights-of-way due to vegetation intrusions is important for electric power distribution companies for safe and secure delivery of electricity. However, the monitoring becomes more challenging if power line corridor (PLC) exists in complex environment such as mountainous terrains or forests. To overcome these challenges, this paper aims to provide an automated method for extraction of individual pylons and monitoring of vegetation near the PLC in hilly terrain. The proposed method starts off by dividing the large dataset into small manageable datasets. A voxel grid is formed on each dataset to separate power lines from pylons and vegetation. The power line points are converted into a binary image to get the individual spans. These span points are used to find nearby vegetation and pylon points and individual pylons and vegetation are further separated using a statistical analysis. Finally, the height and location of extracted vegetation with reference to power lines are estimated and separated into danger and clearance zones. The experiment on two large Australian datasets shows that the proposed method provides high completeness and correctness of 96.5% and 99% for pylons, respectively. Moreover, the growing vegetation beneath and around the PLC that can harm the power lines is identified.
dc.publisherIEEE
dc.relation.ispartofconferencename2020 Digital Image Computing: Techniques and Applications (DICTA)
dc.relation.ispartofconferencetitle2020 Digital Image Computing: Techniques and Applications, DICTA 2020
dc.relation.ispartofdatefrom2020-11-29
dc.relation.ispartofdateto2020-12-02
dc.relation.ispartoflocationMelbourne, Australia
dc.titleAn improved method for pylon extraction and vegetation encroachment analysis in high voltage transmission lines using LiDAR data
dc.typeConference output
dcterms.bibliographicCitationMunir, N; Awrangjeb, M; Stantic, B, An improved method for pylon extraction and vegetation encroachment analysis in high voltage transmission lines using LiDAR data, 2020 Digital Image Computing: Techniques and Applications, DICTA 2020, 2020
dc.date.updated2021-05-13T23:06:29Z
dc.description.versionAccepted Manuscript (AM)
gro.rights.copyright© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
gro.hasfulltextFull Text
gro.griffith.authorAwrangjeb, Mohammad
gro.griffith.authorMunir, Nosheen
gro.griffith.authorStantic, Bela


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