{"id":{"repo_id":"york","oai_identifier":"oai:yorkspace.library.yorku.ca:10315/30746"},"canonical_url":"https://search.dev.ndltd.org/etd/york/oai:yorkspace.library.yorku.ca:10315/30746","repository":{"repo_id":"york","name":"York University","base_url":"https://yorkspace.library.yorku.ca/oai/request"},"display":{"title":"Accuracy Improvement of Terrestrial Mobile Lidar System in Engineering Surveys","abstract":"In this thesis, a number of effective algorithms and strategies were developed to improve the accuracy of terrestrial mobile LiDAR solutions in the field of engineering surveys. A detailed analysis for error budget of the terrestrial mobile LiDAR system has been presented in order to well interpret the effects of individual error sources. Firstly, the 3D conformal coordinate transformation (3DCCT) through Least Squares Method (LSM) was applied by employing the ground control points incorporating with feature constraints. Secondly, the multistrip adjustment (MA) algorithm was developed by taking advantage of the overlapped data strips and the repeated data acquisition over the same survey area using both of tie points and tie features. Lastly, the boresight angles of a terrestrial LiDAR system was preliminarily calibrated by using the planar and/or line features of two scans acquired during consecutive runs in opposite driving directions at the post-processing stage proposed by Keller et al. (2013).","abstract_html":"In this thesis, a number of effective algorithms and strategies were developed to improve the accuracy of terrestrial mobile LiDAR solutions in the field of engineering surveys. A detailed analysis for error budget of the terrestrial mobile LiDAR system has been presented in order to well interpret the effects of individual error sources. Firstly, the 3D conformal coordinate transformation (3DCCT) through Least Squares Method (LSM) was applied by employing the ground control points incorporating with feature constraints. Secondly, the multistrip adjustment (MA) algorithm was developed by taking advantage of the overlapped data strips and the repeated data acquisition over the same survey area using both of tie points and tie features. Lastly, the boresight angles of a terrestrial LiDAR system was preliminarily calibrated by using the planar and/or line features of two scans acquired during consecutive runs in opposite driving directions at the post-processing stage proposed by Keller et al. 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Secondly, the multistrip adjustment (MA) algorithm was developed by taking advantage of the overlapped data strips and the repeated data acquisition over the same survey area using both of tie points and tie features. Lastly, the boresight angles of a terrestrial LiDAR system was preliminarily calibrated by using the planar and/or line features of two scans acquired during consecutive runs in opposite driving directions at the post-processing stage proposed by Keller et al. 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Secondly, the multistrip adjustment (MA) algorithm was developed by taking advantage of the overlapped data strips and the repeated data acquisition over the same survey area using both of tie points and tie features. Lastly, the boresight angles of a terrestrial LiDAR system was preliminarily calibrated by using the planar and/or line features of two scans acquired during consecutive runs in opposite driving directions at the post-processing stage proposed by Keller et al. (2013)."],"dc:identifier.uri":["http://hdl.handle.net/10315/30746"],"dc:language.iso":["en"],"dc:rights":["Author owns copyright, except where explicitly noted. Please contact the author directly with licensing requests."],"dc:subject":["Remote sensing"],"dc:title":["Accuracy Improvement of Terrestrial Mobile Lidar System in Engineering Surveys"],"dc:type":["Electronic Thesis or Dissertation"]},"updated_at":"2026-07-24T06:34:00Z"}