{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,11,5]],"date-time":"2025-11-05T06:24:13Z","timestamp":1762323853889,"version":"build-2065373602"},"reference-count":33,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2015,9,9]],"date-time":"2015-09-09T00:00:00Z","timestamp":1441756800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"NSFC","doi-asserted-by":"publisher","award":["41271452"],"award-info":[{"award-number":["41271452"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Reconstructing three-dimensional model of the pylon from LiDAR (Light Detection And Ranging) point clouds automatically is one of the key techniques for facilities management GIS system of high-voltage nationwide transmission smart grid. This paper presents a model-driven three-dimensional pylon modeling (MD3DM) method using airborne LiDAR data. We start with constructing a parametric model of pylon, based on its actual structure and the characteristics of point clouds data. In this model, a pylon is divided into three parts: pylon legs, pylon body and pylon head. The modeling approach mainly consists of four steps. Firstly, point clouds of individual pylon are detected and segmented from massive high-voltage transmission corridor point clouds automatically. Secondly, an individual pylon is divided into three relatively simple parts in order to reconstruct different parts with different strategies. Its position and direction are extracted by contour analysis of the pylon body in this stage. Thirdly, the geometric features of the pylon head are extracted, from which the head type is derived with a SVM (Support Vector Machine) classifier. After that, the head is constructed by seeking corresponding model from pre-build model library. Finally, the body is modeled by fitting the point cloud to planes. Experiment results on several point clouds data sets from China Southern  high-voltage nationwide transmission grid from Yunnan Province to Guangdong Province show that the proposed approach can achieve the goal of automatic three-dimensional modeling of the pylon effectively.<\/jats:p>","DOI":"10.3390\/rs70911501","type":"journal-article","created":{"date-parts":[[2015,9,9]],"date-time":"2015-09-09T13:16:18Z","timestamp":1441804578000},"page":"11501-11524","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":34,"title":["A Model-Driven Approach for 3D Modeling of Pylon from Airborne LiDAR Data"],"prefix":"10.3390","volume":"7","author":[{"given":"Qingquan","family":"Li","sequence":"first","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"},{"name":"Shenzhen Key Laboratory of Spatial Smart Sensing and Services, Shenzhen University, Shenzhen 518060, China."},{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8537-2409","authenticated-orcid":false,"given":"Zhipeng","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0866-6678","authenticated-orcid":false,"given":"Qingwu","family":"Hu","sequence":"additional","affiliation":[{"name":"Collaborative Innovation Center of Geospatial Technology, Wuhan 430079, China"},{"name":"School of Remote Sensing and Information Engineering of Wuhan University,  Wuhan 430079, China"}]}],"member":"1968","published-online":{"date-parts":[[2015,9,9]]},"reference":[{"key":"ref_1","first-page":"137","article-title":"Lidar applications in the electrical power industry","volume":"XXXVII","author":"Xu","year":"2008","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"You, A., Han, X., Wang, X., and Tang, D. (2013, January 9\u201311). Applications of Lidar in Patrolling Electric-Power Lines. Proceedings of the 2013 International Conference on Technological Advances in Electrical, Electronics and Computer Engineering (TAEECE), Konya, Turkey.","DOI":"10.1109\/TAEECE.2013.6557205"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ussyshkin, R.V., Theriault, L., Sitar, M., and Kou, T. (2011, January 10\u201312). Advantages of airborne Lidar technology in power line asset management. Proceedings of the 2011 International Workshop on Multi-Platform\/Multi-Sensor Remote Sensing and Mapping (M2RSM), Xiamen, China.","DOI":"10.1109\/M2RSM.2011.5697427"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0924-2716(99)00004-0","article-title":"Two algorithms for extracting building models from raw laser altimetry data","volume":"54","author":"Maas","year":"1999","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","unstructured":"Tarsha-Kurdi, F., Landes, T., Grussenmeyer, P., and Koehl, M. Model-Driven and Data-Driven Approaches Using Lidar Data: Analysis and Comparison. Available online: https:\/\/halshs.archives-ouvertes.fr\/halshs-00264846\/document."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"7323","DOI":"10.3390\/s8117323","article-title":"A comprehensive automated 3d approach for building extraction, reconstruction, and regularization from airborne laser scanning point clouds","volume":"8","author":"Dorninger","year":"2008","journal-title":"Sensors"},{"key":"ref_7","first-page":"47","article-title":"3d building reconstruction from Lidar based on a cell decomposition approach","volume":"XXXVIII","author":"Kada","year":"2009","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Huang, H., Brenner, C., and Sester, M. (2011). 3d Building Roof Reconstruction from Point Clouds via Generative Models, ACM.","DOI":"10.1145\/2093973.2093977"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1016\/j.isprsjprs.2012.11.004","article-title":"Model driven reconstruction of roofs from sparse Lidar point clouds","volume":"76","author":"Henn","year":"2013","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"381","DOI":"10.1145\/358669.358692","article-title":"Random sample consensus: A paradigm for model fitting with applications to image analysis and automated cartography","volume":"24","author":"Fischler","year":"1981","journal-title":"Commun. ACM"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Lafarge, F., and Mallet, C. (2011, January 6\u201313). Building Large Urban Environments from Unstructured Point Data. Proceedings of the 2011 IEEE International Conference on Computer Vision (ICCV), Barcelona, Spain.","DOI":"10.1109\/ICCV.2011.6126353"},{"key":"ref_12","first-page":"296","article-title":"Automatic 3d building reconstruction from airborne laser scanning and cadastral data using hough transform","volume":"35","author":"Overby","year":"2004","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_13","unstructured":"Tarsha-Kurdi, F., Landes, T., and Grussenmeyer, P. (2007, January 12\u201314). Hough-Transform and Extended Ransac Algorithms for Automatic Detection of 3d Building Roof Planes from Lidar Data. Proceedings of ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007, Espoo, Finland."},{"key":"ref_14","first-page":"97","article-title":"Extended RANSAC algorithm for automatic detection of building roof planes from Lidar data","volume":"21","author":"Landes","year":"2008","journal-title":"Photogramm. J. Finl."},{"key":"ref_15","unstructured":"Verma, V., Kumar, R., and Hsu, S. (2006, January 17\u201322). 3d Building Detection and Modeling from Aerial Lidar Data. Proceedings of the 2006 IEEE Computer Society Conference on 2006 Computer Vision and Pattern Recognition, New York, NY, USA."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Zhou, Q.-Y., and Neumann, U. (2009, January 20\u201325). A Streaming Framework for Seamless Building Reconstruction from Large-Scale Aerial Lidar Data. Proceedings of the IEEE Conference on 2009 Computer Vision and Pattern Recognition, CVPR 2009, Miami, FL, USA.","DOI":"10.1109\/CVPR.2009.5206760"},{"key":"ref_17","first-page":"49","article-title":"Target graph matching for building reconstruction","volume":"9","author":"Elberink","year":"2009","journal-title":"Proc. Laserscanning"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1109\/TGRS.2009.2030180","article-title":"Segmentation and reconstruction of polyhedral building roofs from aerial Lidar point clouds","volume":"48","author":"Sampath","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1007\/s11263-012-0517-8","article-title":"Creating large-scale city models from 3d-point clouds: A robust approach with hybrid representation","volume":"99","author":"Lafarge","year":"2012","journal-title":"Int. J. Comput. Vis."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"225","DOI":"10.1111\/cgf.12042","article-title":"Surface reconstruction through point set structuring","volume":"32","author":"Lafarge","year":"2013","journal-title":"Comput. Graph. Forum."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"37","DOI":"10.5194\/isprsannals-II-3-W3-37-2013","article-title":"Feature-driven 3d building modeling using planar halfspaces","volume":"II-3\/W3","author":"Kada","year":"2013","journal-title":"ISPRS Ann. Photogramm. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"189","DOI":"10.5194\/isprsannals-II-3-189-2014","article-title":"3D building adjustment using planar half-space regularities","volume":"1","author":"Wichmann","year":"2014","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"275","DOI":"10.1016\/j.isprsjprs.2015.01.002","article-title":"Flexible building primitives for 3d building modeling","volume":"101","author":"Xiong","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"227","DOI":"10.1016\/j.isprsjprs.2014.01.007","article-title":"A graph edit dictionary for correcting errors in roof topology graphs reconstructed from point clouds","volume":"93","author":"Xiong","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_25","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_26","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_27","first-page":"126","article-title":"3D classification of power-line scene from airborne laser scanning data using random forests","volume":"38","author":"Kim","year":"2010","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_28","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_29","unstructured":"Huiming, S. (2011). Research and Application of Optimal Design Method of High Voltage Transmission Tower Structure, Guangzhou University."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1145\/174462.156635","article-title":"Three-dimensional alpha shapes","volume":"13","author":"Edelsbrunner","year":"1994","journal-title":"ACM Trans. Graphics"},{"key":"ref_31","first-page":"692","article-title":"Algorithms study of building boundary extraction and normalization based on Lidar data","volume":"5","author":"Shen","year":"2008","journal-title":"J. Remote Sens."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"273","DOI":"10.1007\/BF00994018","article-title":"Support-vector networks","volume":"20","author":"Cortes","year":"1995","journal-title":"Mach. Learn."},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Chang, C.-C., and Lin, C.-J. (2011). LIBSVM: A library for support vector machines. ACM Trans. Intell. Syst. Technol.","DOI":"10.1145\/1961189.1961199"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11501\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T20:48:13Z","timestamp":1760215693000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/9\/11501"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,9,9]]},"references-count":33,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2015,9]]}},"alternative-id":["rs70911501"],"URL":"https:\/\/doi.org\/10.3390\/rs70911501","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2015,9,9]]}}}