{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,27]],"date-time":"2026-05-27T21:12:21Z","timestamp":1779916341752,"version":"3.53.1"},"reference-count":37,"publisher":"MDPI AG","issue":"18","license":[{"start":{"date-parts":[[2019,9,4]],"date-time":"2019-09-04T00:00:00Z","timestamp":1567555200000},"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>Laser scanning is an effective tool for acquiring geometric attributes of trees and vegetation, which lays a solid foundation for 3-dimensional tree modelling. Existing studies on tree modelling from laser scanning data are vast. However, some works cannot guarantee sufficient modelling accuracy, while some other works are mainly rule-based and therefore highly depend on user inputs. In this paper, we propose a novel method to accurately and automatically reconstruct detailed 3D tree models from laser scans. We first extract an initial tree skeleton from the input point cloud by establishing a minimum spanning tree using the Dijkstra shortest-path algorithm. Then, the initial tree skeleton is pruned by iteratively removing redundant components. After that, an optimization-based approach is performed to fit a sequence of cylinders to approximate the geometry of the tree branches. Experiments on various types of trees from different data sources demonstrate the effectiveness and robustness of our method. The overall fitting error (i.e., the distance between the input points and the output model) is less than 10 cm. The reconstructed tree models can be further applied in the precise estimation of tree attributes, urban landscape visualization, etc. The source code of this work is freely available at https:\/\/github.com\/tudelft3d\/adtree.<\/jats:p>","DOI":"10.3390\/rs11182074","type":"journal-article","created":{"date-parts":[[2019,9,5]],"date-time":"2019-09-05T03:22:36Z","timestamp":1567653756000},"page":"2074","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":112,"title":["AdTree: Accurate, Detailed, and Automatic Modelling of Laser-Scanned Trees"],"prefix":"10.3390","volume":"11","author":[{"given":"Shenglan","family":"Du","sequence":"first","affiliation":[{"name":"3D Geoinformation Research Group, Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Roderik","family":"Lindenbergh","sequence":"additional","affiliation":[{"name":"Department of Geoscience and Remote Sensing, Delft University of Technology, 2628 CN Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1251-8654","authenticated-orcid":false,"given":"Hugo","family":"Ledoux","sequence":"additional","affiliation":[{"name":"3D Geoinformation Research Group, Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1393-7279","authenticated-orcid":false,"given":"Jantien","family":"Stoter","sequence":"additional","affiliation":[{"name":"3D Geoinformation Research Group, Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Liangliang","family":"Nan","sequence":"additional","affiliation":[{"name":"3D Geoinformation Research Group, Faculty of Architecture and the Built Environment, Delft University of Technology, 2628 BL Delft, The Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2019,9,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Deussen, O., Hanrahan, P., Lintermann, B., M\u011bch, R., Pharr, M., and Prusinkiewicz, P. (1998, January 19\u201324). Realistic modeling and rendering of plant ecosystems. Proceedings of the 25th Annual Conference on Computer Graphics and Interactive Techniques, Orlando, FL, USA.","DOI":"10.1145\/280814.280898"},{"key":"ref_2","first-page":"460","article-title":"Forestry applications of airborne laser scanning","volume":"27","author":"Maltamo","year":"2014","journal-title":"Concept Case Stud. Manag. For Ecosys"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"4725","DOI":"10.1080\/01431161.2010.494184","article-title":"A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing","volume":"32","author":"Ke","year":"2011","journal-title":"Int. J. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"969","DOI":"10.1109\/36.921414","article-title":"A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners","volume":"39","author":"Hyyppa","year":"2001","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"4753","DOI":"10.3390\/rs70404753","article-title":"Object-based approach for multi-scale mangrove composition mapping using multi-resolution image datasets","volume":"7","author":"Kamal","year":"2015","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"720","DOI":"10.1145\/1015706.1015785","article-title":"Volumetric reconstruction and interactive rendering of trees from photographs","volume":"23","author":"Martin","year":"2004","journal-title":"ACM Trans. Gr. (ToG)"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/38.920627","article-title":"Reconstructing 3D tree models from instrumented photographs","volume":"21","author":"Shlyakhter","year":"2001","journal-title":"IEEE Comput. Gr. Appl."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"599","DOI":"10.1145\/1141911.1141929","article-title":"Image-based plant modeling","volume":"25","author":"Quan","year":"2006","journal-title":"ACM Trans. Gr. (TOG)"},{"key":"ref_9","unstructured":"Guo, J., Xu, S., Yan, D.M., Cheng, Z., Jaeger, M., and Zhang, X. (2018). Realistic Procedural Plant Modeling from Multiple View Images. IEEE Trans. Vis. Comput. Gr."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.isprsjprs.2016.01.006","article-title":"Terrestrial laser scanning in forest inventories","volume":"115","author":"Liang","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"4323","DOI":"10.3390\/rs6054323","article-title":"Tree stem and height measurements using terrestrial laser scanning and the RANSAC algorithm","volume":"6","author":"Olofsson","year":"2014","journal-title":"Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1016\/S0034-4257(03)00008-7","article-title":"Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America","volume":"85","author":"Brandtberg","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/S0034-4257(03)00140-8","article-title":"Identifying species of individual trees using airborne laser scanner","volume":"90","author":"Holmgren","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Wang, D., Hollaus, M., Puttonen, E., and Pfeifer, N. (2016). Automatic and self-adaptive stem reconstruction in landslide-affected forests. Remote Sens., 8.","DOI":"10.3390\/rs8120974"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"4245","DOI":"10.3390\/f6114245","article-title":"SimpleTree\u2014An efficient open source tool to build tree models from TLS clouds","volume":"6","author":"Hackenberg","year":"2015","journal-title":"Forests"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"491","DOI":"10.3390\/rs5020491","article-title":"Fast automatic precision tree models from terrestrial laser scanner data","volume":"5","author":"Raumonen","year":"2013","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1283","DOI":"10.1007\/s00371-010-0520-4","article-title":"SkelTre","volume":"26","author":"Bucksch","year":"2010","journal-title":"Vis. Comput."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Yan, D.M., Wintz, J., Mourrain, B., Wang, W., Boudon, F., and Godin, C. (2009, January 19\u201321). Efficient and robust reconstruction of botanical branching structure from laser scanned points. Proceedings of the 2009 11th IEEE International Conference on Computer-Aided Design and Computer Graphics, Huangshan, China.","DOI":"10.1109\/CADCG.2009.5246837"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1145\/1289603.1289610","article-title":"Knowledge and heuristic-based modeling of laser-scanned trees","volume":"26","author":"Xu","year":"2007","journal-title":"ACM Trans. Gr. (TOG)"},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Verroust, A., and Lazarus, F. (1999, January 1\u20134). Extracting skeletal curves from 3D scattered data. Proceedings of the Shape Modeling International\u201999, International Conference on Shape Modeling and Applications, Aizu-Wakamatsu, Japan.","DOI":"10.1109\/SMA.1999.749340"},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"4271","DOI":"10.3390\/s140304271","article-title":"PypeTree: A tool for reconstructing tree perennial tissues from point clouds","volume":"14","author":"Delagrange","year":"2014","journal-title":"Sensors"},{"key":"ref_22","first-page":"143","article-title":"Defining and computing curve-skeletons with medial geodesic function","volume":"6","author":"Dey","year":"2006","journal-title":"Symp. Geom. Process."},{"key":"ref_23","first-page":"151","article-title":"Automatic reconstruction of tree skeletal structures from point clouds","volume":"29","author":"Livny","year":"2010","journal-title":"ACM Trans. Gr. (TOG)"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Xu, Y., Sun, Z., Hoegner, L., Stilla, U., and Yao, W. (2018, January 19\u201320). Instance Segmentation of Trees in Urban Areas from MLS Point Clouds Using Supervoxel Contexts and Graph-Based Optimization. Proceedings of the 2018 10th IAPR Workshop on Pattern Recognition in Remote Sensing, Beijing, China.","DOI":"10.1109\/PRRS.2018.8486220"},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Zhou, H., Shenoy, N., and Nicholls, W. (2001, January 2). Efficient minimum spanning tree construction without Delaunay triangulation. Proceedings of the 2001 Asia and South Pacific Design Automation Conference, Yokohama, Japan.","DOI":"10.1145\/370155.370320"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"790","DOI":"10.1109\/34.400568","article-title":"Mean shift, mode seeking, and clustering","volume":"17","author":"Cheng","year":"1995","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"ref_27","first-page":"161","article-title":"Frequent subtree mining\u2014An overview","volume":"66","author":"Chi","year":"2005","journal-title":"Fundam. Inf."},{"key":"ref_28","unstructured":"Wu, S.T., and Marquez, M.R.G. (2003, January 12\u201315). A non-self-intersection Douglas-Peucker algorithm. Proceedings of the 16th Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI 2003), Sao Carlos, Brazil."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"4581","DOI":"10.3390\/rs70404581","article-title":"Analysis of geometric primitives in quantitative structure models of tree stems","volume":"7","author":"Markku","year":"2015","journal-title":"Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"130","DOI":"10.1016\/j.jmsy.2008.07.004","article-title":"Least squares fitting of analytic primitives on a GPU","volume":"27","author":"Panyam","year":"2008","journal-title":"J. Manuf. Syst."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"632","DOI":"10.1016\/j.measurement.2019.01.095","article-title":"Robust cylinder fitting in laser scanning point cloud data","volume":"138","author":"Nurunnabi","year":"2019","journal-title":"Measurement"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"431","DOI":"10.1137\/0111030","article-title":"An algorithm for least-squares estimation of nonlinear parameters","volume":"11","author":"Marquardt","year":"1963","journal-title":"J. Soc. Indust. Appl. Math."},{"key":"ref_33","unstructured":"(2018, September 01). Boost. Available online: https:\/\/www.boost.org\/doc\/libs\/1_66_0\/libs\/graph\/doc\/index.html."},{"key":"ref_34","unstructured":"(2019, March 01). Easy3D. Available online: https:\/\/github.com\/LiangliangNan\/Easy3D."},{"key":"ref_35","unstructured":"(2018, September 01). Mapple. Available online: https:\/\/3d.bk.tudelft.nl\/liangliang\/software.html."},{"key":"ref_36","unstructured":"(2019, January 01). AHN Dataset. Available online: https:\/\/www.pdok.nl\/attenderingsservice-rss\/-\/asset_publisher\/mvZkjafth739\/content\/actueel-hoogtebestand-nederland-ahn3-."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Zhang, W., Wan, P., Wang, T., Cai, S., Chen, Y., Jin, X., and Yan, G. (2019). A Novel Approach for the Detection of Standing Tree Stems from Plot-Level Terrestrial Laser Scanning Data. Remote Sens., 11.","DOI":"10.3390\/rs11020211"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2074\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T13:16:39Z","timestamp":1760188599000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/11\/18\/2074"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,9,4]]},"references-count":37,"journal-issue":{"issue":"18","published-online":{"date-parts":[[2019,9]]}},"alternative-id":["rs11182074"],"URL":"https:\/\/doi.org\/10.3390\/rs11182074","relation":{"has-preprint":[{"id-type":"doi","id":"10.20944\/preprints201907.0058.v1","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,9,4]]}}}