{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,19]],"date-time":"2026-01-19T10:53:20Z","timestamp":1768820000439,"version":"3.49.0"},"reference-count":44,"publisher":"MDPI AG","issue":"6","license":[{"start":{"date-parts":[[2023,3,13]],"date-time":"2023-03-13T00:00:00Z","timestamp":1678665600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61871320"],"award-info":[{"award-number":["61871320"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["61872291"],"award-info":[{"award-number":["61872291"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["17JS099"],"award-info":[{"award-number":["17JS099"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Shaanxi key Laboratory project","award":["61871320"],"award-info":[{"award-number":["61871320"]}]},{"name":"Shaanxi key Laboratory project","award":["61872291"],"award-info":[{"award-number":["61872291"]}]},{"name":"Shaanxi key Laboratory project","award":["17JS099"],"award-info":[{"award-number":["17JS099"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The automatic extraction of individual tree from mobile laser scanning (MLS) scenes has important applications in tree growth monitoring, tree parameter calculation and tree modeling. However, trees often grow in rows and tree crowns overlap with varying shapes, and there is also incompleteness caused by occlusion, which makes individual tree extraction a challenging problem. In this paper, we propose a trunk-constrained and tree structure analysis method to extract trees from scanned urban scenes. Firstly, multi-feature enhancement is performed via PointNet to segment the tree points from raw urban scene point clouds. Next, the candidate local tree trunk clusters are obtained by clustering based on the intercepted local tree trunk layer, and the real local tree trunk is obtained by removing noise data. Then, the trunk is located and extracted by combining circle fitting and region growing, so as to obtain the center of the tree crown. Further, the points near the tree\u2019s crown (core points) are segmented through distance difference, and the tree crown boundary (boundary points) is distinguished by analyzing the density and centroid deflection angle. Therefore, the core and boundary points are deleted to obtain the remaining points (intermediate points). Finally, the core, intermediate and boundary points, as well as the tree trunks, are combined to extract individual tree. The performance of the proposed method was evaluated on the Pairs-Lille-3D dataset, which is a benchmark for point cloud classification, and data were produced using a mobile laser system (MLS) applied to two different cities in France (Paris and Lille). Overall, the precision, recall, and F1-score of instance segmentation were 90.00%, 98.22%, and 99.08%, respectively. The experimental results demonstrate that our method can effectively extract trees with multiple rows of occlusion and improve the accuracy of tree extraction.<\/jats:p>","DOI":"10.3390\/rs15061567","type":"journal-article","created":{"date-parts":[[2023,3,14]],"date-time":"2023-03-14T02:33:36Z","timestamp":1678761216000},"page":"1567","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["Trunk-Constrained and Tree Structure Analysis Method for Individual Tree Extraction from Scanned Outdoor Scenes"],"prefix":"10.3390","volume":"15","author":[{"given":"Xiaojuan","family":"Ning","sequence":"first","affiliation":[{"name":"Institute of Computer Science and Engineering, Xi\u2019an University of Technology, No. 5 South of Jinhua Road, Xi\u2019an 710048, China"},{"name":"Shaanxi Key Laboratory of Network Computing and Security Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yishu","family":"Ma","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Engineering, Xi\u2019an University of Technology, No. 5 South of Jinhua Road, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanyuan","family":"Hou","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Engineering, Xi\u2019an University of Technology, No. 5 South of Jinhua Road, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiyong","family":"Lv","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Engineering, Xi\u2019an University of Technology, No. 5 South of Jinhua Road, Xi\u2019an 710048, China"},{"name":"Shaanxi Key Laboratory of Network Computing and Security Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3742-4029","authenticated-orcid":false,"given":"Haiyan","family":"Jin","sequence":"additional","affiliation":[{"name":"Institute of Computer Science and Engineering, Xi\u2019an University of Technology, No. 5 South of Jinhua Road, Xi\u2019an 710048, China"},{"name":"Shaanxi Key Laboratory of Network Computing and Security Technology, Xi\u2019an 710048, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zengbo","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Mathematics and Statistics, Hengyang Normal University, Hengyang 421002, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yinghui","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Artificial Intelligence and Computer Science, Jiangnan University, 1800 of Lihu Road, Wuxi 214122, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2023,3,13]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"754","DOI":"10.1109\/TGRS.2019.2940146","article-title":"3D Segmentation of Trees through a Flexible Multiclass Graph Cut Algorithm","volume":"58","author":"Williams","year":"2020","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"116104","DOI":"10.1016\/j.envpol.2020.116104","article-title":"A systematic review of the leaf traits considered to contribute to removal of airborne particulate matter pollution in urban areas","volume":"269","author":"Corada","year":"2021","journal-title":"Environ. Pollut."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"208","DOI":"10.1016\/j.isprsjprs.2019.01.005","article-title":"Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest","volume":"148","author":"Liu","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Zhao, Y., Hu, Q., Li, H., Wang, S., and Ai, M. (2018). Evaluating carbon sequestration and PM2.5 removal of urban street trees using mobile laser scanning data. Remote Sens., 10.","DOI":"10.3390\/rs10111759"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1233","DOI":"10.1080\/01431161.2019.1662966","article-title":"Identification of trees and their trunks from mobile laser scanning data of roadway scenes","volume":"41","author":"Yadav","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Du, S., Lindenbergh, R., Ledoux, H., Stoter, J., and Nan, L. (2019). AdTree: Accurate, Detailed, and Automatic Modelling of Laser-Scanned Trees. Remote Sens., 11.","DOI":"10.20944\/preprints201907.0058.v2"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TGRS.2022.3230051","article-title":"Detection of individual trees in UAV LiDAR point clouds using a deep learning framework based on multichannel representation","volume":"60","author":"Luo","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"584","DOI":"10.3390\/rs5020584","article-title":"A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data","volume":"5","author":"Wu","year":"2013","journal-title":"Remote Sens."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"91","DOI":"10.5194\/isprsarchives-XXXVIII-5-W12-91-2011","article-title":"Biomass estimation of individual trees using stem and crown diameter tls measurements","volume":"XXXVIII-5","author":"Holopainen","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"112857","DOI":"10.1016\/j.rse.2021.112857","article-title":"Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD)","volume":"270","author":"Huo","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/j.isprsjprs.2022.01.002","article-title":"Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data","volume":"184","author":"Hu","year":"2022","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"33357","DOI":"10.1007\/s11042-021-11328-7","article-title":"Shape classification guided method for automated extraction of urban trees from terrestrial laser scanning point clouds","volume":"80","author":"Ning","year":"2021","journal-title":"Multimed. Tools Appl."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Ku\u017eelka, K., Slav\u00edk, M., and Surov\u00fd, P. (2020). Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement. Remote Sens., 12.","DOI":"10.3390\/rs12081236"},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Windrim, L., and Bryson, M. (2020). Detection, Segmentation, and Model Fitting of Individual Tree Stems from Airborne Laser Scanning of Forests Using Deep Learning. Remote Sens., 12.","DOI":"10.3390\/rs12091469"},{"key":"ref_15","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"},{"key":"ref_16","first-page":"102580","article-title":"Urban vegetation segmentation using terrestrial LiDAR point clouds based on point non-local means network","volume":"105","author":"Chen","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Brolly, G., Kir\u00e1ly, G., Lehtom\u00e4ki, M., and Liang, X. (2021). Voxel-Based Automatic Tree Detection and Parameter Retrieval from Terrestrial Laser Scans for Plot-Wise Forest Inventory. Remote Sens., 13.","DOI":"10.3390\/rs13040542"},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Kolendo, \u0141., Kozniewski, M., Ksepko, M., Chmur, S., and Neroj, B. (2021). Parameterization of the Individual Tree Detection Method Using Large Dataset from Ground Sample Plots and Airborne Laser Scanning for Stands Inventory in Coniferous Forest. Remote Sens., 13.","DOI":"10.3390\/rs13142753"},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Gollob, C., Ritter, T., Wassermann, C., and Nothdurft, A. (2019). Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots. Remote Sens., 11.","DOI":"10.3390\/rs11131602"},{"key":"ref_20","first-page":"164","article-title":"Automatic dendrometry: Tree detection, tree height and diameter estimation using terrestrial laser scanning","volume":"69","author":"Cabo","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Oveland, I., Hauglin, M., Giannetti, F., Kj\u00f8rsvik, N.S., and Gobakken, T. (2018). Comparing Three Different Ground Based Laser Scanning Methods for Tree Stem Detection. Remote Sens., 10.","DOI":"10.3390\/rs10040538"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1109\/TGRS.2020.2996064","article-title":"Iterative Training Sample Expansion to Increase and Balance the Accuracy of Land Classification from VHR Imagery","volume":"59","author":"Lv","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_23","first-page":"1","article-title":"Spatial\u2013Spectral Attention Network Guided with Change Magnitude Image for Land Cover Change Detection Using Remote Sensing Images","volume":"60","author":"Lv","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"105213","DOI":"10.1016\/j.compag.2020.105213","article-title":"Multilayered tree crown extraction from LiDAR data using graphbased segmentation","volume":"170","author":"Dong","year":"2020","journal-title":"Comput. Electron. Agric."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"211","DOI":"10.5194\/isprs-archives-XLIII-B2-2020-211-2020","article-title":"Using mobile laser scanning point clouds to extract urban roadside trees for ecological benefits estimation","volume":"43","author":"Fan","year":"2020","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_26","first-page":"102368","article-title":"Confidence-guided roadside individual tree extraction for ecological benefit estimation","volume":"102","author":"Fan","year":"2021","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_27","first-page":"100371","article-title":"An automated approach for street trees detection using mobile laser scanner data","volume":"20","author":"Husain","year":"2020","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/j.isprsjprs.2016.07.009","article-title":"A dual growing method for the automatic extraction of individual trees from mobile laser scanning data","volume":"120","author":"Li","year":"2016","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"326","DOI":"10.1016\/j.isprsjprs.2021.03.002","article-title":"Individual tree extraction from urban mobile laser scanning point clouds using deep pointwise direction embedding","volume":"175","author":"Luo","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Trochta, J., Kr\u016f\u010dek, M., Vr\u0161ka, T., and Kr\u00e1l, K. (2017). 3D Forest: An application for descriptions of three-dimensional forest structures using terrestrial LiDAR. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0176871"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"110440","DOI":"10.1016\/j.measurement.2021.110440","article-title":"A branch-trunk-constrained hierarchical clustering method for street trees individual extraction from mobile laser scanning point clouds","volume":"189","author":"Li","year":"2022","journal-title":"Measurement"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"11","DOI":"10.4316\/AECE.2019.03002","article-title":"Top-Down Approach to the Automatic Extraction of Individual Trees from Scanned Scene Point Cloud Data","volume":"19","author":"Ning","year":"2019","journal-title":"Adv. Electr. Comput. Eng."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1111","DOI":"10.1016\/j.ins.2022.06.032","article-title":"Extraction of indoor objects based on the exponential function density clustering model","volume":"607","author":"Chen","year":"2022","journal-title":"Inf. Sci."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1055","DOI":"10.1109\/JSTARS.2020.2979369","article-title":"An individual tree segmentation method based on watershed algorithm and three-dimensional spatial distribution analysis from airborne LiDAR point clouds","volume":"13","author":"Yang","year":"2020","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Yan, W., Guan, H., Cao, L., Yu, Y., Li, C., and Lu, J. (2020). A self-adaptive mean shift tree-segmentation method using UAV LiDAR data. Remote Sens., 12.","DOI":"10.3390\/rs12030515"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"400","DOI":"10.1016\/j.isprsjprs.2018.08.010","article-title":"A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds","volume":"144","author":"Dai","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"112307","DOI":"10.1016\/j.rse.2021.112307","article-title":"Individual tree crown segmentation from airborne LiDAR data using a novel Gaussian filter and energy function minimization-based approach","volume":"256","author":"Yun","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/j.isprsjprs.2020.11.016","article-title":"Combining graph-cut clustering with object-based stem detection for tree segmentation in highly dense airborne lidar point clouds","volume":"172","author":"Dersch","year":"2021","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","unstructured":"Wang, Y., Jiang, T., Liu, J., Li, X., and Liang, C. (2020). Hierarchical instance recognition of individual roadside trees in environmentally complex urban areas from UAV laser scanning point clouds. ISPRS Int. J. GeoInf., 9.","DOI":"10.3390\/ijgi9100595"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"97834","DOI":"10.1109\/ACCESS.2021.3094307","article-title":"Airborne LiDAR and photogrammetric point cloud fusion for extraction of urban tree metrics according to street network segmentation","volume":"9","author":"Yang","year":"2021","journal-title":"IEEE Access"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2052","DOI":"10.1109\/LGRS.2020.3012718","article-title":"Individual Tree Segmentation Based on Mean Shift and Crown Shape Model for Temperate Forest","volume":"18","author":"Tusa","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Ning, X., Ma, Y., Hou, Y., Lv, Z., Jin, H., and Wang, Y. (2022). Semantic Segmentation Guided Coarse-to-Fine Detection of Individual Trees from MLS Point Clouds Based on Treetop Points Extraction and Radius Expansion. Remote Sens., 14.","DOI":"10.3390\/rs14194926"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"545","DOI":"10.1177\/0278364918767506","article-title":"Paris-Lille-3D: A large and high-quality ground-truth urban point cloud dataset for automatic segmentation and classification","volume":"37","author":"Roynard","year":"2018","journal-title":"Int. J. Robot. Res."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1080\/2150704X.2018.1444286","article-title":"A supervoxel approach to the segmentation of individual trees from LiDAR point clouds","volume":"9","author":"Xu","year":"2018","journal-title":"Remote Sens. Lett."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/6\/1567\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T18:54:03Z","timestamp":1760122443000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/6\/1567"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,3,13]]},"references-count":44,"journal-issue":{"issue":"6","published-online":{"date-parts":[[2023,3]]}},"alternative-id":["rs15061567"],"URL":"https:\/\/doi.org\/10.3390\/rs15061567","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,3,13]]}}}