{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,2]],"date-time":"2026-06-02T16:29:56Z","timestamp":1780417796559,"version":"3.54.1"},"reference-count":50,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T00:00:00Z","timestamp":1579564800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100012226","name":"Fundamental Research Funds for the Central Universities","doi-asserted-by":"publisher","award":["No. 2042019KF0034"],"award-info":[{"award-number":["No. 2042019KF0034"]}],"id":[{"id":"10.13039\/501100012226","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The detailed structure information under the forest canopy is important for forestry surveying. As a high-precision environmental sensing and measurement method, terrestrial laser scanning (TLS) is widely used in high-precision forestry surveying. In TLS-based forestry surveys, stem-mapping, which is focused on detecting and extracting trunks, is one of the core data processing tasks and the basis for the subsequent calculation of tree attributes; one of the most basic attributes is the diameter at breast height (DBH). This article explores and improves the methods for stem mapping and DBH estimation from TLS data. Firstly, an improved 3D stem mapping algorithm considering the growth direction in random sample consistency (RANSAC) cylinder fitting is proposed to extract and fit the individual tree point cloud section. It constructs the hierarchical optimum cylinder of the trunk and introduces the growth direction into the establishment of the backbone buffer in the next layer. Experimental results show that it can effectively remove most of the branches and reduce the interference of the branches to the discrimination of trunks and improve the integrity of stem extraction by about 36%. Secondly, a robust least squares ellipse fitting method based on the elliptic hypothesis is proposed for DBH estimation. Experimental results show that the DBH estimation accuracy of the proposed estimation method is improved compared with other methods. The mean root mean squared error (RMSE) of the proposed estimation method is 1.14 cm, compared with other methods with a mean RMSE of 1.70, 2.03, and 2.14 cm. The mean relative accuracy of the proposed estimation method is 95.2%, compared with other methods with a mean relative accuracy of 92.9%, 91.9%, and 90.9%.<\/jats:p>","DOI":"10.3390\/rs12030352","type":"journal-article","created":{"date-parts":[[2020,1,21]],"date-time":"2020-01-21T11:25:59Z","timestamp":1579605959000},"page":"352","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":35,"title":["Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data"],"prefix":"10.3390","volume":"12","author":[{"given":"WenFang","family":"Ye","sequence":"first","affiliation":[{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Chuang","family":"Qian","sequence":"additional","affiliation":[{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jian","family":"Tang","sequence":"additional","affiliation":[{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Liu","sequence":"additional","affiliation":[{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"XiaoYun","family":"Fan","sequence":"additional","affiliation":[{"name":"GNSS Research Center, Wuhan University, 129 Luoyu Road, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xinlian","family":"Liang","sequence":"additional","affiliation":[{"name":"Department of Remote Sensing and Photogrammetry, Finnish Geospatial Research Institute, 02431 Masala, Finland"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"HongJuan","family":"Zhang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2020,1,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"959","DOI":"10.1007\/s13595-011-0102-2","article-title":"The use of terrestrial LiDAR technology in forest science: Application fields, benefits and challenges","volume":"68","author":"Dassot","year":"2011","journal-title":"Ann. For. Sci."},{"key":"ref_2","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_3","doi-asserted-by":"crossref","unstructured":"Liu, C., Xing, Y., Duanmu, J., and Tian, X. (2018). Evaluating Different Methods for Estimating Diameter at Breast Height from Terrestrial Laser Scanning. Remote Sens., 10.","DOI":"10.3390\/rs10040513"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.compag.2017.10.019","article-title":"Performance of stem denoising and stem modelling algorithms on single tree point clouds from terrestrial laser scanning","volume":"143","author":"Olofsson","year":"2017","journal-title":"Comput. Electron. Agric."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.3390\/rs3112494","article-title":"Airborne Light Detection and Ranging (LiDAR) for Individual Tree Stem Location, Height, and Biomass Measurements","volume":"3","author":"Edson","year":"2011","journal-title":"Remote Sens."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"97","DOI":"10.1016\/j.isprsjprs.2018.04.019","article-title":"In-situ measurements from mobile platforms: An emerging approach to address the old challenges associated with forest inventories","volume":"143","author":"Liang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","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_8","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_9","doi-asserted-by":"crossref","first-page":"6040","DOI":"10.1117\/1.JRS.10.026040","article-title":"Adaptive circle-ellipse fitting method for estimating tree diameter based on single terrestrial laser scanning","volume":"10","author":"Bu","year":"2016","journal-title":"J. Appl. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"362","DOI":"10.1016\/0734-189X(89)90088-1","article-title":"A simple approach for the estimation of circular arc center and its radius","volume":"45","author":"Thomas","year":"1989","journal-title":"Comput. Vis. Graph. Image Process."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"\u010cer\u0148ava, J., Mokro\u0161, M., Tu\u010dek, J., Antal, M., and Slatkovsk\u00e1, Z. (2019). Processing Chain for Estimation of Tree Diameter from GNSS-IMU-Based Mobile Laser Scanning Data. Remote Sens., 11.","DOI":"10.3390\/rs11060615"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1739","DOI":"10.1109\/TGRS.2013.2253783","article-title":"Automated Stem Curve Measurement Using Terrestrial Laser Scanning","volume":"52","author":"Xinlian","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"109","DOI":"10.2480\/agrmet.D-18-00012","article-title":"Automatic individual tree detection and canopy segmentation from three-dimensional point cloud images obtained from ground-based lidar","volume":"74","author":"Itakura","year":"2018","journal-title":"J. Agric. Meteorol."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Brede, B., Lau, A., Bartholomeus, H.M., and Kooistra, L. (2017). Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR. Sensors, 17.","DOI":"10.3390\/s17102371"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.1016\/j.rse.2019.111355","article-title":"Non-destructive tree volume estimation through quantitative structure modelling: Comparing UAV laser scanning with terrestrial LIDAR","volume":"233","author":"Brede","year":"2019","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.agrformet.2014.07.008","article-title":"Airborne Lidar-derived volume metrics for aboveground biomass estimation: A comparative assessment for conifer stands","volume":"198\u2013199","author":"Tao","year":"2014","journal-title":"Agric. For. Meteorol."},{"key":"ref_17","first-page":"163","article-title":"Estimating residual biomass of olive tree crops using terrestrial laser scanning","volume":"75","author":"Estornell","year":"2019","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"984","DOI":"10.3390\/f4040984","article-title":"Above-Ground Biomass and Biomass Components Estimation Using LiDAR Data in a Coniferous Forest","volume":"4","author":"He","year":"2013","journal-title":"Forests"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1016\/j.ecolind.2017.02.045","article-title":"Above-ground biomass estimation using airborne discrete-return and full-waveform LiDAR data in a coniferous forest","volume":"78","author":"Nie","year":"2017","journal-title":"Ecol. Indic."},{"key":"ref_20","first-page":"122","article-title":"Accuracy of tree diameter estimation from terrestrial laser scanning by circle-fitting methods","volume":"63","author":"Bucha","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_21","first-page":"833","article-title":"New Development of Forest Canopy Height Remote Sensing","volume":"31","author":"Lixin","year":"2016","journal-title":"Remote Sens. Technol. Appl."},{"key":"ref_22","unstructured":"Haala, N., Reulke, R., Thies, M., and Aschoff, T. (2005, January 24\u201325). Combination of terrestrial Laser Scanning with high resolution panoramic Images for Investigations in Forest Applications and tree species recognition. Proceedings of the Panoramic Photogrammetry Workshop, Berlin, Germany."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1109\/TRO.2004.838003","article-title":"3-D mapping of natural environments with trees by means of mobile perception","volume":"21","author":"Forsman","year":"2005","journal-title":"IEEE Trans. Robot."},{"key":"ref_24","unstructured":"Forsman, M., B\u00f6rlin, N., and Holmgren, J. (September, January 25). Estimation of tree stem attributes using terrestrial photogrammetry. Proceedings of the ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Melbourne, Australia."},{"key":"ref_25","doi-asserted-by":"crossref","unstructured":"Yang, B., Dai, W., Dong, Z., and Liu, Y. (2016). Automatic Forest Mapping at Individual Tree Levels from Terrestrial Laser Scanning Point Clouds with a Hierarchical Minimum Cut Method. Remote Sens., 8.","DOI":"10.3390\/rs8050372"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"219","DOI":"10.14358\/PERS.77.3.219","article-title":"Automated Methods for Measuring DBH and Tree Heights with a Commercial Scanning Lidar","volume":"77","author":"Huang","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"S426","DOI":"10.5589\/m08-046","article-title":"Retrieval of forest structural parameters using a ground-based lidar instrument (Echidna\u00ae)","volume":"34","author":"Strahler","year":"2014","journal-title":"Can. J. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"839","DOI":"10.1002\/rob.20134","article-title":"Natural terrain classification using three-dimensional Ladar data for ground robot mobility","volume":"23","author":"Lalonde","year":"2010","journal-title":"J. Field Robot."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3923","DOI":"10.3390\/f6113923","article-title":"Detecting stems in dense and homogeneous forest using single-scan TLS","volume":"6","author":"Xia","year":"2015","journal-title":"Forests"},{"key":"ref_30","first-page":"43","article-title":"Foliar and woody materials discriminated using terrestrial LiDAR in a mixed natural forest","volume":"64","author":"Zhu","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_31","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_32","doi-asserted-by":"crossref","first-page":"3749","DOI":"10.3390\/rs5083749","article-title":"SVM-Based Classification of Segmented Airborne LiDAR Point Clouds in Urban Areas","volume":"5","author":"Zhang","year":"2013","journal-title":"Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"214","DOI":"10.1111\/j.1467-8659.2007.01016.x","article-title":"Efficient RANSAC for Point-Cloud Shape Detection","volume":"26","author":"Schnabel","year":"2007","journal-title":"Comput. Graph. Forum"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/j.isprsjprs.2015.01.011","article-title":"Octree-based region growing for point cloud segmentation","volume":"104","author":"Vo","year":"2015","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Burt, A., Disney, M., Calders, K., and Goslee, S. (2018). Extracting individual trees from lidar point clouds using treeseg. Methods Ecol. Evol.","DOI":"10.1111\/2041-210X.13121"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"661","DOI":"10.1109\/TGRS.2011.2161613","article-title":"Automatic stem mapping using single-scan terrestrial laser scanning","volume":"50","author":"Liang","year":"2011","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","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_38","doi-asserted-by":"crossref","unstructured":"Wieser, M., Mandlburger, G., Hollaus, M., Otepka, J., Glira, P., and Pfeifer, N. (2017). A Case Study of UAS Borne Laser Scanning for Measurement of Tree Stem Diameter. Remote Sens., 9.","DOI":"10.3390\/rs9111154"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"294","DOI":"10.1016\/j.isprsjprs.2018.11.027","article-title":"Measuring stem diameters with TLS in boreal forests by complementary fitting procedure","volume":"147","author":"Raumonen","year":"2019","journal-title":"Isprs J. Photogramm. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Liu, G., Wang, J., Dong, P., Chen, Y., and Liu, Z. (2018). Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level. Forests, 9.","DOI":"10.3390\/f9070398"},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. (2016). An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation. Remote Sens., 8.","DOI":"10.3390\/rs8060501"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"495","DOI":"10.1080\/2150704X.2016.1157639","article-title":"The effect of TLS point cloud sampling on tree detection and diameter measurement accuracy","volume":"7","author":"Kankare","year":"2016","journal-title":"Remote Sens. Lett."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.rse.2012.01.020","article-title":"3-D mapping of a multi-layered Mediterranean forest using ALS data","volume":"121","author":"Ferraz","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"75","DOI":"10.14358\/PERS.78.1.75","article-title":"A New Method for Segmenting Individual Trees from the Lidar Point Cloud","volume":"78","author":"Li","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Yu, Y., Li, J., Guan, H., Zai, D., and Wang, C. (2014, January 23\u201325). Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds. Proceedings of the ISPRS-International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Riva del Garda, Italy.","DOI":"10.5194\/isprsarchives-XL-5-629-2014"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Berveglieri, A., Tommaselli, A.M.G., Liang, X., and Honkavaara, E. (2017). Vertical Optical Scanning with Panoramic Vision for Tree Trunk Reconstruction. Sensors, 17.","DOI":"10.3390\/s17122791"},{"key":"ref_47","first-page":"211","article-title":"Tree height estimation methods for terrestrial laser scanning in a forest reserve","volume":"36","author":"Brolly","year":"2007","journal-title":"Geol. Comput. Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"2207","DOI":"10.1109\/TIP.2013.2246518","article-title":"Robust ellipse fitting based on sparse combination of data points","volume":"22","author":"Liang","year":"2013","journal-title":"IEEE Trans. Image Process."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"137","DOI":"10.1016\/j.isprsjprs.2018.06.021","article-title":"International benchmarking of terrestrial laser scanning approaches for forest inventories","volume":"144","author":"Liang","year":"2018","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Ravaglia, J., Fournier, R.A., Bac, A., V\u00e9ga, C., C\u00f4t\u00e9, J.-F., Piboule, A., and R\u00e9millard, U. (2019). Comparison of Three Algorithms to Estimate Tree Stem Diameter from Terrestrial Laser Scanner Data. Forests, 10.","DOI":"10.3390\/f10070599"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/352\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,13]],"date-time":"2025-10-13T13:20:28Z","timestamp":1760361628000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/3\/352"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,1,21]]},"references-count":50,"journal-issue":{"issue":"3","published-online":{"date-parts":[[2020,2]]}},"alternative-id":["rs12030352"],"URL":"https:\/\/doi.org\/10.3390\/rs12030352","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,1,21]]}}}