{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T08:47:37Z","timestamp":1775206057037,"version":"3.50.1"},"reference-count":107,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2023,6,25]],"date-time":"2023-06-25T00:00:00Z","timestamp":1687651200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Regional Innovation and Development of the National Natural Science Foundation of China","award":["U21A20244"],"award-info":[{"award-number":["U21A20244"]}]},{"name":"Regional Innovation and Development of the National Natural Science Foundation of China","award":["2572019CP08"],"award-info":[{"award-number":["2572019CP08"]}]},{"name":"Regional Innovation and Development of the National Natural Science Foundation of China","award":["31870622"],"award-info":[{"award-number":["31870622"]}]},{"name":"Special Fund Project for Basic Research in Central Universities","award":["U21A20244"],"award-info":[{"award-number":["U21A20244"]}]},{"name":"Special Fund Project for Basic Research in Central Universities","award":["2572019CP08"],"award-info":[{"award-number":["2572019CP08"]}]},{"name":"Special Fund Project for Basic Research in Central Universities","award":["31870622"],"award-info":[{"award-number":["31870622"]}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["U21A20244"],"award-info":[{"award-number":["U21A20244"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["2572019CP08"],"award-info":[{"award-number":["2572019CP08"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"Natural Science Foundation of China","doi-asserted-by":"publisher","award":["31870622"],"award-info":[{"award-number":["31870622"]}],"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>Crown vertical profiles (CVP) play an essential role in stand biomass and forest fire prediction. Traditionally, due to measurement difficulties, CVP models developed based on a small number of individual trees are not convincing. Terrestrial laser scanning (TLS) provides new insights for researching trees\u2019 CVPs. However, there is a limited understanding of the ability to accurately describe CVPs with TLS. In this study, we propose a new approach to automatically extract the crown radius (CR) at different heights and confirm the correctness and effectiveness of the proposed approach with field measurement data from 30 destructively harvested sample trees. We then applied the approach to extract the CR from 283 trees in 6 sample plots to develop a two-level nonlinear mixed-effects (NLME) model for the CVP. The results of the study showed that the average extraction accuracy of the CR when the proposed approach was applied was 90.12%, with differences in the extraction accuracies at different relative depths into the crown (RDINC) ranges. The TLS-based extracted CR strongly correlated with the field-measured CR, with an R2 of 0.93. Compared with the base model, the two-level NLME model has significantly improved the prediction accuracy, with Ra2 increasing by 13.8% and RMSE decreasing by 23.46%. All our research has demonstrated that TLS has great potential for accurately extracting CRs, which would provide a novel way to nondestructively measure the crown structure. Moreover, our research lays the foundation for the future development of CVP models using TLS at a regional scale.<\/jats:p>","DOI":"10.3390\/rs15133272","type":"journal-article","created":{"date-parts":[[2023,6,26]],"date-time":"2023-06-26T03:14:56Z","timestamp":1687749296000},"page":"3272","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["A Novel Approach to Characterizing Crown Vertical Profile Shapes Using Terrestrial Laser Scanning (TLS)"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-6639-1660","authenticated-orcid":false,"given":"Fan","family":"Wang","sequence":"first","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4381-4608","authenticated-orcid":false,"given":"Yuman","family":"Sun","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7318-8997","authenticated-orcid":false,"given":"Weiwei","family":"Jia","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1326-4924","authenticated-orcid":false,"given":"Dandan","family":"Li","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Xiaoyong","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"given":"Yiren","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3162-8621","authenticated-orcid":false,"given":"Haotian","family":"Guo","sequence":"additional","affiliation":[{"name":"Department of Forest Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"},{"name":"Key Laboratory of Sustainable Forest Ecosystem Management, School of Forestry, Northeast Forestry University, Harbin 150040, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,6,25]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Quan, Y., Li, M., Zhen, Z., Hao, Y., and Wang, B. (2020). The Feasibility of Modelling the Crown Profile of Larix Olgensis Using Unmanned Aerial Vehicle Laser Scanning Data. Sensors, 20.","DOI":"10.3390\/s20195555"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"7236","DOI":"10.1080\/01431161.2013.817715","article-title":"Estimation of Tree Crown Volume from Airborne Lidar Data Using Computational Geometry","volume":"34","author":"Korhonen","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1007\/s10310-003-0060-0","article-title":"Accuracy and Precision of Crown Profile, Volume, and Surface Area Measurements of 29-Year-Old Japanese Cypress Trees Using a Spiegel Relascope","volume":"9","author":"Waguchi","year":"2004","journal-title":"J. For. Res."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Lu, C., Xu, H., Zhang, J., Wang, A., Wu, H., Bao, R., and Ou, G. (2022). A Method for Estimating Forest Aboveground Biomass at the Plot Scale Combining the Horizontal Distribution Model of Biomass and Sampling Technique. Forests, 13.","DOI":"10.3390\/f13101612"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Alonso-Rego, C., Arellano-P\u00e9rez, S., Guerra-Hern\u00e1ndez, J., Molina-Valero, J.A., Mart\u00ednez-Calvo, A., P\u00e9rez-Cruzado, C., Castedo-Dorado, F., Gonz\u00e1lez-Ferreiro, E., \u00c1lvarez-Gonz\u00e1lez, J.G., and Ruiz-Gonz\u00e1lez, A.D. (2021). Estimating Stand and Fire-Related Surface and Canopy Fuel Variables in Pine Stands Using Low-Density Airborne and Single-Scan Terrestrial Laser Scanning Data. Remote Sens., 13.","DOI":"10.3390\/rs13245170"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1080\/07038992.2016.1220827","article-title":"Using Simulated 3D Surface Fuelbeds and Terrestrial Laser Scan Data to Develop Inputs to Fire Behavior Models","volume":"42","author":"Rowell","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Alonso-Rego, C., Arellano-P\u00e9rez, S., Cabo, C., Ordo\u00f1ez, C., \u00c1lvarez-Gonz\u00e1lez, J.G., D\u00edaz-Varela, R.A., and Ruiz-Gonz\u00e1lez, A.D. (2020). Estimating Fuel Loads and Structural Characteristics of Shrub Communities by Using Terrestrial Laser Scanning. Remote Sens., 12.","DOI":"10.3390\/rs12223704"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1106","DOI":"10.14214\/sf.1106","article-title":"Conifer Crown Profile Models from Terrestrial Laser Scanning","volume":"49","author":"Ferrarese","year":"2015","journal-title":"Silva Fennica"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"2059","DOI":"10.1139\/x03-126","article-title":"Crown Profile Equations for Stand-Grown Western Hemlock Trees in Northwestern Oregon","volume":"33","author":"Marshall","year":"2003","journal-title":"Can. J. For. Res."},{"key":"ref_10","first-page":"217","article-title":"An Adjustable Predictor of Crown Profile for Stand-Grown Douglas-Fir Trees","volume":"45","author":"Hann","year":"1999","journal-title":"For. Sci."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Stefanidou, A., Gitas, I.Z., Korhonen, L., Stavrakoudis, D., and Georgopoulos, N. (2020). LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest. Remote Sens., 12.","DOI":"10.3390\/rs12101565"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2135","DOI":"10.1126\/science.288.5474.2135","article-title":"China\u2019s Forest Policy for the 21st Century","volume":"288","author":"Zhang","year":"2000","journal-title":"Science"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"6776","DOI":"10.1109\/TGRS.2015.2448056","article-title":"Canopy Density Model: A New ALS-Derived Product to Generate Multilayer Crown Cover Maps","volume":"53","author":"Ferraz","year":"2015","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"113543","DOI":"10.1016\/j.rse.2023.113543","article-title":"A LiDAR Biomass Index-Based Approach for Tree- and Plot-Level Biomass Mapping over Forest Farms Using 3D Point Clouds","volume":"290","author":"Du","year":"2023","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1016\/j.rse.2018.05.016","article-title":"A New Approach with DTM\u2014Independent Metrics for Forest Growing Stock Prediction Using UAV Photogrammetric Data","volume":"213","author":"Giannetti","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"830","DOI":"10.3390\/rs4040830","article-title":"LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada","volume":"4","author":"Treitz","year":"2012","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2014.10.004","article-title":"Generalizing Predictive Models of Forest Inventory Attributes Using an Area-Based Approach with Airborne LiDAR Data","volume":"156","author":"Bouvier","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2653","DOI":"10.1080\/01431161.2016.1183833","article-title":"Analysis of a Lidar Voxel-Derived Vertical Profile at the Plot and Individual Tree Scales for the Estimation of Forest Canopy Layer Characteristics","volume":"37","author":"Sumnall","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/j.rse.2004.10.013","article-title":"Estimating Forest Canopy Fuel Parameters Using LIDAR Data","volume":"94","author":"Andersen","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"186","DOI":"10.1016\/j.isprsjprs.2017.10.002","article-title":"Mapping the Height and Spatial Cover of Features beneath the Forest Canopy at Small-Scales Using Airborne Scanning Discrete Return Lidar","volume":"133","author":"Sumnall","year":"2017","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1016\/j.isprsjprs.2015.07.008","article-title":"A Revised Terrain Correction Method for Forest Canopy Height Estimation Using ICESat\/GLAS Data","volume":"108","author":"Nie","year":"2015","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Pu, Y., Xu, D., Wang, H., Li, X., and Xu, X. (2023). A New Strategy for Individual Tree Detection and Segmentation from Leaf-on and Leaf-off UAV-LiDAR Point Clouds Based on Automatic Detection of Seed Points. Remote Sens., 15.","DOI":"10.3390\/rs15061619"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Lisiewicz, M., Kami\u0144ska, A., Kraszewski, B., and Stere\u0144czak, K. (2022). Correcting the Results of CHM-Based Individual Tree Detection Algorithms to Improve Their Accuracy and Reliability. Remote Sens., 14.","DOI":"10.3390\/rs14081822"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Hershey, J.L., McDill, M.E., Miller, D.A., Holderman, B., and Michael, J.H. (2022). A Voxel-Based Individual Tree Stem Detection Method Using Airborne LiDAR in Mature Northeastern U.S. Forests. Remote Sens., 14.","DOI":"10.3390\/rs14030806"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1016\/j.rse.2016.05.028","article-title":"Lidar Detection of Individual Tree Size in Tropical Forests","volume":"183","author":"Ferraz","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"67","DOI":"10.1186\/s40663-021-00340-w","article-title":"Individual Tree Extraction from Terrestrial Laser Scanning Data via Graph Pathing","volume":"8","author":"Wang","year":"2021","journal-title":"For. Ecosyst."},{"key":"ref_27","first-page":"102893","article-title":"A Novel Algorithm of Individual Tree Crowns Segmentation Considering Three-Dimensional Canopy Attributes Using UAV Oblique Photos","volume":"112","author":"Lei","year":"2022","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"378","DOI":"10.1016\/j.rse.2013.07.044","article-title":"An Efficient, Multi-Layered Crown Delineation Algorithm for Mapping Individual Tree Structure across Multiple Ecosystems","volume":"154","author":"Duncanson","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_29","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_30","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/j.isprsjprs.2020.10.016","article-title":"Individual Tree Detection and Crown Delineation from Unmanned Aircraft System (UAS) LiDAR in Structurally Complex Mixed Species Eucalypt Forests","volume":"171","author":"Jaskierniak","year":"2021","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Hastings, J.H., Ollinger, S.V., Ouimette, A.P., Sanders-DeMott, R., Palace, M.W., Ducey, M.J., Sullivan, F.B., Basler, D., and Orwig, D.A. (2020). Tree Species Traits Determine the Success of LiDAR-Based Crown Mapping in a Mixed Temperate Forest. Remote Sens., 12.","DOI":"10.3390\/rs12020309"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Wu, R., Chen, Y., Wen, C., Wang, C., and Li, J. (2016, January 2). Delineation of individual tree crowns for mobile laser scanning data. Proceedings of the 2nd ISPRS International Conference on Computer Vision in Remote Sensing (CVRS 2015), SPIE, Xiamen, China.","DOI":"10.1117\/12.2234909"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"112102","DOI":"10.1016\/j.rse.2020.112102","article-title":"Terrestrial Laser Scanning in Forest Ecology: Expanding the Horizon","volume":"251","author":"Calders","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Xia, S., Chen, D., Peethambaran, J., Wang, P., and Xu, S. (2021). Point Cloud Inversion: A Novel Approach for the Localization of Trees in Forests from TLS Data. Remote Sens., 13.","DOI":"10.3390\/rs13030338"},{"key":"ref_35","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_36","doi-asserted-by":"crossref","unstructured":"Heinzel, J., and Huber, M.O. (2017). Tree Stem Diameter Estimation from Volumetric TLS Image Data. Remote Sens., 9.","DOI":"10.3390\/rs9060614"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Wang, D., Hollaus, M., Puttonen, E., and Pfeifer, N. (2016, January 9). Fast and robust stem reconstruction in complex environments using terrestrial laser scanning. Proceedings of the The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, W\u00fcrzburg, Germany.","DOI":"10.5194\/isprs-archives-XLI-B3-411-2016"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"272","DOI":"10.1109\/LGRS.2016.2638738","article-title":"Reconstructing Stem Cross Section Shapes from Terrestrial Laser Scanning","volume":"14","author":"Wang","year":"2017","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_39","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."},{"key":"ref_40","first-page":"102941","article-title":"Quantifying the Effects of Competition on the Dimensions of Scots Pine and Norway Spruce Crowns","volume":"112","author":"Bianchi","year":"2022","journal-title":"Int. J. Appl. Earth Obs."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"1877","DOI":"10.3390\/rs70201877","article-title":"Terrestrial Laser Scanning as an Effective Tool to Retrieve Tree Level Height, Crown Width, and Stem Diameter","volume":"7","author":"Srinivasan","year":"2015","journal-title":"Remote Sens."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"67","DOI":"10.4995\/raet.2017.7429","article-title":"Estimaci\u00f3n de par\u00e1metros de estructura de nogales utilizando l\u00e1ser esc\u00e1ner terrestre","volume":"67","author":"Estornell","year":"2017","journal-title":"Revista Teledetecci\u00f3n"},{"key":"ref_43","doi-asserted-by":"crossref","unstructured":"Uzquiano, S., Barbeito, I., San Mart\u00edn, R., Ehbrecht, M., Seidel, D., and Bravo, F. (2021). Quantifying Crown Morphology of Mixed Pine-Oak Forests Using Terrestrial Laser Scanning. Remote Sens., 13.","DOI":"10.3390\/rs13234955"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Panagiotidis, D., and Abdollahnejad, A. (2021). Reliable Estimates of Merchantable Timber Volume from Terrestrial Laser Scanning. Remote Sens., 13.","DOI":"10.3390\/rs13183610"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.compag.2012.08.005","article-title":"Terrestrial Laser Scanning for Measuring the Solid Wood Volume, Including Branches, of Adult Standing Trees in the Forest Environment","volume":"89","author":"Dassot","year":"2012","journal-title":"Comput. Electron. Agric."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"905","DOI":"10.1111\/2041-210X.12933","article-title":"Using Terrestrial Laser Scanning Data to Estimate Large Tropical Trees Biomass and Calibrate Allometric Models: A Comparison with Traditional Destructive Approach","volume":"9","author":"Ploton","year":"2018","journal-title":"Methods Ecol. Evol."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1111\/2041-210X.12301","article-title":"Nondestructive Estimates of Above-Ground Biomass Using Terrestrial Laser Scanning","volume":"6","author":"Calders","year":"2015","journal-title":"Methods Ecol. Evol."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Fan, G., Nan, L., Chen, F., Dong, Y., Wang, Z., Li, H., and Chen, D. (2020). A New Quantitative Approach to Tree Attributes Estimation Based on LiDAR Point Clouds. Remote Sens., 12.","DOI":"10.3390\/rs12111779"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1219","DOI":"10.1007\/s00468-018-1704-1","article-title":"Quantifying Branch Architecture of Tropical Trees Using Terrestrial LiDAR and 3D Modelling","volume":"32","author":"Bentley","year":"2018","journal-title":"Trees"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"111355","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_51","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.isprsjprs.2022.07.021","article-title":"Comparing Tree Attributes Derived from Quantitative Structure Models Based on Drone and Mobile Laser Scanning Point Clouds across Varying Canopy Cover Conditions","volume":"192","author":"Qi","year":"2022","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Raumonen, P., Casella, E., Calders, K., Murphy, S., \u00c5kerblom, M., and Kaasalainen, M. (2015). Massive-scale tree modelling from tls data. Int. Soc. Photogramm. Remote Sens. Ann. Photogramm., 189\u2013196.","DOI":"10.5194\/isprsannals-II-3-W4-189-2015"},{"key":"ref_53","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_54","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1111\/2041-210X.12904","article-title":"Estimation of Above-Ground Biomass of Large Tropical Trees with Terrestrial LiDAR","volume":"9","author":"Lau","year":"2018","journal-title":"Methods Ecol. Evol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"102","DOI":"10.1139\/x96-100","article-title":"Predicting the Crown Shape of Loblolly Pine Trees","volume":"27","author":"Baldwin","year":"1997","journal-title":"Can. J. For. Res."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2370","DOI":"10.1016\/j.foreco.2009.03.038","article-title":"A Crown Profile Model for Pinus Radiata D. Don in Northwestern Spain","volume":"257","author":"Marshall","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1128","DOI":"10.1139\/cjfr-2021-0286","article-title":"Developing Crown Shape Model Considering a Novel Competition Index\u2014A Case for Korean Pine Plantation in Northeast China","volume":"52","author":"Sun","year":"2022","journal-title":"Can. J. For. Res."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/S0378-1127(97)00033-9","article-title":"Crown Profile Models Based on Branch Attributes in Coastal Douglas-Fir","volume":"96","author":"Roeh","year":"1997","journal-title":"For. Ecol. Manag."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.foreco.2004.07.051","article-title":"Modeling Dominant Height Growth Based on Nonlinear Mixed-Effects Model: A Clonal Eucalyptus Plantation Case Study","volume":"204","author":"Calegario","year":"2005","journal-title":"For. Ecol. Manag."},{"key":"ref_60","first-page":"311","article-title":"Modeling and Prediction of Forest Growth Variables Based on Multilevel Nonlinear Mixed Models","volume":"47","author":"Hall","year":"2001","journal-title":"For. Sci."},{"key":"ref_61","first-page":"84","article-title":"Crown Shape Model for Larix olgensis Plantation Based on Mixed Effect","volume":"53","author":"Gao","year":"2017","journal-title":"Sci. Silvae Sinicae"},{"key":"ref_62","first-page":"108","article-title":"Crown Prediction Model of Larix principis-rupprechtii Plantation in Saihanba of Hebei Province, Northern China","volume":"57","author":"Zhao","year":"2021","journal-title":"Sci. Silvae Sin."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2017.04.030","article-title":"Data Acquisition Considerations for Terrestrial Laser Scanning of Forest Plots","volume":"196","author":"Wilkes","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.isprsjprs.2016.01.001","article-title":"Octree-Based Segmentation for Terrestrial LiDAR Point Cloud Data in Industrial Applications","volume":"113","author":"Su","year":"2016","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_65","first-page":"1","article-title":"Structure-Aware Subsampling of Tree Point Clouds","volume":"19","author":"Wang","year":"2022","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.isprsjprs.2016.03.016","article-title":"Improved Progressive TIN Densification Filtering Algorithm for Airborne LiDAR Data in Forested Areas","volume":"117","author":"Zhao","year":"2016","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1016\/j.measurement.2017.03.007","article-title":"A Revised Progressive TIN Densification for Filtering Airborne LiDAR Data","volume":"104","author":"Nie","year":"2017","journal-title":"Measurement"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.isprsjprs.2015.10.007","article-title":"Segmenting Tree Crowns from Terrestrial and Mobile LiDAR Data by Exploring Ecological Theories","volume":"110","author":"Tao","year":"2015","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_69","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_70","doi-asserted-by":"crossref","first-page":"A562","DOI":"10.1364\/OE.26.00A562","article-title":"Simple Method for Direct Crown Base Height Estimation of Individual Conifer Trees Using Airborne LiDAR Data","volume":"26","author":"Luo","year":"2018","journal-title":"Opt. Express"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Vandendaele, B., Fournier, R.A., Vepakomma, U., Pelletier, G., Lejeune, P., and Martin-Ducup, O. (2021). Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level. Remote Sens., 13.","DOI":"10.3390\/rs13142796"},{"key":"ref_72","first-page":"100574","article-title":"Comparison of Spruce and Beech Tree Attributes from Field Data, Airborne and Terrestrial Laser Scanning Using Manual and Automatic Methods","volume":"23","author":"Novotny","year":"2021","journal-title":"Remote Sens. Appl. Soc. Environ."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"561","DOI":"10.1016\/j.isprsjprs.2009.04.002","article-title":"3D Segmentation of Single Trees Exploiting Full Waveform LIDAR Data","volume":"64","author":"Reitberger","year":"2009","journal-title":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Ye, W., Qian, C., Tang, J., Liu, H., Fan, X., Liang, X., and Zhang, H. (2020). Improved 3D Stem Mapping Method and Elliptic Hypothesis-Based DBH Estimation from Terrestrial Laser Scanning Data. Remote Sens., 12.","DOI":"10.3390\/rs12030352"},{"key":"ref_75","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":"Int. Soc. Photogramm. Remote Sens. J. Photogramm."},{"key":"ref_76","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_77","unstructured":"Fischler, M.A., and Firschein, O. (1987). Readings in Computer Vision, Elsevier."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1109\/TCSVT.2017.2780181","article-title":"Robust Plane Detection Using Depth Information from a Consumer Depth Camera","volume":"29","author":"Jin","year":"2019","journal-title":"IEEE Trans. Circuits Syst. Video Technol."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/0020-0190(72)90045-2","article-title":"An Efficient Algorith for Determining the Convex Hull of a Finite Planar Set","volume":"1","author":"Graham","year":"1972","journal-title":"Inf. Process. Lett."},{"key":"ref_80","doi-asserted-by":"crossref","unstructured":"Rocha, K.D., Silva, C.A., Cosenza, D.N., Mohan, M., Klauberg, C., Schlickmann, M.B., Xia, J., Leite, R.V., de Almeida, D.R.A., and Atkins, J.W. (2023). Crown-Level Structure and Fuel Load Characterization from Airborne and Terrestrial Laser Scanning in a Longleaf Pine (Pinus palustris Mill.) Forest Ecosystem. Remote Sens., 15.","DOI":"10.3390\/rs15041002"},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Poorazimy, M., Ronoud, G., Yu, X., Luoma, V., Hyypp\u00e4, J., Saarinen, N., Kankare, V., and Vastaranta, M. (2022). Feasibility of Bi-Temporal Airborne Laser Scanning Data in Detecting Species-Specific Individual Tree Crown Growth of Boreal Forests. Remote Sens., 14.","DOI":"10.3390\/rs14194845"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"176","DOI":"10.1016\/j.compag.2012.09.017","article-title":"Different Methodologies for Calculating Crown Volumes of Platanus Hispanica Trees Using Terrestrial Laser Scanner and a Comparison with Classical Dendrometric Measurements","volume":"90","author":"Sajdak","year":"2013","journal-title":"Comput. Electron. Agric."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"120303","DOI":"10.1016\/j.foreco.2022.120303","article-title":"Exploring Tree Growth Allometry Using Two-Date Terrestrial Laser Scanning","volume":"518","author":"Yrttimaa","year":"2022","journal-title":"For. Ecol. Manag."},{"key":"ref_84","doi-asserted-by":"crossref","unstructured":"Zhou, L., Li, X., Zhang, B., Xuan, J., Gong, Y., Tan, C., Huang, H., and Du, H. (2022). Estimating 3D Green Volume and Aboveground Biomass of Urban Forest Trees by UAV-Lidar. Remote Sens., 14.","DOI":"10.3390\/rs14205211"},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1016\/j.csda.2003.10.012","article-title":"A Simple More General Boxplot Method for Identifying Outliers","volume":"47","author":"Schwertman","year":"2004","journal-title":"Comput. Stat. Data Anal."},{"key":"ref_86","doi-asserted-by":"crossref","unstructured":"Li, D., Guo, H., Jia, W., and Wang, F. (2021). Analysis of Taper Functions for Larix Olgensis Using Mixed Models and TLS. Forests, 12.","DOI":"10.3390\/f12020196"},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"518","DOI":"10.1139\/x74-075","article-title":"Coniferous Stands Characterized with The Weibull Distribution","volume":"4","author":"Schreuder","year":"1974","journal-title":"Can. J. For. Res."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1007\/s00468-004-0338-7","article-title":"Modeling the Vertical Foliage Distribution of an Individual Castanopsis cuspidata (Thunb.) Schottky, a Dominant Broad-Leaved Tree in Japanese Warm-Temperate Forest","volume":"18","author":"Saito","year":"2004","journal-title":"Trees"},{"key":"ref_89","first-page":"10","article-title":"Modelling outer crown profile for planted Pinus koraiensis and Larix olgensis trees in Heilongjiang Province, China","volume":"42","author":"Gao","year":"2018","journal-title":"J. Nanjing For. Univ."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"109182","DOI":"10.1016\/j.agrformet.2022.109182","article-title":"Climate-Sensitive Tree Height-Diameter Models for Mixed Forests in Northeastern China","volume":"326","author":"Tian","year":"2022","journal-title":"Agric. For. Meteorol."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"117901","DOI":"10.1016\/j.foreco.2020.117901","article-title":"Mixed-Effects Generalized Height\u2013Diameter Model for Young Silver Birch Stands on Post-Agricultural Lands","volume":"460","author":"Bronisz","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_92","first-page":"25","article-title":"Based on Mixed-Effects Model and Empirical Best Linear Unbiased Predictor to Predict Growth Profile of Dominant Height","volume":"51","author":"Zu","year":"2015","journal-title":"Sci. Silvae Sin."},{"key":"ref_93","doi-asserted-by":"crossref","unstructured":"Yrttimaa, T., Luoma, V., Saarinen, N., Kankare, V., Junttila, S., Holopainen, M., Hyypp\u00e4, J., and Vastaranta, M. (2020). Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning. Remote Sens., 12.","DOI":"10.20944\/preprints202007.0154.v1"},{"key":"ref_94","doi-asserted-by":"crossref","unstructured":"Schneider, R., Calama, R., and Martin-Ducup, O. (2020). Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.) Cone Production Using Terrestrial Laser Scanner. Remote Sens., 12.","DOI":"10.3390\/rs12010173"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1007\/s00468-010-0452-7","article-title":"Comparing Canopy Metrics Derived from Terrestrial and Airborne Laser Scanning in a Douglas-Fir Dominated Forest Stand","volume":"24","author":"Hilker","year":"2010","journal-title":"Trees"},{"key":"ref_96","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1111\/2041-210X.13342","article-title":"LeWoS: A Universal Leaf-Wood Classification Method to Facilitate the 3D Modelling of Large Tropical Trees Using Terrestrial LiDAR","volume":"11","author":"Wang","year":"2020","journal-title":"Methods Ecol. Evol."},{"key":"ref_97","doi-asserted-by":"crossref","first-page":"1252","DOI":"10.1016\/j.agrformet.2011.05.004","article-title":"Estimating Leaf Area Distribution in Savanna Trees from Terrestrial LiDAR Measurements","volume":"151","author":"Widlowski","year":"2011","journal-title":"Agric. For. Meteorol."},{"key":"ref_98","doi-asserted-by":"crossref","unstructured":"Wang, D., Brunner, J., Ma, Z., Lu, H., Hollaus, M., Pang, Y., and Pfeifer, N. (2018). Separating Tree Photosynthetic and Non-Photosynthetic Components from Point Cloud Data Using Dynamic Segment Merging. Forests, 9.","DOI":"10.3390\/f9050252"},{"key":"ref_99","doi-asserted-by":"crossref","unstructured":"Sun, J., Wang, P., Gao, Z., Liu, Z., Li, Y., Gan, X., and Liu, Z. (2021). Wood\u2013Leaf Classification of Tree Point Cloud Based on Intensity and Geometric Information. Remote Sens., 13.","DOI":"10.3390\/rs13204050"},{"key":"ref_100","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_101","first-page":"52","article-title":"Modeling Crown Characteristic Attributes and Profile of Larix olgensis Using UAV-borne LiDAR","volume":"47","author":"Quan","year":"2019","journal-title":"J. Northeast For. Univ."},{"key":"ref_102","first-page":"40","article-title":"Outer Upper Crown Profile Simulation and Visualization for Cunninghamia lanceolata Based on UAV-borne LiDAR Data","volume":"34","author":"Xu","year":"2021","journal-title":"For. Res."},{"key":"ref_103","doi-asserted-by":"crossref","unstructured":"Wang, F., Sun, Y., Jia, W., Zhu, W., Li, D., Zhang, X., Tang, Y., and Guo, H. (2023). Development of Estimation Models for Individual Tree Aboveground Biomass Based on TLS-Derived Parameters. Forests, 14.","DOI":"10.3390\/f14020351"},{"key":"ref_104","doi-asserted-by":"crossref","unstructured":"Wang, M., Im, J., Zhao, Y., and Zhen, Z. (2022). Multi-Platform LiDAR for Non-Destructive Individual Aboveground Biomass Estimation for Changbai Larch (Larix olgensis Henry) Using a Hierarchical Bayesian Approach. Remote Sens., 14.","DOI":"10.3390\/rs14174361"},{"key":"ref_105","doi-asserted-by":"crossref","unstructured":"Liu, X., Hao, Y., Widagdo, F.R.A., Xie, L., Dong, L., and Li, F. (2021). Predicting Height to Crown Base of Larix Olgensis in Northeast China Using UAV-LiDAR Data and Nonlinear Mixed Effects Models. Remote Sens., 13.","DOI":"10.3390\/rs13091834"},{"key":"ref_106","doi-asserted-by":"crossref","first-page":"2315","DOI":"10.1139\/x94-299","article-title":"Development of Primary Branches and Crown Profile of Fraxinusexcelsior","volume":"24","author":"Cluzeau","year":"1994","journal-title":"Can. J. For. Res."},{"key":"ref_107","first-page":"445","article-title":"Crown Profile Modeling of Loblolly Pine by Nonparametric Regression Analysi","volume":"44","author":"Doruska","year":"1998","journal-title":"For. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3272\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:00:38Z","timestamp":1760126438000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/13\/3272"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,6,25]]},"references-count":107,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2023,7]]}},"alternative-id":["rs15133272"],"URL":"https:\/\/doi.org\/10.3390\/rs15133272","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,6,25]]}}}