{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,10]],"date-time":"2026-03-10T19:06:19Z","timestamp":1773169579683,"version":"3.50.1"},"reference-count":63,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2023,8,20]],"date-time":"2023-08-20T00:00:00Z","timestamp":1692489600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["2022JBGS02"],"award-info":[{"award-number":["2022JBGS02"]}]},{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["2021LFR029"],"award-info":[{"award-number":["2021LFR029"]}]},{"name":"Leading Goose Project of the Science Technology Department of Zhejiang Province","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]},{"name":"National Natural Science Foundation of China","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"National Natural Science Foundation of China","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"National Natural Science Foundation of China","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"National Natural Science Foundation of China","award":["2022JBGS02"],"award-info":[{"award-number":["2022JBGS02"]}]},{"name":"National Natural Science Foundation of China","award":["2021LFR029"],"award-info":[{"award-number":["2021LFR029"]}]},{"name":"National Natural Science Foundation of China","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["2022JBGS02"],"award-info":[{"award-number":["2022JBGS02"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["2021LFR029"],"award-info":[{"award-number":["2021LFR029"]}]},{"name":"Scientific Research Project of Baishanzu National Park","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["2022JBGS02"],"award-info":[{"award-number":["2022JBGS02"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["2021LFR029"],"award-info":[{"award-number":["2021LFR029"]}]},{"name":"Talent launching project of scientific research and development fund of Zhejiang A and F University","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2023C02035"],"award-info":[{"award-number":["2023C02035"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["32201553"],"award-info":[{"award-number":["32201553"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["32171785"],"award-info":[{"award-number":["32171785"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2022JBGS02"],"award-info":[{"award-number":["2022JBGS02"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2021LFR029"],"award-info":[{"award-number":["2021LFR029"]}]},{"name":"Key Research and Development Program of Zhejiang Province","award":["2021C02005"],"award-info":[{"award-number":["2021C02005"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Optimizing the spatial structure of forests is important for improving the quality of forest ecosystems. Light detection and ranging (LiDAR) could accurately extract forest spatial structural parameters, which has significant advantages in spatial optimization and resource monitoring. In this study, we used unmanned aerial vehicle LiDAR (UAV-LiDAR) and backpack-LiDAR to acquire point cloud data of Metasequoia plantation forests from different perspectives. Then the parameters, such as diameter at breast height and tree height, were extracted based on the point cloud data, while the accuracy was verified using ground-truth data. Finally, a single-tree-level thinning tool was developed to optimize the spatial structure of the stand based on multi-objective planning and the Monte Carlo algorithm. The results of the study showed that the accuracy of LiDAR-based extraction was (R2 = 0.96, RMSE = 3.09 cm) for diameter at breast height, and the accuracy of R2 and RMSE for tree height extraction were 0.85 and 0.92 m, respectively. Thinning improved stand objective function value Q by 25.40%, with the most significant improvement in competition index CI and openness K of 17.65% and 22.22%, respectively, compared to the pre-optimization period. The direct effects of each spatial structure parameter on the objective function values were ranked as follows: openness K (1.18) &gt; aggregation index R (0.67) &gt; competition index CI (0.42) &gt; diameter at breast height size ratio U (0.06). Additionally, the indirect effects were ranked as follows: aggregation index R (0.86) &gt; diameter at breast height size ratio U (0.48) &gt; competition index CI (0.33). The study realized the optimization of stand spatial structure based on double LiDAR data, providing a new reference for forest management and structure optimization.<\/jats:p>","DOI":"10.3390\/rs15164090","type":"journal-article","created":{"date-parts":[[2023,8,21]],"date-time":"2023-08-21T01:46:56Z","timestamp":1692582416000},"page":"4090","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Optimizing the Spatial Structure of Metasequoia Plantation Forest Based on UAV-LiDAR and Backpack-LiDAR"],"prefix":"10.3390","volume":"15","author":[{"given":"Chao","family":"Chen","sequence":"first","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Lv","family":"Zhou","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Research Center of Forest Management Engineering of State Forestry and Grassland Administration, Beijing Forestry University, Beijing 100083, China"}]},{"given":"Xuejian","family":"Li","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Yinyin","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Jiacong","family":"Yu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"given":"Lujin","family":"Lv","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6765-2279","authenticated-orcid":false,"given":"Huaqiang","family":"Du","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Subtropical Silviculture, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"Key Laboratory of Carbon Cycling in Forest Ecosystems and Carbon Sequestration of Zhejiang Province, Zhejiang A & F University, Hangzhou 311300, China"},{"name":"School of Environmental and Resources Science, Zhejiang A & F University, Hangzhou 311300, China"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Dong, L., Wei, H., and Liu, Z. (2020). Optimizing Forest Spatial Structure with Neighborhood-Based Indices: Four Case Studies from Northeast China. Forests, 11.","DOI":"10.3390\/f11040413"},{"key":"ref_2","first-page":"117","article-title":"Advances in Study of Forest Spatial Structure","volume":"46","author":"Tang","year":"2010","journal-title":"Sci. Silvae Sin."},{"key":"ref_3","first-page":"48","article-title":"Spatial structure diversity of semi-natural and plantation stands of larix gmelini in Changbai Mountains","volume":"37","author":"Chen","year":"2015","journal-title":"J. Beijing For. Univ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"445","DOI":"10.2307\/1931034","article-title":"Distance to Nearest Neighbor as a Measure of Spatial Relationships in Populations","volume":"35","author":"Clark","year":"1954","journal-title":"Ecology"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"561","DOI":"10.3832\/ifor2115-010","article-title":"Selection priority for harvested trees according to stand structural indices","volume":"10","author":"Li","year":"2017","journal-title":"Iforest Biogeosciences For."},{"key":"ref_6","unstructured":"Fries, J. (1974). Growth Models for Tree and Stand Simulation, Royal College of Forestry."},{"key":"ref_7","first-page":"10","article-title":"Spatial Patterns of Shaded Coniferous Forests in the Xinglong Mountains and Their Responses to the Use of Light Energy","volume":"4","author":"Luo","year":"1984","journal-title":"Acta Ecol. Sin."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"146674","DOI":"10.1016\/j.scitotenv.2021.146674","article-title":"Biodiversity increased both productivity and its spatial stability in temperate forests in northeastern China","volume":"780","author":"Gao","year":"2021","journal-title":"Sci. Total Environ."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1180","DOI":"10.1111\/j.1654-1103.2012.01431.x","article-title":"The bivariate distribution characteristics of spatial structure in natural Korean pine broad-leaved forest","volume":"23","author":"Li","year":"2012","journal-title":"J. Veg. Sci."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"119399","DOI":"10.1016\/j.foreco.2021.119399","article-title":"Variation of carbon density components with overstory structure of larch plantations in northwest China and its implication for optimal forest management","volume":"496","author":"Ahmad","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.foreco.2017.11.030","article-title":"Thinning increases tree growth by delaying drought-induced growth cessation in a Mediterranean evergreen oak coppice","volume":"409","author":"Cabon","year":"2018","journal-title":"For. Ecol. Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"109089","DOI":"10.1016\/j.agrformet.2022.109089","article-title":"Response of soil respiration to thinning is altered by thinning residue treatment in Cunninghamia lanceolata plantations","volume":"324","author":"Zhang","year":"2022","journal-title":"Agric. For. Meteorol."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"109193","DOI":"10.1016\/j.ecolind.2022.109193","article-title":"Spatially explicit optimization of the forest management tradeoff between timber production and carbon sequestration","volume":"142","author":"Deng","year":"2022","journal-title":"Ecol. Indic."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"106","DOI":"10.1016\/j.foreco.2014.02.042","article-title":"Spatial structure of timber harvested according to structure-based forest management","volume":"322","author":"Li","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Ye, S., Zheng, Z., Diao, Z., Ding, G., Bao, Y., Liu, Y., and Gao, G. (2018). Effects of Thinning on the Spatial Structure of Larix principis-rupprechtii Plantation. Sustainability, 10.","DOI":"10.3390\/su10041250"},{"key":"ref_16","first-page":"76","article-title":"Evaluation of Stand Spatial Structure of Cunninghamia lanceolata Public Welfare Forest by Using Structural Equation Model","volume":"58","author":"Zhao","year":"2022","journal-title":"Sci. Silvae Sin."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"119965","DOI":"10.1016\/j.foreco.2021.119965","article-title":"Optimizing neighborhood-based stand spatial structure: Four cases of boreal forests","volume":"506","author":"Dong","year":"2022","journal-title":"For. Ecol. Manag."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Qiu, H., Zhang, H., Lei, K., Hu, X., Yang, T., and Jiang, X. (2023). A New Tree-Level Multi-Objective Forest Harvest Model (MO-PSO): Integrating Neighborhood Indices and PSO Algorithm to Improve the Optimization Effect of Spatial Structure. Forests, 14.","DOI":"10.3390\/f14030441"},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"100001","DOI":"10.1016\/j.fecs.2022.100001","article-title":"Two-level optimization approach to tree-level forest planning","volume":"9","author":"Sun","year":"2022","journal-title":"For. Ecosyst."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.3390\/f6041121","article-title":"Tree-Level Harvest Optimization for Structure-Based Forest Management Based on the Species Mingling Index","volume":"6","author":"Bettinger","year":"2015","journal-title":"Forests"},{"key":"ref_21","first-page":"23","article-title":"Generalizing Predictive Models of Sub-Tropical Forest Inventory Attributes Using anArea-Based Approach with Airborne LiDAR Data","volume":"57","author":"Li","year":"2021","journal-title":"Sci. Silvae Sin."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhang, B., Li, X., Du, H., Zhou, G., Mao, F., Huang, Z., Zhou, L., Xuan, J., Gong, Y., and Chen, C. (2022). Estimation of Urban Forest Characteristic Parameters Using UAV-Lidar Coupled with Canopy Volume. Remote Sens., 14.","DOI":"10.3390\/rs14246375"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/j.foreco.2017.10.041","article-title":"Tree spatial patterns and stand attributes in temperate forests: The importance of plot size, sampling design, and null model","volume":"407","author":"Carrer","year":"2018","journal-title":"For. Ecol. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Jiang, X., Li, G., Lu, D., Chen, E., and Wei, X. (2020). Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data. Remote Sens., 12.","DOI":"10.3390\/rs12071101"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"108781","DOI":"10.1016\/j.agrformet.2021.108781","article-title":"Three-dimensional estimation of deciduous forest canopy structure and leaf area using multi-directional, leaf-on and leaf-off airborne lidar data","volume":"314","author":"Yin","year":"2022","journal-title":"Agric. For. Meteorol."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.foreco.2019.02.002","article-title":"The effectiveness of lidar remote sensing for monitoring forest cover attributes and landscape restoration","volume":"438","author":"Almeida","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1016\/j.isprsjprs.2018.12.006","article-title":"Estimating canopy structure and biomass in bamboo forests using airborne LiDAR data","volume":"148","author":"Cao","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_28","first-page":"103067","article-title":"Efficient co-registration of UAV and ground LiDAR forest point clouds based on canopy shapes","volume":"114","author":"Shao","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1016\/j.fecs.2022.100065","article-title":"Ground-based\/UAV-LiDAR data fusion for quantitative structure modeling and tree parameter retrieval in subtropical planted forest","volume":"9","author":"Fekry","year":"2022","journal-title":"For. Ecosyst."},{"key":"ref_30","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_31","first-page":"102658","article-title":"Integrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan","volume":"106","author":"Shimizu","year":"2022","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_32","first-page":"102014","article-title":"Estimation of aboveground biomass of Robinia pseudoacacia forest in the Yellow River Delta based on UAV and Backpack LiDAR point clouds","volume":"86","author":"Lu","year":"2020","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_33","first-page":"638","article-title":"Integrating Airborne LiDAR and Terrestrial Laser Scanner forest parameters for accurate above-ground biomass\/carbon estimation in Ayer Hitam tropical forest, Malaysia","volume":"73","author":"Bazezew","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1080\/22797254.2018.1482733","article-title":"Integrating terrestrial and airborne laser scanning for the assessment of single-tree attributes in Mediterranean forest stands","volume":"51","author":"Giannetti","year":"2018","journal-title":"Eur. J. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Xuan, J., Li, X., Du, H., Zhou, G., Mao, F., Wang, J., Zhang, B., Gong, Y., Zhu, D.e., and Zhou, L. (2023). Intelligent Estimating the Tree Height in Urban Forests Based on Deep Learning Combined with a Smartphone and a Comparison with UAV-LiDAR. Remote Sens., 15.","DOI":"10.3390\/rs15010097"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"113143","DOI":"10.1016\/j.rse.2022.113143","article-title":"Individual tree segmentation and tree species classification in subtropical broadleaf forests using UAV-based LiDAR, hyperspectral, and ultrahigh-resolution RGB data","volume":"280","author":"Qin","year":"2022","journal-title":"Remote Sens. Environ."},{"key":"ref_37","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":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"117","DOI":"10.1080\/01431160902882561","article-title":"Adaptive clustering of airborne LiDAR data to segment individual tree crowns in managed pine forests","volume":"31","author":"Lee","year":"2010","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1660","DOI":"10.1109\/LGRS.2020.3005166","article-title":"The Development and Evaluation of a Backpack LiDAR System for Accurate and Efficient Forest Inventory","volume":"18","author":"Su","year":"2021","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/j.isprsjprs.2014.06.015","article-title":"Keypoint-based 4-Points Congruent Sets\u2014Automated marker-less registration of laser scans","volume":"96","author":"Theiler","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Weinmann, M., and Jutzi, B. (2015). Geometric point quality assessment for the automated, markerless and robust registration of unordered TLS point clouds. ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci., 89\u201396.","DOI":"10.5194\/isprsannals-II-3-W5-89-2015"},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Xu, Z., Shen, X., and Cao, L. (2023). Extraction of Forest Structural Parameters by the Comparison of Structure from Motion (SfM) and Backpack Laser Scanning (BLS) Point Clouds. Remote Sens., 15.","DOI":"10.3390\/rs15082144"},{"key":"ref_43","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":"ISPRS J. Photogramm. Remote Sens."},{"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","first-page":"51","article-title":"Extraction of individual tree parameters by combining terrestrial and UAV LiDAR","volume":"38","author":"Zhu","year":"2022","journal-title":"Trans. Chin. Soc. Agric. Eng."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"56","DOI":"10.5424\/fs\/2016251-07968","article-title":"The influence of sampling unit size and spatial arrangement patterns on neighborhood-based spatial structure analyses of forest stands","volume":"25","author":"Wang","year":"2016","journal-title":"For. Syst."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Cui, R., Qi, S., Wu, B., Zhang, D., Zhang, L., Zhou, P., Ma, N., and Huang, X. (2022). The Influence of Stand Structure on Understory Herbaceous Plants Species Diversity of Platycladus orientalis Plantations in Beijing, China. Forests, 13.","DOI":"10.3390\/f13111921"},{"key":"ref_48","first-page":"28","article-title":"Edge Correction of Voronoi Diagram in Forest Spatial Structure Analysis","volume":"53","author":"Liu","year":"2017","journal-title":"Sci. Silvae Sin."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Wang, Z., Li, Y., Meng, Y., Li, C., and Zhang, Z. (2022). Thinning Effects on Stand Structure and Carbon Content of Secondary Forests. Forests, 13.","DOI":"10.3390\/f13040512"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"105944","DOI":"10.1016\/j.ecolind.2019.105944","article-title":"Assessment of spatial stand structure of hemiboreal conifer dominated forests according to different levels of naturalness","volume":"110","author":"Korjus","year":"2020","journal-title":"Ecol. Indic."},{"key":"ref_51","first-page":"25","article-title":"Study on Spatial Structure Optimizing Model of Stand Selection Cutting","volume":"40","author":"Tang","year":"2004","journal-title":"Sci. Silvae Sin."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1186\/s13717-016-0063-3","article-title":"Applications of structural equation modeling (SEM) in ecological research: An updated review","volume":"5","author":"Fan","year":"2016","journal-title":"Ecol. Process."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"124","DOI":"10.1016\/j.foreco.2015.07.026","article-title":"A comparison of a neighborhood search technique for forest spatial harvest scheduling problems: A case study of the simulated annealing algorithm","volume":"356","author":"Dong","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"561","DOI":"10.14214\/sf.545","article-title":"Eight heuristic planning techniques applied to three increasingly difficult wildlife planning problems","volume":"36","author":"Bettinger","year":"2002","journal-title":"Silva Fenn."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/S0034-4257(97)00041-2","article-title":"Estimating timber volume of forest stands using airborne laser scanner data","volume":"61","year":"1997","journal-title":"Remote Sens. Environ. Interdiscip. J."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Chen, B., Li, Z., Pang, Y., Liu, Q., Gao, X., Gao, J., and Fu, A. (2017, January 23\u201328). Forest height estimation based on uav lidar simulated waveform. Proceedings of the 2017 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Fort Worth, TX, USA.","DOI":"10.1109\/IGARSS.2017.8127595"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Xie, Y., Yang, T., Wang, X., Chen, X., Pang, S., Hu, J., Wang, A., Chen, L., and Shen, Z. (2022). Applying a Portable Backpack Lidar to Measure and Locate Trees in a Nature Forest Plot: Accuracy and Error Analyses. Remote Sens., 14.","DOI":"10.3390\/rs14081806"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"421","DOI":"10.1186\/s40663-020-00237-0","article-title":"Accuracy assessment and error analysis for diameter at breast height measurement of trees obtained using a novel backpack LiDAR system","volume":"7","author":"Xie","year":"2020","journal-title":"For. Ecosyst."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Su, Y., Guan, H., Hu, T., and Guo, Q. (2018, January 22\u201327). The Integration of Uavand Backpack Lidar Systems for Forest Inventory. Proceedings of the IGARSS 2018\u20132018 IEEE International Geoscience and Remote Sensing Symposium, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8517639"},{"key":"ref_60","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_61","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1007\/s11355-019-00379-6","article-title":"Estimating the heights and diameters at breast height of trees in an urban park and along a street using mobile LiDAR","volume":"15","author":"Heo","year":"2019","journal-title":"Landsc. Ecol. Eng."},{"key":"ref_62","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_63","first-page":"77","article-title":"Visual Management Simulation for Pinus sylvestris var.mongolica Plantation Based on Optimized Spatial Structure","volume":"48","author":"Dong","year":"2012","journal-title":"Sci. Silvae Sin."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/16\/4090\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T20:37:53Z","timestamp":1760128673000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/15\/16\/4090"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,8,20]]},"references-count":63,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2023,8]]}},"alternative-id":["rs15164090"],"URL":"https:\/\/doi.org\/10.3390\/rs15164090","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,8,20]]}}}