{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,27]],"date-time":"2026-04-27T06:50:50Z","timestamp":1777272650254,"version":"3.51.4"},"reference-count":98,"publisher":"MDPI AG","issue":"21","license":[{"start":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T00:00:00Z","timestamp":1604275200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100002322","name":"Coordena\u00e7\u00e3o de Aperfei\u00e7oamento de Pessoal de N\u00edvel Superior","doi-asserted-by":"publisher","award":["88882.461705\/2019-01"],"award-info":[{"award-number":["88882.461705\/2019-01"]}],"id":[{"id":"10.13039\/501100002322","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Funda&amp;#x00E7;&amp;#x00E3;o de Amparo &amp;#x00E0; Pesquisa do Estado de S&amp;#x00E3;o Paulo","award":["#2018\/21338-3; #2019\/14697-0"],"award-info":[{"award-number":["#2018\/21338-3; #2019\/14697-0"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Fast-growing Eucalyptus spp. forest plantations and their resultant wood products are economically important and may provide a low-cost means to sequester carbon for greenhouse gas reduction. The development of advanced and optimized frameworks for estimating forest plantation attributes from lidar remote sensing data combined with statistical modeling approaches is a step towards forest inventory operationalization and might improve industry efficiency in monitoring and managing forest resources. In this study, we first developed and tested a framework for modeling individual tree attributes in fast-growing Eucalyptus forest plantation using airborne lidar data and linear mixed-effect models (LME) and assessed the gain in accuracy compared to a conventional linear fixed-effects model (LFE). Second, we evaluated the potential of using the tree-level estimates for determining tree attribute uniformity across different stand ages. In the field, tree measurements, such as tree geolocation, species, genotype, age, height (Ht), and diameter at breast height (dbh) were collected through conventional forest inventory practices, and tree-level aboveground carbon (AGC) was estimated using allometric equations. Individual trees were detected and delineated from lidar-derived canopy height models (CHM), and crown-level metrics (e.g., crown volume and crown projected area) were computed from the lidar 3-D point cloud. Field and lidar-derived crown metrics were combined for ht, dbh, and AGC modeling using an LME. We fitted a varying intercept and slope model, setting species, genotype, and stand (alone and nested) as random effects. For comparison, we also modeled the same attributes using a conventional LFE model. The tree attribute estimates derived from the best LME model were used for assessing forest uniformity at the tree level using the Lorenz curves and Gini coefficient (GC). We successfully detected 96.6% of the trees from the lidar-derived CHM. The best LME model for estimating the tree attributes was composed of the stand as a random effect variable, and canopy height, crown volume, and crown projected area as fixed effects. The %RMSE values for tree-level height, dbh, and AGC were 8.9%, 12.1%, and 23.7% for the LFE model and improved to 7.3%, 7.1%, and 13.6%, respectively, for the LME model. Tree attributes uniformity was assessed with the Lorenz curves and tree-level estimations, especially for the older stands. All stands showed a high level of tree uniformity with GC values approximately 0.2. This study demonstrates that accurate detection of individual trees and their associated crown metrics can be used to estimate Ht, dbh, and AGC stocks as well as forest uniformity in fast-growing Eucalyptus plantations forests using lidar data as inputs to LME models. This further underscores the high potential of our proposed approach to monitor standing stock and growth in Eucalyptus\u2014and similar forest plantations for carbon dynamics and forest product planning.<\/jats:p>","DOI":"10.3390\/rs12213599","type":"journal-article","created":{"date-parts":[[2020,11,2]],"date-time":"2020-11-02T19:51:31Z","timestamp":1604346691000},"page":"3599","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":38,"title":["Individual Tree Attribute Estimation and Uniformity Assessment in Fast-Growing Eucalyptus spp. Forest Plantations Using Lidar and Linear Mixed-Effects Models"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7840-3905","authenticated-orcid":false,"given":"Rodrigo","family":"Leite","sequence":"first","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa, MG 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7844-3560","authenticated-orcid":false,"given":"Carlos","family":"Silva","sequence":"additional","affiliation":[{"name":"Department of Geographical Sciences, University of Maryland, College Park, MD 20740, USA"},{"name":"School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"}]},{"given":"Midhun","family":"Mohan","sequence":"additional","affiliation":[{"name":"Department of Geography, University of California\u2014Berkeley, Berkeley, CA 94709, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0185-3959","authenticated-orcid":false,"given":"Adri\u00e1n","family":"Cardil","sequence":"additional","affiliation":[{"name":"Tecnosylva, Parque Tecnol\u00f3gico de Le\u00f3n, 24009 Le\u00f3n, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8747-0085","authenticated-orcid":false,"given":"Danilo","family":"Almeida","sequence":"additional","affiliation":[{"name":"Department of Forest Sciences, University of S\u00e3o Paulo, \u201cLuiz de Queiroz\u201d College of Agriculture (USP\/ESALQ), Av. P\u00e1dua Dias, 11, Piracicaba, SP 13418-900, Brazil"}]},{"given":"Samuel","family":"Carvalho","sequence":"additional","affiliation":[{"name":"College of Forestry, Federal University of Mato Grosso, Av. Fernando Correa da Costa, 2367, Boa Esperan\u00e7a, Cuiab\u00e1, MT 78060-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7813-088X","authenticated-orcid":false,"given":"Wan","family":"Jaafar","sequence":"additional","affiliation":[{"name":"Earth Observation Centre, Institute of Climate Change, National University of Malaysia (UKM), Bangi 43600, Malaysia"}]},{"given":"Juan","family":"Guerra-Hern\u00e1ndez","sequence":"additional","affiliation":[{"name":"Centro de iniciativas empresariais, Fundaci\u00f3n CEL. O Palomar s\/n, 27004 Lugo, Spain"},{"name":"Forest Research Centre, School of Agriculture, University of Lisbon, Instituto Superior de Agronomia, 1649-004 Lisboa, Portugal"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2534-4478","authenticated-orcid":false,"given":"Aaron","family":"Weiskittel","sequence":"additional","affiliation":[{"name":"Center for Research on Sustainable Forests, University of Maine, 5755 Nutting Hall, Orono, ME 04469, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7480-1458","authenticated-orcid":false,"given":"Andrew","family":"Hudak","sequence":"additional","affiliation":[{"name":"US Forest Service (USDA), Rocky Mountain Research Station, RMRS, 1221 South Main Street, Fort Collins, CO 80526, USA"}]},{"given":"Eben","family":"Broadbent","sequence":"additional","affiliation":[{"name":"Spatial Ecology and Conservation Lab, School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1689-4881","authenticated-orcid":false,"given":"Gabriel","family":"Prata","sequence":"additional","affiliation":[{"name":"Spatial Ecology and Conservation Lab, School of Forest Resources and Conservation, University of Florida, Gainesville, FL 32611, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0493-7581","authenticated-orcid":false,"given":"Ruben","family":"Valbuena","sequence":"additional","affiliation":[{"name":"School of Natural Sciences, Bangor University, Bangor LL57 2W, UK"}]},{"given":"H\u00e9lio","family":"Leite","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa, MG 36570-900, Brazil"}]},{"given":"Mariana","family":"Taquetti","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa, MG 36570-900, Brazil"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0003-8354","authenticated-orcid":false,"given":"Alvaro","family":"Soares","sequence":"additional","affiliation":[{"name":"Institute of Agricultural Sciences, Federal University of Uberl\u00e2ndia, Monte Carmelo, MG 38500-000, Brazil"}]},{"given":"Henrique","family":"Scolforo","sequence":"additional","affiliation":[{"name":"Department of Forestry and Environmental Resources, North Carolina State University, Raleigh, NC 27695, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7597-2427","authenticated-orcid":false,"given":"Cibele","family":"Amaral","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Vi\u00e7osa, Vi\u00e7osa, MG 36570-900, Brazil"}]},{"given":"Ana","family":"Dalla Corte","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of Paran\u00e1, Curitiba, PR 80210-170, Brazil"}]},{"given":"Carine","family":"Klauberg","sequence":"additional","affiliation":[{"name":"Department of Forest Engineering, Federal University of S\u00e3o Jo\u00e3o Del Rei, Sete Lagoas, MG 35701-970, Brazil"}]}],"member":"1968","published-online":{"date-parts":[[2020,11,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"57","DOI":"10.1016\/j.foreco.2015.06.021","article-title":"Changes in planted forests and future global implications","volume":"352","author":"Payn","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_2","unstructured":"Ib\u00e1, I.-I.B. (2019). De \u00c1rvores Report 2019, OSAC."},{"key":"ref_3","first-page":"65","article-title":"The future of planted forests","volume":"22","author":"Carle","year":"2020","journal-title":"Int. For. Rev."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Sedjo, R.A. (1999). The potential of high-yield plantation forestry for meeting timber needs. Planted Forests: Contributions to the Quest for Sustainable Societies. Forestry Sciences, Springer.","DOI":"10.1007\/978-94-017-2689-4_21"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1890\/080116","article-title":"The role of plantations in managing the world\u2019s forests in the Anthropocene","volume":"8","author":"Paquette","year":"2010","journal-title":"Front. Ecol. Environ."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"674","DOI":"10.1080\/02827581.2016.1220617","article-title":"Valuation and production possibilities on a working forest using multi-objective programming, Woodstock, timber NPV, and carbon storage and sequestration","volume":"31","author":"Roise","year":"2016","journal-title":"Scand. J. For. Res."},{"key":"ref_7","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."},{"key":"ref_8","first-page":"591","article-title":"Mapping aboveground carbon stocks using LiDAR data in Eucalyptus spp. plantations in the state of Sao Paulo, Brazil","volume":"42","author":"Silva","year":"2014","journal-title":"Sci. For."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"554","DOI":"10.1080\/07038992.2016.1196582","article-title":"Imputation of Individual Longleaf Pine (Pinus palustris Mill.) Tree Attributes from Field and LiDAR Data","volume":"42","author":"Silva","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/S0034-4257(01)00228-0","article-title":"Estimating tree heights and number of stems in young forest stands using airborne laser scanner data","volume":"78","author":"Bjerknes","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/S0034-4257(01)00243-7","article-title":"Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve","volume":"79","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_12","first-page":"465","article-title":"Modelling individual tree aboveground biomass using discrete return LiDAR in lowland dipterocarp forest of Malaysia","volume":"29","author":"Woodhouse","year":"2017","journal-title":"J. Trop. For. Sci."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1080\/02827580500373186","article-title":"Weibull and percentile models for lidar-based estimation of basal area distribution","volume":"20","author":"Gobakken","year":"2005","journal-title":"Scand. J. For. Res."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Dalla Corte, A.P., Rex, F.E., De Almeida, D.R.A., Sanquetta, C.R., Silva, C.A., Moura, M.M., Wilkinson, B., Zambrano, A.M.A., Da Cunha Neto, E.M., and Veras, H.F.P. (2020). Measuring Individual Tree Diameter and Height Using GatorEye High-Density UAV-Lidar in an Integrated Crop-Livestock-Forest System. Remote Sens., 12.","DOI":"10.3390\/rs12050863"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1093\/sjaf\/27.3.149","article-title":"A Simplified Method of Predicting Percent Volume in Log Portions","volume":"27","author":"Oderwald","year":"2003","journal-title":"South. J. Appl. For."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Silva, C., Klauberg, C., Hudak, A., Vierling, L., Jaafar, W., Mohan, M., Garcia, M., Ferraz, A., Cardil, A., and Saatchi, S. (2017). Predicting Stem Total and Assortment Volumes in an Industrial Pinus taeda L. Forest Plantation Using Airborne Laser Scanning Data and Random Forest. Forests, 8.","DOI":"10.3390\/f8070254"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0034-4257(88)90028-4","article-title":"Estimating forest biomass and volume using airborne laser data","volume":"24","author":"Nelson","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2012.02.023","article-title":"Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys","volume":"123","author":"Hudak","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","unstructured":"Wan Mohd Jaafar, W., Woodhouse, I., Silva, C., Omar, H., Abdul Maulud, K., Hudak, A., Klauberg, C., Cardil, A., and Mohan, M. (2018). Improving Individual Tree Crown Delineation and Attributes Estimation of Tropical Forests Using Airborne LiDAR Data. Forests, 9.","DOI":"10.3390\/f9120759"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1177\/0309133310365596","article-title":"Estimating plot-level tree height and volume of Eucalyptus grandis plantations using small-footprint, discrete return lidar data","volume":"34","author":"Tesfamichael","year":"2010","journal-title":"Progr. Phys. Geogr. Earth Environ."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"489","DOI":"10.1007\/s13595-015-0457-x","article-title":"Stand volume models based on stable metrics as from multiple ALS acquisitions in Eucalyptus plantations","volume":"72","author":"Packalen","year":"2015","journal-title":"Ann. For. Sci."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"422","DOI":"10.1093\/forestry\/cpw016","article-title":"A principal component approach for predicting the stem volume in Eucalyptus plantations in Brazil using airborne LiDAR data","volume":"89","author":"Silva","year":"2016","journal-title":"Forestry"},{"key":"ref_23","doi-asserted-by":"crossref","unstructured":"Silva, C.A., Hudak, A.T., Klauberg, C., Vierling, L.A., Gonzalez-Benecke, C., de Padua Chaves Carvalho, S., Rodriguez, L.C.E., and Cardil, A. (2017). Combined effect of pulse density and grid cell size on predicting and mapping aboveground carbon in fast-growing Eucalyptus forest plantation using airborne LiDAR data. Carbon Balance Manag., 12.","DOI":"10.1186\/s13021-017-0081-1"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/j.foreco.2006.04.005","article-title":"Optimal rotations on Eucalyptus plantations including carbon sequestration-A comparison of results in Brazil and Spain","volume":"229","author":"Rodriguez","year":"2006","journal-title":"Forest Ecol. Manag."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"920","DOI":"10.1016\/j.foreco.2007.09.085","article-title":"Production and carbon allocation in a clonal Eucalyptus plantation with water and nutrient manipulations","volume":"255","author":"Stape","year":"2008","journal-title":"For. Ecol. Manag."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1007\/s11056-017-9588-2","article-title":"Optimal rotation length for carbon sequestration in Eucalyptus plantations in subtropical China","volume":"48","author":"Zhou","year":"2017","journal-title":"New For."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1481","DOI":"10.3390\/rs2061481","article-title":"Comparison of area-based and individual tree-based methods for predicting plot-level forest attributes","volume":"2","author":"Yu","year":"2010","journal-title":"Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1339","DOI":"10.1080\/01431160701736489","article-title":"Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests","volume":"29","author":"Leckie","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"923","DOI":"10.14358\/PERS.72.8.923","article-title":"Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data","volume":"72","author":"Chen","year":"2006","journal-title":"Photogr. Eng. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10310-007-0041-9","article-title":"Detection of individual trees and estimation of tree height using LiDAR data","volume":"12","author":"Kwak","year":"2007","journal-title":"J. For. Res."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"590","DOI":"10.3832\/ifor1989-010","article-title":"Estimation of aboveground forest biomass in Galicia (NW Spain) by the combined use of LiDAR, LANDSAT ETM+ and National Forest Inventory data","volume":"10","author":"Vega","year":"2017","journal-title":"iForest Biogeosci. For."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Mohan, M., De Mendon\u00e7a, B.A.F., Silva, C.A., Klauberg, C., de Saboya Ribeiro, A.S., de Ara\u00fajo, E.J.G., Monte, M.A., and Cardil, A. (2019). Optimizing individual tree detection accuracy and measuring forest uniformity in coconut (Cocos nucifera L.) plantations using airborne laser scanning. Ecol. Model., 409.","DOI":"10.1016\/j.ecolmodel.2019.108736"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Packalen, P., Pukkala, T., and Pascual, A. (2020). Combining spatial and economic criteria in tree-level harvest planning. For. Ecosyst., 7.","DOI":"10.1186\/s40663-020-00234-3"},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1085","DOI":"10.1007\/s13595-011-0124-9","article-title":"ALS-based estimation of plot volume and site index in a eucalyptus plantation with a nonlinear mixed-effect model that accounts for the clone effect","volume":"68","author":"Maltamo","year":"2011","journal-title":"Ann. For. Sci."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1139\/cjfr-2014-0435","article-title":"Linear mixed-effects models and calibration applied to volume models in two rotations of Eucalyptus grandis plantations","volume":"46","author":"Batista","year":"2016","journal-title":"Can. J. For. Res."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"1","DOI":"10.7717\/peerj.9522","article-title":"Perils and pitfalls of mixed-effects regression models in biology","volume":"8","author":"Silk","year":"2020","journal-title":"PeerJ"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Pinheiro, J.C., and Bates, D.M. (2000). Linear Mixed-Effects Models: Basic Concepts and Examples. In: Mixed-effects models in S and S-Plus. Stat. Comput., 3\u201356.","DOI":"10.1007\/978-1-4419-0318-1_1"},{"key":"ref_38","doi-asserted-by":"crossref","unstructured":"Zuur, A., Ieno, E.N., Walker, N.J., Saveliev, A.A., and Smith, G.M. (2009). Mixed Effects Models and Extensions in Ecology with R., Springer Science & Business Media.","DOI":"10.1007\/978-0-387-87458-6"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"486","DOI":"10.1037\/1082-989X.3.4.486","article-title":"Fixed- and random-effects models in meta-analysis","volume":"3","author":"Hedges","year":"1998","journal-title":"Psychol. Methods"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"221","DOI":"10.1002\/sim.3478","article-title":"Fixed effects, random effects and GEE: What are the differences?","volume":"28","author":"Gardiner","year":"2009","journal-title":"Stat. Med."},{"key":"ref_41","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_42","doi-asserted-by":"crossref","first-page":"1649","DOI":"10.1139\/x11-083","article-title":"Combining tree height samples produced by airborne laser scanning and stand management records to estimate plot volume in Eucalyptus plantations","volume":"41","author":"Vauhkonen","year":"2011","journal-title":"Can. J. For. Res."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"290","DOI":"10.1109\/JSTARS.2013.2261978","article-title":"Testing Different Methods of Forest Height and Aboveground Biomass Estimations From ICESat\/GLAS Data in Eucalyptus Plantations in Brazil","volume":"7","author":"Baghdadi","year":"2014","journal-title":"IEEE J. Select. Topics Appl. Earth Observ. Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"145","DOI":"10.1016\/j.foreco.2017.02.025","article-title":"Incorporating rainfall data to better plan eucalyptus clones deployment in eastern Brazil","volume":"391","author":"Scolforo","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"9","DOI":"10.1590\/01047760201824012466","article-title":"Height-diameter models for Eucalyptus sp. plantations in Brazil","volume":"24","author":"Ribeiro","year":"2018","journal-title":"CERNE"},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Bourdier, T., Cordonnier, T., Kunstler, G., Piedallu, C., Lagarrigues, G., and Courbaud, B. (2016). Tree size inequality reduces forest productivity: An analysis combining inventory data for ten European species and a light competition model. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0151852"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.foreco.2016.04.035","article-title":"Increasing stand structural heterogeneity reduces productivity in Brazilian Eucalyptus monoclonal stands","volume":"373","author":"Soares","year":"2016","journal-title":"For. Ecol. Manag."},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Soares, A.A.V., Scolforo, H.F., Forrester, D.I., Carneiro, R.L., and Campoe, O.C. (2020). Exploring the relationship between stand growth, structure and growth dominance in Eucalyptus monoclonal plantations across a continent-wide environmental gradient in Brazil. For. Ecol. Manag., 474.","DOI":"10.1016\/j.foreco.2020.118340"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/j.foreco.2016.11.010","article-title":"Development of stand structural heterogeneity and growth dominance in thinned Eucalyptus stands in Brazil","volume":"384","author":"Soares","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1007\/BF00379630","article-title":"The meaning and measurement of size hierarchies in plant populations","volume":"61","author":"Weiner","year":"1984","journal-title":"Oecologia"},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1890\/0012-9658(2000)081[1139:DIIPSO]2.0.CO;2","article-title":"Describing Inequality in Plant Size or Fecundity","volume":"81","author":"Damgaard","year":"2000","journal-title":"Ecology"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1016\/j.foreco.2012.03.036","article-title":"Diversity and equitability ordering profiles applied to study forest structure","volume":"276","author":"Valbuena","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1063","DOI":"10.1139\/cjfr-2013-0147","article-title":"Characterizing forest structural types and shelterwood dynamics from Lorenz-based indicators predicted by airborne laser scanning","volume":"43","author":"Valbuena","year":"2013","journal-title":"Can. J. For. Res."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"723","DOI":"10.1080\/15481603.2016.1231605","article-title":"Fusion of airborne LiDAR and multispectral sensors reveals synergic capabilities in forest structure characterization","volume":"53","author":"Manzanera","year":"2016","journal-title":"GISci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Adhikari, H., Valbuena, R., Pellikka, P.K.E., and Heiskanen, J. (2020). Mapping forest structural heterogeneity of tropical montane forest remnants from airborne laser scanning and Landsat time series. Ecol. Indic., 108.","DOI":"10.1016\/j.ecolind.2019.105739"},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1127\/0941-2948\/2013\/0507","article-title":"K\u00f6ppen\u2019s climate classification map for Brazil","volume":"22","author":"Alvares","year":"2013","journal-title":"Meteorol. Zeitsch."},{"key":"ref_57","first-page":"365","article-title":"Height-Diameter and Height-Diameter-Age Equations For Second-Growth Douglas-Fir","volume":"13","author":"Curtis","year":"1967","journal-title":"For. Sci."},{"key":"ref_58","unstructured":"McGaughey, R.J. (2018). FUSION\/LDV: Software for LiDAR Data Analysis and Visualization, US Department of Agriculture, Forest Service, Pacific Northwest Research Station."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1016\/S0924-2716(98)00009-4","article-title":"Determination of terrain models in wooded areas with airborne laser scanner data","volume":"53","author":"Kraus","year":"1998","journal-title":"ISPRS J. Photogr. Remote Sens."},{"key":"ref_60","unstructured":"Silva, C.A., Crookston, N.L., Hudak, A.T., Vierling, L.A., and Klauberg, C. (2020, October 29). rLiDAR: LiDAR Data Processing and Visualization. Available online: https:\/\/cran.r-project.org\/web\/packages\/rLiDAR\/index.html."},{"key":"ref_61","unstructured":"R Core Team (2019). R: A Language and Environment for Statistical Computing, R Core Team."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1890\/13-0070.1","article-title":"The importance of crown dimensions to improve tropical tree biomass estimates","volume":"24","author":"Goodman","year":"2014","journal-title":"Ecol. Appl."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1016\/j.rse.2016.10.026","article-title":"LIDAR-based estimation of bole biomass for precision management of an Amazonian forest: Comparisons of ground-based and remotely sensed estimates","volume":"187","author":"Figueiredo","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v067.i01","article-title":"Fitting Linear Mixed-Effects Models Using lme4","volume":"67","author":"Bates","year":"2015","journal-title":"J. Stat. Softw."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Wilkinson, G.N., and Rogers, C.E. (1973). Symbolic Description of Factorial Models for Analysis of Variance. Appl. Stat., 22.","DOI":"10.2307\/2346786"},{"key":"ref_66","unstructured":"Chambers, J.M., and Hastie, T.J. (1992). Linear models. Statistical Models in S., Wadsworth & Brooks\/Cole."},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Shapiro, S.S., and Wilk, M.B. (1965). An Analysis of Variance Test for Normality (Complete Samples). Biometrika, 52.","DOI":"10.2307\/2333709"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Breusch, T.S., and Pagan, A.R. (1979). A Simple Test for Heteroscedasticity and Random Coefficient Variation. Econometrica, 47.","DOI":"10.2307\/1911963"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1093\/biomet\/76.2.297","article-title":"Regression and time series model selection in small samples","volume":"76","author":"Hurvich","year":"1989","journal-title":"Biometrika"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"18","DOI":"10.5589\/m13-012","article-title":"Patterns of covariance between airborne laser scanning metrics and Lorenz curve descriptors of tree size inequality","volume":"39","author":"Valbuena","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Adnan, S., Maltamo, M., Packalen, P., Meht\u00e4talo, L., Ammaturo, N., and Valbuena, R. (2020). Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification. Remote Sens. Environ., under review.","DOI":"10.1016\/j.rse.2021.112464"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1016\/j.isprsjprs.2014.06.002","article-title":"Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves","volume":"95","author":"Valbuena","year":"2014","journal-title":"ISPRS J. Photogr. Remote Sens."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1093\/forestry\/cpr051","article-title":"Comparative testing of single-tree detection algorithms under different types of forest","volume":"85","author":"Vauhkonen","year":"2012","journal-title":"Forestry"},{"key":"ref_75","first-page":"295","article-title":"Varredura a Laser aerotransportado para estimativa de vari\u00e1veis dendrom\u00e9tricas Airborne Laser Scanner technology for estimating dendrometric variables","volume":"36","author":"Lingnau","year":"2008","journal-title":"Sci. For. Piracicaba"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1016\/j.isprsjprs.2011.10.006","article-title":"Combination of individual tree detection and area-based approach in imputation of forest variables using airborne laser data","volume":"67","author":"Vastaranta","year":"2012","journal-title":"ISPRS J. Photogr. Remote Sens."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Mohan, M., Silva, C., Klauberg, C., Jat, P., Catts, G., Cardil, A., Hudak, A., and Dia, M. (2017). Individual Tree Detection from Unmanned Aerial Vehicle (UAV) Derived Canopy Height Model in an Open Canopy Mixed Conifer Forest. Forests, 8.","DOI":"10.3390\/f8090340"},{"key":"ref_78","doi-asserted-by":"crossref","unstructured":"Beland, M., Parker, G., Sparrow, B., Harding, D., Chasmer, L., Phinn, S., Antonarakis, A., and Strahler, A. (2019). On promoting the use of lidar systems in forest ecosystem research. For. Ecol. Manag., 450.","DOI":"10.1016\/j.foreco.2019.117484"},{"key":"ref_79","doi-asserted-by":"crossref","unstructured":"Leite, R.V., do Amaral, C.H., de Paula Pires, R., Silva, C.A., Soares, C.P.B., Macedo, R.P., da Silva, A.A.L., Broadbent, E.N., Mohan, M., and Leite, H.G. (2020). Estimating stem volume in eucalyptus plantations using airborne LiDAR: A comparison of area- and individual tree-based approaches. Remote Sens., 12.","DOI":"10.3390\/rs12091513"},{"key":"ref_80","unstructured":"Breidenbach, J., McGaughey, R.J., Andersen, H.-E., K\u00e4ndler, G., and Reutebuch, S.E. (2007). A mixed-effects model to estimate stand volume by means of small footprint airborne lidar data for an American and a German study site. Proceedings of ISPRS Workshop Laser Scanning, Silvilaser 2007. Available online: https:\/\/foto.aalto.fi\/ls2007\/final_papers\/Breidenbach_2007.pdf."},{"key":"ref_81","doi-asserted-by":"crossref","unstructured":"Fu, L., Zhang, H., Lu, J., Zang, H., Lou, M., and Wang, G. (2015). Multilevel nonlinear mixed-effect crown ratio models for individual trees of Mongolian oak (quercus mongolica) in northeast China. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0133294"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1080\/136588100240831","article-title":"Regression analysis with spatially autocorrelated error: Simulation studies and application to mapping of soil organic matter","volume":"14","author":"Lark","year":"2000","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"2181","DOI":"10.1007\/s10457-018-0334-3","article-title":"Comparison between spatial and non-spatial regression models for investigating tree\u2013soil relationships in a polycyclic tree plantation of Northern Italy and implications for management","volume":"93","author":"Comolli","year":"2019","journal-title":"Agrofor. Syst."},{"key":"ref_84","first-page":"57","article-title":"Par\u01cemetros da copa e a sua rela\u00e7\u00e3o com o di\u01cemetro e altura das \u00e1rvores de eucalipto em diferentes idades","volume":"40","author":"Wink","year":"2012","journal-title":"Sci. For. For. Sci."},{"key":"ref_85","doi-asserted-by":"crossref","unstructured":"Ferraz, A., Saatchi, S., Kellner, J., and Clark, D. (2018, January 22\u201327). Improving Carbon Estimation of Large Tropical Trees by Linking Airborne Lidar Crown Size to Field Inventory. Proceedings of the IGARSS 2018\u20142018 IEEE International Geoscience and Remote Sensing Symposium IEEE, Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518246"},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14214\/sf.10006","article-title":"Incorporating tree-and stand-level information on crown base height into multivariate forest management inventories based on airborne laser scanning","volume":"52","author":"Maltamo","year":"2018","journal-title":"Silva Fenn."},{"key":"ref_87","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.foreco.2019.05.053","article-title":"Linking forest growth with stand structure: Tree size inequality, tree growth or resource partitioning and the asymmetry of competition","volume":"447","author":"Forrester","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"e005","DOI":"10.5424\/fs\/2018272-11713","article-title":"Estimating forest uniformity in Eucalyptus spp. and Pinus taeda L. stands using field measurements and structure from motion point clouds generated from unmanned aerial vehicle (UAV) data collection","volume":"27","author":"Hentz","year":"2018","journal-title":"For. Syst."},{"key":"ref_89","doi-asserted-by":"crossref","first-page":"1614","DOI":"10.3390\/rs3081614","article-title":"Effects of individual tree detection error sources on forest management planning calculations","volume":"3","author":"Vastaranta","year":"2011","journal-title":"Remote Sens."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"1590","DOI":"10.1139\/cjfr-2017-0084","article-title":"Effects of plot size, stand density, and scan density on the relationship between airborne laser scanning metrics and the Gini coefficient of tree size inequality","volume":"47","author":"Adnan","year":"2017","journal-title":"Can. J. For. Res."},{"key":"ref_91","first-page":"781","article-title":"Calibration of Height and Volume Equations with Random Parameters","volume":"37","author":"Lappi","year":"1991","journal-title":"For. Sci."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1093\/sjaf\/29.1.22","article-title":"A Random-Parameter Height-Dbh Model for Cherrybark Oak","volume":"29","author":"Lynch","year":"2005","journal-title":"South. J. Appl. For."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"1","DOI":"10.14214\/sf.10179","article-title":"Transferability and calibration of airborne laser scanning based mixed-effects models to estimate the attributes of sawlog-sized scots pines","volume":"53","author":"Korhonen","year":"2019","journal-title":"Silva Fenn."},{"key":"ref_94","doi-asserted-by":"crossref","first-page":"1682","DOI":"10.3390\/f5071682","article-title":"Outlook for the Next Generation\u2019s Precision Forestry in Finland","volume":"5","author":"Holopainen","year":"2014","journal-title":"Forests"},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"845","DOI":"10.18671\/scifor.v43n108.9","article-title":"Redu\u00e7\u00e3o do erro amostral na estimativa do volume de povoamentos de Eucalyptus ssp. por meio de escaneamento laser aerotransportado","volume":"43","author":"Laranja","year":"2015","journal-title":"Sci. For."},{"key":"ref_96","doi-asserted-by":"crossref","unstructured":"Melville, G., Stone, C., and Turner, R. (2015). Application of LiDAR data to maximise the efficiency of inventory plots in softwood plantations. N. Z. J. For. Sci., 45.","DOI":"10.1186\/s40490-015-0038-7"},{"key":"ref_97","doi-asserted-by":"crossref","unstructured":"Da Silva, V.S., Silva, C.A., Mohan, M., Cardil, A., Rex, F.E., Loureiro, G.H., de Almeida, D.R.A., Broadbent, E.N., Gorgens, E.B., and Dalla Corte, A.P. (2020). Combined Impact of sample size and modeling approaches for predicting stem volume in Eucalyptus spp. forest plantations using field and LiDAR data. Remote Sens., 12.","DOI":"10.3390\/rs12091438"},{"key":"ref_98","doi-asserted-by":"crossref","first-page":"5211","DOI":"10.1080\/01431161.2018.1486519","article-title":"Comparison of ALS- and UAV(SfM)-derived high-density point clouds for individual tree detection in Eucalyptus plantations","volume":"39","author":"Cosenza","year":"2018","journal-title":"Int. J. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/21\/3599\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:28:21Z","timestamp":1760178501000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/21\/3599"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,11,2]]},"references-count":98,"journal-issue":{"issue":"21","published-online":{"date-parts":[[2020,11]]}},"alternative-id":["rs12213599"],"URL":"https:\/\/doi.org\/10.3390\/rs12213599","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,11,2]]}}}