{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:11:42Z","timestamp":1760145102642,"version":"build-2065373602"},"reference-count":96,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T00:00:00Z","timestamp":1718928000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Scion\u2019s Strategic Science Investment Fund and the Forest Growers Levy Trust"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Individual-tree-based models (IBMs) have emerged to provide finer-scale operational simulations of stand dynamics by accommodating and\/or representing tree-to-tree interactions and competition. Like stand-level growth model development, IBMs need an array of detailed data from individual trees in any stand through repeated measurement. Conventionally, these data have been collected through forest mensuration by establishing permanent sample plots or temporary measurement plots. With the evolution of remote sensing technology, it is now possible to efficiently collect more detailed information reflecting the heterogeneity of the whole forest stand than before. Among many techniques, airborne laser scanning (ALS) has proved to be reliable and has been reported to have potential to provide unparallel input data for growth models. This study utilized repeated ALS data to develop a model to project the annualized individual tree height increment (\u0394HT) in a conifer plantation by considering spatially explicit competition through a mixed-effects modelling approach. The ALS data acquisition showed statistical and biological consistency over time in terms of both response and important explanatory variables, with correlation coefficients ranging from 0.65 to 0.80. The height increment model had high precision (RMSE = 0.92) and minimal bias (0.03), respectively, for model fitting. Overall, the model showed high integrity with the current biological understanding of individual tree growth in a monospecific Pinus radiata plantation. The approach used in this study provided a robust model of annualized individual tree height growth, suggesting such an approach to modelling will be useful for future forest management.<\/jats:p>","DOI":"10.3390\/rs16132270","type":"journal-article","created":{"date-parts":[[2024,6,21]],"date-time":"2024-06-21T08:50:08Z","timestamp":1718959808000},"page":"2270","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Spatially Explicit Individual Tree Height Growth Models from Bi-Temporal Aerial Laser Scanning"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3037-1721","authenticated-orcid":false,"given":"Serajis","family":"Salekin","sequence":"first","affiliation":[{"name":"Scion (New Zealand Forest Research Institute Ltd.), Rotorua 3046, New Zealand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0625-6002","authenticated-orcid":false,"given":"David","family":"Pont","sequence":"additional","affiliation":[{"name":"Scion (New Zealand Forest Research Institute Ltd.), Rotorua 3046, New Zealand"}]},{"given":"Yvette","family":"Dickinson","sequence":"additional","affiliation":[{"name":"Scion (New Zealand Forest Research Institute Ltd.), Rotorua 3046, New Zealand"}]},{"given":"Sumedha","family":"Amarasena","sequence":"additional","affiliation":[{"name":"Scion (New Zealand Forest Research Institute Ltd.), Rotorua 3046, New Zealand"}]}],"member":"1968","published-online":{"date-parts":[[2024,6,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Burkhart, H.E., and Tom\u00e9, M. (2012). Modeling Forest Trees and Stands, Springer.","DOI":"10.1007\/978-90-481-3170-9"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Weiskittel, A.R., Hann, D.W., Kershaw, J.A., and Vanclay, J.K. (2011). Forest Growth and Yield Modeling, John Wiley & Sons.","DOI":"10.1002\/9781119998518"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Pretzsch, H. (2009). Forest dynamics, growth, and yield. Forest Dynamics, Growth and Yield: From Measurement to Model, Springer.","DOI":"10.1007\/978-3-540-88307-4"},{"key":"ref_4","unstructured":"Munro, D.D. (1974). Forest Growth Models\u2014A Prognosis, Royal College of Forestry."},{"key":"ref_5","unstructured":"Jorgensen, S.E., and Fath, B.D. (2008). Plant competition. Encyclopedia of Ecology, Elsevier."},{"key":"ref_6","first-page":"816","article-title":"Distance-dependent competition measures for predicting growth of individual trees","volume":"35","author":"Burkhart","year":"1989","journal-title":"For. Sci."},{"key":"ref_7","first-page":"403","article-title":"Stand density measures: An interpretation","volume":"16","author":"Curtis","year":"1970","journal-title":"For. Sci."},{"key":"ref_8","unstructured":"Oliver, C.D., and Larson, B.C. (1996). Forest Stand Dynamics, John Wiley and Sons. Updated ed.; Yale School of the Environment."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1586","DOI":"10.1016\/j.foreco.2010.01.035","article-title":"Competition and tree crowns: A neighborhood analysis of three boreal tree species","volume":"259","author":"Thorpe","year":"2010","journal-title":"For. Ecol. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Twery, M.J., and Weiskittel, A.R. (2013). Forest-management modelling. Environmental Modelling, John Wiley and Sons.","DOI":"10.1002\/9781118351475.ch23"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"1065","DOI":"10.1093\/aob\/mcm246","article-title":"Models for forest ecosystem management: A European perspective","volume":"101","author":"Pretzsch","year":"2007","journal-title":"Ann. Bot."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"103","DOI":"10.1515\/boku-2017-0010","article-title":"Possibilities and limitations of individual-tree growth models\u2014A review on model evaluations","volume":"68","author":"Vospernik","year":"2017","journal-title":"Die Bodenkult. J. Land Manag. Food Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"360","DOI":"10.1016\/0169-5347(90)90095-U","article-title":"Asymmetric competition in plant populations","volume":"5","author":"Weiner","year":"1990","journal-title":"Trends Ecol. Evol."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1051\/forest:19990405","article-title":"Distance-dependent competition measures for Eucalyptus plantations in Portugal","volume":"56","author":"Soares","year":"1999","journal-title":"Ann. For. Sci."},{"key":"ref_15","first-page":"360","article-title":"Evaluation of competition indices in individual tree growth models","volume":"41","author":"Biging","year":"1995","journal-title":"For. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.ppees.2007.11.002","article-title":"Competition among plants: Concepts, individual-based modelling approaches, and a proposal for a future research strategy","volume":"9","author":"Berger","year":"2008","journal-title":"Perspect. Plant Ecol. Evol. Syst."},{"key":"ref_17","first-page":"74","article-title":"A simulation model for managing jack-pine stands simulation","volume":"30","author":"Hegyi","year":"1974","journal-title":"R. Coll. For. Res. Notes"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1016\/j.foreco.2018.11.002","article-title":"Comparing performance of contrasting distance-independent and distance-dependent competition metrics in predicting individual tree diameter increment and survival within structurally-heterogeneous, mixed-species forests of Northeastern United States","volume":"433","author":"Kuehne","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"596315","DOI":"10.3389\/fpls.2020.596315","article-title":"Spatial models with inter-tree competition from airborne laser scanning improve estimates of genetic variance","volume":"11","author":"Pont","year":"2021","journal-title":"Front. Plant Sci."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"195","DOI":"10.1007\/s40725-015-0020-x","article-title":"Characterizing forest growth and productivity using remotely sensed data","volume":"1","author":"Coops","year":"2015","journal-title":"Curr. For. Rep."},{"key":"ref_21","first-page":"11","article-title":"Remote sensing in forestry: Current challenges, considerations and directions","volume":"97","author":"Fassnacht","year":"2023","journal-title":"For. Int. J. For. Res."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"111","DOI":"10.1016\/j.foreco.2013.02.031","article-title":"Maintaining high rates of carbon storage in old forests: A mechanism linking canopy structure to forest function","volume":"298","author":"Hardiman","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"405","DOI":"10.1016\/j.oneear.2020.05.001","article-title":"Applications in remote sensing to forest ecology and management","volume":"2","author":"Lechner","year":"2020","journal-title":"One Earth"},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Maltamo, M., N\u00e6sset, E., and Vauhkonen, J. (2014). Forestry Applications of Airborne Laser Scanning, Springer. [1st ed.].","DOI":"10.1007\/978-94-017-8663-8"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1080\/07038992.2016.1207484","article-title":"Remote sensing technologies for enhancing forest inventories: A review","volume":"42","author":"White","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"112477","DOI":"10.1016\/j.rse.2021.112477","article-title":"Modelling lidar-derived estimates of forest attributes over space and time: A review of approaches and future trends","volume":"260","author":"Coops","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s40725-021-00135-w","article-title":"Estimating changes in forest attributes and enhancing growth projections: A review of existing approaches and future directions using airborne 3D point cloud data","volume":"7","author":"Tompalski","year":"2021","journal-title":"Curr. For. Rep."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/S0034-4257(01)00290-5","article-title":"Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data","volume":"80","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"520","DOI":"10.1111\/btp.12538","article-title":"Landscape-scale lidar analysis of aboveground biomass distribution in secondary Brazilian Atlantic Forest","volume":"50","author":"Becknell","year":"2018","journal-title":"Biotropica"},{"key":"ref_30","first-page":"113","article-title":"Detection of biomass change in a Norwegian mountain forest area using small footprint airborne laser scanner data","volume":"22","author":"Gregoire","year":"2012","journal-title":"Stat. Methods Appl."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Dalponte, M., Liu, S., and Gianelle, D. (2018, January 22\u201327). Detection of forest changes with multi-temporal Lidar data. Proceedings of the IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Valencia, Spain.","DOI":"10.1109\/IGARSS.2018.8518153"},{"key":"ref_32","first-page":"458","article-title":"Modeling and predicting aboveground biomass change in young forest using multi-temporal airborne laser scanner data","volume":"30","author":"Gobakken","year":"2015","journal-title":"Scand. J. For. Res."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"485","DOI":"10.1080\/17538947.2017.1336578","article-title":"Quantifying individual tree growth and tree competition using bi-temporal airborne laser scanning data: A case study in the Sierra Nevada Mountains, California","volume":"11","author":"Ma","year":"2018","journal-title":"Int. J. Digit. Earth"},{"key":"ref_34","doi-asserted-by":"crossref","unstructured":"Hao, Y., Widagdo, F.R.A., Liu, X., Quan, Y., Dong, L., and Li, F. (2021). Individual tree diameter estimation in small-scale forest inventory using UAV laser scanning. Remote Sens., 13.","DOI":"10.3390\/rs13010024"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.ecoinf.2016.12.004","article-title":"Individual tree- and stand-based development following natural disturbance in a heterogeneously structured forest: A LiDAR-based approach","volume":"38","author":"Hill","year":"2017","journal-title":"Ecol. Inform."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"2216","DOI":"10.1109\/TGRS.2012.2211023","article-title":"Growth-competition-based stem diameter and volume modeling for tree-level forest inventory using airborne LiDAR data","volume":"51","author":"Lo","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1029\/2009JG000933","article-title":"Estimation of tropical forest height and biomass dynamics using lidar remote sensing at La Selva, Costa Rica","volume":"115","author":"Dubayah","year":"2010","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"5079","DOI":"10.1002\/ece3.4075","article-title":"Monitoring individual tree-based change with airborne lidar","volume":"8","author":"Duncanson","year":"2018","journal-title":"Ecol. Evol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"1784","DOI":"10.1016\/j.rse.2007.09.002","article-title":"Height growth reconstruction of a boreal forest canopy over a period of 58 years using a combination of photogrammetric and lidar models","volume":"112","author":"Vega","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_40","unstructured":"Holmgren, J. (2003). Estimation of Forest Variables Using Airborne Laser Scanning, Swedish University of Agricultural Sciences."},{"key":"ref_41","first-page":"551","article-title":"Fusion of small-footprint Lidar and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA","volume":"50","author":"Popescu","year":"2004","journal-title":"For. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","unstructured":"Yang, Z., Liu, Q., Luo, P., Ye, Q., Duan, G., Sharma, R.P., Zhang, H., Wang, G., and Fu, L. (2020). Prediction of individual tree diameter and height to crown base using nonlinear simultaneous regression and airborne LiDAR data. Remote Sens., 12.","DOI":"10.3390\/rs12142238"},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"217","DOI":"10.1007\/s12524-015-0494-9","article-title":"Estimating tree growth using crown metrics derived from LiDAR data","volume":"44","author":"Nakajima","year":"2015","journal-title":"J. Indian Soc. Remote Sens."},{"key":"ref_44","unstructured":"Pont, D. (2016). Assessment of Individual Trees Using Aerial Laser Scanning in New Zealand Radiata Pine Forests, University of Canterbury."},{"key":"ref_45","unstructured":"Pont, D. (2004, January 7\u201311). Analyses of basic crown-stem growth relationship in Radiata pine. Proceedings of the 4th International Workshop on Functional-Structural Plant Models (FSPM), Montpellier, France."},{"key":"ref_46","first-page":"611","article-title":"Quantifying the precision of forest stand height and canopy cover estimates derived from air photo interpretation","volume":"94","author":"Tompalski","year":"2021","journal-title":"For. Int. J. For. Res."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Nguyen, T.H., Jones, S., Soto-Berelov, M., Haywood, A., and Hislop, S. (August, January 28). Estimate forest biomass dynamics using multi-temporal lidar and single date inventory data. Proceedings of the GARSS 2019\u20142019 IEEE International Geoscience and Remote Sensing Symposium 2019, Yokohama, Japan.","DOI":"10.1109\/IGARSS.2019.8897905"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Poudel, K., Flewelling, J., and Temesgen, H. (2018). Predicting volume and biomass change from multi-temporal lidar sampling and remeasured field inventory data in Panther creek watershed, Oregon, USA. Forests, 9.","DOI":"10.3390\/f9010028"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1895","DOI":"10.1590\/0001-3765201720160324","article-title":"Modeling and mapping basal area of Pinus taeda L. plantation using airborne LiDAR data","volume":"89","author":"Silva","year":"2017","journal-title":"An. Acad. Bras. Ci\u00eancias"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"150","DOI":"10.1016\/j.foreco.2012.05.043","article-title":"Deriving individual tree competition indices from airborne laser scanning","volume":"280","author":"Pedersen","year":"2012","journal-title":"For. Ecol. Manag."},{"key":"ref_51","first-page":"137","article-title":"Puruki experimental catchment: Site, climate, forest management and research","volume":"17","author":"Beets","year":"1987","journal-title":"N. Z. J. For. Sci."},{"key":"ref_52","first-page":"3","article-title":"Puruki experimental forest\u2014Half a century of forestry research","volume":"66","author":"Garrett","year":"2021","journal-title":"N. Z. J. For."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"637","DOI":"10.3390\/f2030637","article-title":"Leaf area index, biomass carbon and growth rate of radiata pine genetic types and relationships with LiDAR","volume":"2","author":"Beets","year":"2011","journal-title":"Forests"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"3819","DOI":"10.1080\/01431161.2015.1054048","article-title":"Calibrated tree counting on remotely sensed images of planted forests","volume":"36","author":"Pont","year":"2015","journal-title":"Int. J. Remote Sens."},{"key":"ref_55","unstructured":"ESRI (2021). ArcGIS Realease 10.8, ESRI."},{"key":"ref_56","unstructured":"Suarez-Minguez, J.C. (2010). An Analysis of the Consequences of Stand Variability in Sitka Spruce Plantations in Britain Using a Combination of Airborne LiDAR Analysis and Models, University of Sheffield."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"1355","DOI":"10.14358\/PERS.73.12.1355","article-title":"Estimating basal area and stem volume for individual trees from LiDAR data","volume":"73","author":"Chen","year":"2007","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_58","unstructured":"R Core Team (2023). R: A Language and Environment for Statistical Computing, 4.3.1, R Foundation for Statistical Computing."},{"key":"ref_59","unstructured":"RStudio Team (2023). RStudio: Integrated Development for R, RStudio, PBC."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.21105\/joss.01686","article-title":"Welcome to the tidyverse","volume":"4","author":"Wickham","year":"2019","journal-title":"J. Open Source Softw."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v067.i01","article-title":"Fitting Linear Mixed-Effects Models Using\u2014lme4","volume":"67","author":"Bates","year":"2015","journal-title":"J. Stat. Softw."},{"key":"ref_62","unstructured":"Hamner, B., and Frasco, M. (2018). Metrics: Evaluation Metrics for Machine Learning, R Package Team. R Package Version 0.1.4."},{"key":"ref_63","unstructured":"Cook, R.D., and Weisberg, S. (2009). Applied Regression Including Computing and Graphics, John Wiley & Sons."},{"key":"ref_64","first-page":"819","article-title":"A new growth curve and its application to timber yield studies","volume":"37","author":"Schumacher","year":"1939","journal-title":"J. For."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"267","DOI":"10.1016\/S0378-1127(97)00090-X","article-title":"Augmenting empirical stand projection equations with edaphic and climatic variables","volume":"98","author":"Woollons","year":"1997","journal-title":"For. Ecol. Manag."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"127","DOI":"10.1016\/j.tree.2008.10.008","article-title":"Generalized linear mixed models: A practical guide for ecology and evolution","volume":"24","author":"Bolker","year":"2009","journal-title":"Trends Ecol. Evol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"719","DOI":"10.1093\/biomet\/78.4.719","article-title":"Estimation in generalized linear models with random effects","volume":"78","author":"Schall","year":"1991","journal-title":"Biometrika"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1016\/S0378-1127(02)00041-5","article-title":"Criteria for comparing the adaptability of forest growth models","volume":"172","author":"Robinson","year":"2003","journal-title":"For. Ecol. Manag."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0304-3800(96)01932-1","article-title":"Evaluating forest growth models","volume":"98","author":"Vanclay","year":"1997","journal-title":"Ecol. Model."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"201","DOI":"10.1016\/S0167-7152(96)00128-9","article-title":"Unifying the derivations for the Akaike and corrected Akaike information criteria","volume":"33","author":"Cavanaugh","year":"1997","journal-title":"Stat. Probab. Lett."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Onyutha, C. (2020). From R-squared to coefficient of model accuracy for assessing \u201cgoodness-of-fits\u201d. Geosci. Model Dev. Discuss., 1\u201325.","DOI":"10.5194\/gmd-2020-51"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"MIT Critical Data. (2016). Sensitivity analysis and model validation. Secondary Analysis of Electronic Health Records, Data, Springer International Publishing.","DOI":"10.1007\/978-3-319-43742-2"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1016\/j.foreco.2013.07.057","article-title":"Influence of competition and age on tree growth in structurally complex old-growth forests in northern Minnesota, USA","volume":"308","author":"Aakala","year":"2013","journal-title":"For. Ecol. Manag."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.foreco.2014.04.027","article-title":"Canopy space filling and tree crown morphology in mixed-species stands compared with monocultures","volume":"327","author":"Pretzsch","year":"2014","journal-title":"For. Ecol. Manag."},{"key":"ref_75","first-page":"264","article-title":"Quantification and incorporation of uncertainty in forest growth and yield projections using a Bayesian probabilistic framework: A demonstration for plantation coastal Douglas-fir in the Pacific Northwest, USA","volume":"11","author":"Willson","year":"2019","journal-title":"Math. Comput. For. Nat. Resour. Sci."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"207","DOI":"10.1016\/0378-1127(84)90068-9","article-title":"Problems of hypothesis testing of regressions with multiple measurements from individual sampling units","volume":"7","author":"West","year":"1984","journal-title":"For. Ecol. Manag."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1080\/00949658608810962","article-title":"Approaches to regression analysis with multiple measurements from individual sampling units","volume":"26","author":"West","year":"1986","journal-title":"J. Stat. Comput. Simul."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"4","DOI":"10.14214\/sf.a9197","article-title":"A conspectus on estimating function theory and its applicability to recurrent modeling issues in forest biometry","volume":"29","author":"Schabenberger","year":"1995","journal-title":"Silva Fenn."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/S0378-1127(00)00632-0","article-title":"Stochastic structure and individual-tree growth models","volume":"154","author":"Fox","year":"2001","journal-title":"For. Ecol. Manag."},{"key":"ref_80","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_81","first-page":"907","article-title":"A height prediction model with random stand and tree parameters: An alternative to traditional site index methods","volume":"34","author":"Lappi","year":"1988","journal-title":"For. Sci."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"287","DOI":"10.14214\/sf.a9214","article-title":"A method for using random parameters in analyzing permanent sample plots","volume":"29","author":"Penner","year":"1995","journal-title":"Silva Fenn."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"120843","DOI":"10.1016\/j.foreco.2023.120843","article-title":"Optimizing height measurement for the long-term forest experiments in Sweden","volume":"532","author":"Ogana","year":"2023","journal-title":"For. Ecol. Manag."},{"key":"ref_84","doi-asserted-by":"crossref","first-page":"120209","DOI":"10.1016\/j.foreco.2022.120209","article-title":"Mixed-effects generalized height-diameter model: A tool for forestry management of young sweet chestnut stands","volume":"514","author":"Dias","year":"2022","journal-title":"For. Ecol. Manag."},{"key":"ref_85","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.foreco.2015.08.035","article-title":"Separating effects of crown structure and competition for light on trunk growth of Sequoia sempervirens","volume":"358","author":"Coonen","year":"2015","journal-title":"For. Ecol. Manag."},{"key":"ref_86","doi-asserted-by":"crossref","first-page":"76","DOI":"10.1007\/s13595-021-01099-4","article-title":"Single-tree crown shape and crown volume models for Pinus nigra J. F. Arnold in central Italy","volume":"78","author":"Marchi","year":"2021","journal-title":"Ann. For. Sci."},{"key":"ref_87","first-page":"18","article-title":"Assessing tree crown volume\u2014A review","volume":"94","author":"Zhu","year":"2020","journal-title":"For. Int. J. For. Res."},{"key":"ref_88","doi-asserted-by":"crossref","first-page":"17","DOI":"10.1186\/s40663-015-0041-8","article-title":"Analysing the effect of stand density and site conditions on structure and growth of Oak species using Nelder trials along an environmental gradient: Experimental design, evaluation methods, and results","volume":"2","author":"Uhl","year":"2015","journal-title":"For. Ecosyst."},{"key":"ref_89","first-page":"364","article-title":"A new competition model for individual trees","volume":"17","author":"Bella","year":"1971","journal-title":"For. Sci."},{"key":"ref_90","doi-asserted-by":"crossref","first-page":"374","DOI":"10.1111\/jvs.12096","article-title":"Tree growth and competition in an old-growth Picea abies forest of boreal Sweden: Influence of tree spatial patterning","volume":"25","author":"Fraver","year":"2014","journal-title":"J. Veg. Sci."},{"key":"ref_91","doi-asserted-by":"crossref","first-page":"tpae044","DOI":"10.1093\/treephys\/tpae044","article-title":"Water status dynamics and drought tolerance of juvenile European beech, Douglas fir and Norway spruce trees as dependent on neighborhood and nitrogen supply","volume":"44","author":"Paligi","year":"2024","journal-title":"Tree Physiol."},{"key":"ref_92","doi-asserted-by":"crossref","first-page":"118369","DOI":"10.1016\/j.foreco.2020.118369","article-title":"On studying the patterns of individual-based tree mortality in natural forests: A modelling analysis","volume":"475","author":"Weiskittel","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_93","doi-asserted-by":"crossref","first-page":"1192","DOI":"10.1111\/geb.12081","article-title":"Climate-related variation in mortality and recruitment determine regional forest-type distributions","volume":"22","author":"Vanderwel","year":"2013","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_94","unstructured":"Ali, S.S., Dare, P., and Jones, S.D. (September, January 28). Fusion of remotely sensed multispectral imagery and LiDAR data for forest structure assessment at the tree level. Proceedings of the International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Beijing, China."},{"key":"ref_95","doi-asserted-by":"crossref","first-page":"653","DOI":"10.1093\/aob\/mcab111","article-title":"Terrestrial laser scanning: A new standard of forest measuring and modelling?","volume":"128","author":"Kaitaniemi","year":"2021","journal-title":"Ann. Bot."},{"key":"ref_96","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."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/13\/2270\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:02:24Z","timestamp":1760108544000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/13\/2270"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,6,21]]},"references-count":96,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2024,7]]}},"alternative-id":["rs16132270"],"URL":"https:\/\/doi.org\/10.3390\/rs16132270","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,6,21]]}}}