{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,24]],"date-time":"2026-04-24T13:57:01Z","timestamp":1777039021785,"version":"3.51.4"},"reference-count":83,"publisher":"MDPI AG","issue":"13","license":[{"start":{"date-parts":[[2020,7,1]],"date-time":"2020-07-01T00:00:00Z","timestamp":1593561600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Transformation to Continuous Cover Forestry (CCF) is a long and difficult process in which frequent management interventions rapidly alter forest structure and dynamics with long lasting impacts. Therefore, a critical component of transformation is the acquisition of up-to-date forest inventory data to direct future management decisions. Recently, the use of single tree detection methods derived from unmanned aerial vehicle (UAV) has been identified as being a cost effective method for inventorying forests. However, the rapidly changing structure of forest stands in transformation amplifies the difficultly in transferability of current individual tree detection (ITD) methods. This study presents a novel ITD Bayesian parameter optimisation approach that uses quantile regression and external biophysical tree data sets to provide a transferable and low cost ITD approach to monitoring stands in transformation. We applied this novel method to 5 stands in a variety of transformation stages in the UK and to a independent test study site in California, USA, to assess the accuracy and transferability of this method. Requiring small amounts of training data (15 reference trees) this approach had a mean test accuracy (F-score = 0.88) and provided mean tree diameter estimates (RMSE = 5.6 cm) with differences that were not significance to the ground data (p &lt; 0.05). We conclude that this method can be used to monitor forests stands in transformation and thus can also be applied to a wide range of forest structures with limited manual parameterisation between sites.<\/jats:p>","DOI":"10.3390\/rs12132115","type":"journal-article","created":{"date-parts":[[2020,7,2]],"date-time":"2020-07-02T02:44:25Z","timestamp":1593657865000},"page":"2115","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["A Transferable and Effective Method for Monitoring Continuous Cover Forestry at the Individual Tree Level Using UAVs"],"prefix":"10.3390","volume":"12","author":[{"given":"Guy","family":"Bennett","sequence":"first","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7928-8873","authenticated-orcid":false,"given":"Andy","family":"Hardy","sequence":"additional","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7435-0148","authenticated-orcid":false,"given":"Pete","family":"Bunting","sequence":"additional","affiliation":[{"name":"Department of Geography and Earth Sciences, Aberystwyth University, Aberystwyth SY23 3DB, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Philippe","family":"Morgan","sequence":"additional","affiliation":[{"name":"SelectFor Limited, Plas y Wenallt, Llanafan, Aberystwyth, Ceredigion SY23 4AX, UK"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-6310-3427","authenticated-orcid":false,"given":"Andrew","family":"Fricker","sequence":"additional","affiliation":[{"name":"Cal Poly, Social Sciences Department, Grand Avenue, San Luis Obispo, CA 93407, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,7,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"457","DOI":"10.1007\/s10584-014-1281-2","article-title":"The impacts of climate change across the globe: A multi-sectoral assessment","volume":"134","author":"Arnell","year":"2016","journal-title":"Clim. Chang."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1016\/j.foreco.2009.09.023","article-title":"Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems","volume":"259","author":"Lindner","year":"2010","journal-title":"For. Ecol. Manag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1038\/nclimate3303","article-title":"Forest disturbances under climate change","volume":"7","author":"Seidl","year":"2017","journal-title":"Nat. Clim. Chang."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1203","DOI":"10.1007\/s10531-013-0458-8","article-title":"Plantation forests, climate change and biodiversity","volume":"22","author":"Pawson","year":"2013","journal-title":"Biodivers. Conserv."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1093\/forestry\/cpv043","article-title":"What is close-to-nature silviculture in a changing world?","volume":"89","year":"2016","journal-title":"Forestry"},{"key":"ref_6","first-page":"37","article-title":"Towards a new forestry","volume":"95","author":"Franklin","year":"1989","journal-title":"Am. For."},{"key":"ref_7","unstructured":"Mason, B., and Kerr, G. (2000). Transforming Even-Aged Conifer Stands to Continuous Cover Management, Technical Report."},{"key":"ref_8","first-page":"492","article-title":"Suitability of close-to-nature silviculture for adapting temperate European forests to climate change","volume":"87","author":"Brang","year":"2014","journal-title":"For. Int. J. For. Res."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"87","DOI":"10.1016\/S0378-1127(00)00699-X","article-title":"Opportunities and strategies of transforming regular forests to irregular forests","volume":"151","year":"2001","journal-title":"For. Ecol. Manag."},{"key":"ref_10","unstructured":"Swift, D.E., Canadian Wood Fibre Centre, Ung, C.H., Wang, X., and Gagn\u00e9, R. (2013). Impacts of Partial Harvesting on Stand Dynamics and Tree Grades for Northern Hardwoods of the Acadian Forest Region, NRCan, Canadian Forest Service\u2014Canadian Wood Fibre Centre. Technical Report."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Pommerening, A., Pallar\u00e9s Ramos, C., K\u0229dziora, W., Haufe, J., and Stoyan, D. (2018). Rating experiments in forestry: How much agreement is there in tree marking?. PLoS ONE, 13.","DOI":"10.1371\/journal.pone.0194747"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.3390\/rs4061519","article-title":"Development of a UAV-LiDAR System with Application to Forest Inventory","volume":"4","author":"Wallace","year":"2012","journal-title":"Remote Sens."},{"key":"ref_13","doi-asserted-by":"crossref","unstructured":"Torresan, C., Berton, A., Carotenuto, F., Di, S.F., Gioli, B., Matese, A., Miglietta, F., Zaldei, A., Wallace, L., and Torresan, C. (2016). Forestry applications of UAVs in Europe: A review Forestry applications of UAVs in Europe: A review. Int. J. Remote Sens., 1\u201321.","DOI":"10.1080\/01431161.2016.1252477"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1016\/j.biocon.2016.03.027","article-title":"Seeing the forest from drones: Testing the potential of lightweight drones as a tool for long-term forest monitoring","volume":"198","author":"Zhang","year":"2016","journal-title":"Biol. Conserv."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1243","DOI":"10.1080\/01431160701736513","article-title":"High-quality image matching and automated generation of 3D tree models","volume":"29","author":"Baltsavias","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"15933","DOI":"10.3390\/rs71215809","article-title":"Comparison of Laser and Stereo Optical, SAR and InSAR Point Clouds from Air- and Space-Borne Sources in the Retrieval of Forest Inventory Attributes","volume":"7","author":"Yu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2971","DOI":"10.3390\/rs70302971","article-title":"Intercomparison of UAV, Aircraft and Satellite Remote Sensing Platforms for Precision Viticulture","volume":"7","author":"Matese","year":"2015","journal-title":"Remote Sens."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"351","DOI":"10.14358\/PERS.70.3.351","article-title":"Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery","volume":"70","author":"Wang","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_19","first-page":"214","article-title":"Continuous cover forestry in Britain","volume":"106","author":"Helliwell","year":"2012","journal-title":"Q. J. For."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Vauhkonen, J., Maltamo, M., McRoberts, R.E., and N\u00e6sset, E. (2014). Introduction to Forestry Applications of Airborne Laser Scanning. Forestry Applications of Airborne Laser Scanning, Springer.","DOI":"10.1007\/978-94-017-8663-8"},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Wallace, L., Lucieer, A., and Watson, C.S. (2014). Evaluating Tree Detection and Segmentation Routines on Very High Resolution UAV LiDAR Data. IEEE Trans. Geosci. Remote Sens., 52.","DOI":"10.1109\/TGRS.2014.2315649"},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Zhen, Z., Quackenbush, L., and Zhang, L. (2016). Trends in Automatic Individual Tree Crown Detection and Delineation\u2014Evolution of LiDAR Data. Remote Sens., 8.","DOI":"10.3390\/rs8040333"},{"key":"ref_23","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_24","doi-asserted-by":"crossref","unstructured":"Perrin, G., Descombes, X., and Zerubia, J. (2005, January 14). A marked point process model for tree crown extraction in plantations. Proceedings of the IEEE International Conference on Image Processing (ICIP), Genova, Italy.","DOI":"10.1109\/ICIP.2005.1529837"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"699","DOI":"10.14358\/PERS.82.9.699","article-title":"An Individual Tree-Based Automated Registration of Aerial Images to LiDAR Data in a Forested Area","volume":"82","author":"Lee","year":"2016","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"S1","DOI":"10.5589\/m08-055","article-title":"The influence of conifer forest canopy cover on the accuracy of two individual tree measurement algorithms using lidar data","volume":"34","author":"Falkowski","year":"2008","journal-title":"Can. J. Remote Sens."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"357","DOI":"10.14358\/PERS.72.4.357","article-title":"Detection of Individual Tree Crowns in Airborne Lidar Data","volume":"72","author":"Koch","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1007\/s40725-017-0051-6","article-title":"Individual Tree Crown Methods for 3D Data from Remote Sensing","volume":"3","author":"Lindberg","year":"2017","journal-title":"Curr. For. Rep."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"950","DOI":"10.3390\/rs4040950","article-title":"An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning","volume":"4","author":"Kaartinen","year":"2012","journal-title":"Remote Sens."},{"key":"ref_30","unstructured":"Monnet, J.M., Mermin, E., Chanussot, J., Berger, F., and Emgr, U. (2010, January 14\u201317). Tree top detection using local maxima filtering: A parameter sensitivity analysis Tree top detection using local maxima filtering: A parameter sensitivity analysis Tree top detection using local maxima filtering: A parameter sensitivity analysis. Proceedings of the 10th International Conference on LiDAR Applications for Assessing Forest Ecosystems (Silvilaser 2010), Freiburg, Germany."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Wu, X., Shen, X., Cao, L., Wang, G., and Cao, F. (2019). Assessment of Individual Tree Detection and Canopy Cover Estimation using Unmanned Aerial Vehicle based Light Detection and Ranging (UAV-LiDAR) Data in Planted Forests. Remote Sens., 11.","DOI":"10.3390\/rs11080908"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1122","DOI":"10.3390\/f5061122","article-title":"Sensitivity analysis of 3D individual tree detection from LiDAR point clouds of temperate forests","volume":"5","author":"Yao","year":"2014","journal-title":"Forests"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1508","DOI":"10.1016\/j.envsoft.2010.04.012","article-title":"How to avoid a perfunctory sensitivity analysis","volume":"25","author":"Saltelli","year":"2010","journal-title":"Environ. Model. Softw."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.envsoft.2019.01.012","article-title":"Why so many published sensitivity analyses are false: A systematic review of sensitivity analysis practices","volume":"114","author":"Saltelli","year":"2019","journal-title":"Environ. Model. Softw."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1093\/jpe\/rtt019","article-title":"Response of tree-ring width to climate warming and selective logging in larch forests of the Mongolian Altai","volume":"7","author":"Dulamsuren","year":"2014","journal-title":"J. Plant Ecol."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Montoro Girona, M., Rossi, S., Lussier, J.M., Walsh, D., and Morin, H. (2017). Understanding tree growth responses after partial cuttings: A new approach. PLoS ONE, 12.","DOI":"10.1371\/journal.pone.0172653"},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Alonzo, M., Andersen, H.E., Morton, D., and Cook, B. (2018). Quantifying Boreal Forest Structure and Composition Using UAV Structure from Motion. Forests, 9.","DOI":"10.3390\/f9030119"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"9632","DOI":"10.3390\/rs70809632","article-title":"Inventory of Small Forest Areas Using an Unmanned Aerial System","volume":"7","author":"Puliti","year":"2015","journal-title":"Remote Sens."},{"key":"ref_39","first-page":"53","article-title":"Using an Unmanned Aerial Vehicle (UAV) to capture micro-topography of Antarctic moss beds","volume":"27","author":"Lucieer","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2738","DOI":"10.1109\/TGRS.2013.2265295","article-title":"Direct Georeferencing of Ultrahigh-Resolution UAV Imagery","volume":"52","author":"Turner","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","unstructured":"Remke, A., Rodrigo-Comino, J., Gyasi-Agyei, Y., Cerd\u00e0, A., and Ries, J. (2018). Combining the Stock Unearthing Method and Structure-from-Motion Photogrammetry for a Gapless Estimation of Soil Mobilisation in Vineyards. ISPRS Int. J. Geo-Inf., 7.","DOI":"10.3390\/ijgi7120461"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1111\/phor.12259","article-title":"GPS precise point positioning for UAV photogrammetry","volume":"33","author":"Grayson","year":"2018","journal-title":"Photogramm. Rec."},{"key":"ref_43","unstructured":"Susse, R., Morgan, P.P., and Association Futaie Irr\u00e9guli\u00e8re (2011). Management of Irregular Forests: Developing the Full Potential of the Forest: Economic Aspects, Environmental Aspects, Social Aspects, Azur Multimedia."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"113","DOI":"10.1007\/s11104-007-9235-3","article-title":"Influence of soil thickness on stand characteristics in a Sierra Nevada mixed-conifer forest","volume":"294","author":"Meyer","year":"2007","journal-title":"Plant Soil"},{"key":"ref_45","doi-asserted-by":"crossref","unstructured":"Fricker, G.A., Ventura, J.D., Wolf, J.A., North, M.P., Davis, F.W., and Franklin, J. (2019). A Convolutional Neural Network Classifier Identifies Tree Species in Mixed-Conifer Forest from Hyperspectral Imagery. Remote Sens., 11.","DOI":"10.3390\/rs11192326"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2411","DOI":"10.1080\/01431161.2016.1225181","article-title":"Comparison of UAV photograph-based and airborne lidar-based point clouds over forest from a forestry application perspective","volume":"38","author":"Thiel","year":"2017","journal-title":"Int. J. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","unstructured":"Fujimoto, A., Haga, C., Matsui, T., Machimura, T., Hayashi, K., Sugita, S., and Takagi, H. (2019). An End to End Process Development for UAV-SfM Based Forest Monitoring: Individual Tree Detection, Species Classification and Carbon Dynamics Simulation. Forests, 10.","DOI":"10.3390\/f10080680"},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1080\/19475705.2017.1300608","article-title":"Estimating tree heights with images from an unmanned aerial vehicle","volume":"8","author":"Birdal","year":"2017","journal-title":"Geomat. Nat. Hazards Risk"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"607","DOI":"10.1109\/LGRS.2018.2803259","article-title":"Very High Resolution Object-Based Land Use\u2013Land Cover Urban Classification Using Extreme Gradient Boosting","volume":"15","author":"Georganos","year":"2018","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_50","doi-asserted-by":"crossref","unstructured":"Deckmyn, G., Mali, B., Kraigher, H., Torelli, N., Op de Beeck, M., and Ceulemans, R. (2009). Using the process-based stand model ANAFORE including Bayesian optimisation to predict wood quality and quantity and their uncertainty in Slovenian beech. Silva Fenn., 43.","DOI":"10.14214\/sf.204"},{"key":"ref_51","doi-asserted-by":"crossref","unstructured":"Sa\u010dkov, I., Kulla, L., and Bucha, T. (2019). A Comparison of Two Tree Detection Methods for Estimation of Forest Stand and Ecological Variables from Airborne LiDAR Data in Central European Forests. Remote Sens., 11.","DOI":"10.3390\/rs11121431"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Tanhuanp\u00e4\u00e4, T., Saarinen, N., Kankare, V., Nurminen, K., Vastaranta, M., Honkavaara, E., Karjalainen, M., Yu, X., Holopainen, M., and Hyypp\u00e4, J. (2016). Evaluating the Performance of High-Altitude Aerial Image-Based Digital Surface Models in Detecting Individual Tree Crowns in Mature Boreal Forests. Forests, 7.","DOI":"10.3390\/f7070143"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Sokolova, M., Japkowicz, N., and Szpakowicz, S. (2006). Beyond Accuracy, F-Score and ROC: A Family of Discriminant Measures for Performance Evaluation, Springer.","DOI":"10.1007\/11941439_114"},{"key":"ref_54","doi-asserted-by":"crossref","unstructured":"Goutte, C., and Gaussier, E. (2005). A Probabilistic Interpretation of Precision, Recall and F-Score, with Implication for Evaluation. Advances in Information Retrieval, Springer.","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"ref_55","doi-asserted-by":"crossref","unstructured":"Barnes, C., Balzter, H., Barrett, K., Eddy, J., Milner, S., and Su\u00e1rez, J.C. (2017). Remote sensing Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands. Remote Sens., 9.","DOI":"10.3390\/rs9030231"},{"key":"ref_56","unstructured":"Popescu, S.C., and Wynne, R.H. (2004). Seeing the trees in the forest: Using lidar and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogramm. Eng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1016\/j.ufug.2015.04.006","article-title":"Crown size and growing space requirement of common tree species in urban centres, parks, and forests","volume":"14","author":"Pretzsch","year":"2015","journal-title":"Urban For. Urban Green."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1098\/rsbl.2009.0228","article-title":"Plant height-crown radius and canopy coverage-density relationships determine above-ground biomass-density relationship in stressful environments","volume":"5","author":"Dai","year":"2009","journal-title":"Biol. Lett."},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Brieger, F., Herzschuh, U., Pestryakova, L.A., Bookhagen, B., Zakharov, E.S., and Kruse, S. (2019). Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds. Remote Sens., 11.","DOI":"10.3390\/rs11121447"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Nuijten, R., Coops, N., Goodbody, T., and Pelletier, G. (2019). Examining the Multi-Seasonal Consistency of Individual Tree Segmentation on Deciduous Stands Using Digital Aerial Photogrammetry (DAP) and Unmanned Aerial Systems (UAS). Remote Sens., 11.","DOI":"10.3390\/rs11070739"},{"key":"ref_61","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_62","doi-asserted-by":"crossref","first-page":"303","DOI":"10.5558\/tfc76303-2","article-title":"Height prediction equations using diameter and stand density measures","volume":"76","author":"Staudhammer","year":"2000","journal-title":"For. Chron."},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Goldbergs, G., Maier, S., Levick, S., and Edwards, A. (2018). Efficiency of Individual Tree Detection Approaches Based on Light-Weight and Low-Cost UAS Imagery in Australian Savannas. Remote Sens., 10.","DOI":"10.3390\/rs10020161"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Lutz, J.A., Larson, A.J., Freund, J.A., Swanson, M.E., and Bible, K.J. (2013). The Importance of Large-Diameter Trees to Forest Structural Heterogeneity. PLoS ONE, 8.","DOI":"10.1371\/journal.pone.0082784"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Fichtner, A., Forrester, D.I., H\u00e4rdtle, W., Sturm, K., and von Oheimb, G. (2015). Facilitative-Competitive Interactions in an Old-Growth Forest: The Importance of Large-Diameter Trees as Benefactors and Stimulators for Forest Community Assembly. PLoS ONE, 10.","DOI":"10.1371\/journal.pone.0120335"},{"key":"ref_66","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_67","first-page":"98","article-title":"PTrees: A point-based approach to forest tree extraction from lidar data","volume":"33","author":"Vega","year":"2014","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"2690","DOI":"10.1109\/TGRS.2013.2264548","article-title":"Bayesian approach to tree detection based on airborne laser scanning data","volume":"52","author":"Lahivaara","year":"2014","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Maltamo, M., Kallio, E., Bollands\u00e5s, O.M., N\u00e6sset, E., Gobakken, T., and Pesonen, A. (2014). Assessing Dead Wood by Airborne Laser Scanning. Forestry Applications of Airborne Laser Scanning, Springer.","DOI":"10.1007\/978-94-017-8663-8"},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Krause, S., Sanders, T.G., Mund, J.P., and Greve, K. (2019). UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring. Remote Sens., 11.","DOI":"10.3390\/rs11070758"},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Marques, P., P\u00e1dua, L., Ad\u00e3o, T., Hru\u0161ka, J., Peres, E., Sousa, A., and Sousa, J.J. (2019). UAV-Based Automatic Detection and Monitoring of Chestnut Trees. Remote Sens., 11.","DOI":"10.3390\/rs11070855"},{"key":"ref_72","unstructured":"Wolf, P.R., and Dewitt, B.A. (2000). Elements of Photogrammetry: With Applications in GIS, McGraw-Hill."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"132","DOI":"10.1016\/j.isprsjprs.2018.11.008","article-title":"Is field-measured tree height as reliable as believed\u2014A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest","volume":"147","author":"Wang","year":"2019","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"13895","DOI":"10.3390\/rs71013895","article-title":"Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure","volume":"7","author":"Dandois","year":"2015","journal-title":"Remote Sens."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1186\/s13021-015-0013-x","article-title":"Airborne lidar-based estimates of tropical forest structure in complex terrain: Opportunities and trade-offs for REDD+","volume":"10","author":"Leitold","year":"2015","journal-title":"Carbon Balance Manag."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"413","DOI":"10.14214\/sf.409","article-title":"Equilibrium curves and growth models to deal with forests in transition to uneven-aged structure-application in two sample stands","volume":"38","author":"Sterba","year":"2004","journal-title":"Silva Fenn."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Maltamo, M., Peuhkurinen, J., Malinen, J., Vauhkonen, J., Packal\u00e9n, P., and Tokola, T. (2009). Predicting tree attributes and quality characteristics of Scots pine using airborne laser scanning data. Silva Fenn., 43.","DOI":"10.14214\/sf.203"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1016\/j.rse.2010.01.016","article-title":"Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics","volume":"114","author":"Vauhkonen","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"3475","DOI":"10.3390\/rs6043475","article-title":"Multisource Single-Tree Inventory in the Prediction of Tree Quality Variables and Logging Recoveries","volume":"6","author":"Vastaranta","year":"2014","journal-title":"Remote Sens."},{"key":"ref_80","first-page":"1","article-title":"Estimation of diameter and height of individual trees for Pinus sylvestris L. based on the individualising of crowns using airborne LiDAR and the National Forestry Inventory data","volume":"25","author":"Sanz","year":"2016","journal-title":"For. Syst."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"1032","DOI":"10.3390\/f5051032","article-title":"Urban-Tree-Attribute Update Using Multisource Single-Tree Inventory","volume":"5","author":"Saarinen","year":"2014","journal-title":"Forests"},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"493","DOI":"10.1016\/j.rse.2007.04.018","article-title":"A LiDAR-derived canopy density model for tree stem and crown mapping in Australian forests","volume":"111","author":"Lee","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"6770","DOI":"10.1038\/s41598-017-07200-0","article-title":"Forest understory trees can be segmented accurately within sufficiently dense airborne laser scanning point clouds","volume":"7","author":"Hamraz","year":"2017","journal-title":"Sci. Rep."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2115\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T09:46:09Z","timestamp":1760175969000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/12\/13\/2115"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,7,1]]},"references-count":83,"journal-issue":{"issue":"13","published-online":{"date-parts":[[2020,7]]}},"alternative-id":["rs12132115"],"URL":"https:\/\/doi.org\/10.3390\/rs12132115","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,7,1]]}}}