iForest - Biogeosciences and Forestry


When a definition makes the difference: operative issues about tree height measures from RPAS-derived CHMs

Samuele De Petris   , Roberta Berretti, Filippo Sarvia, Enrico Borgogno Mondino

iForest - Biogeosciences and Forestry, Volume 13, Issue 5, Pages 404-408 (2020)
doi: https://doi.org/10.3832/ifor3411-013
Published: Sep 03, 2020 - Copyright © 2020 SISEF

Short Communications

Tree height (H) survey is a fundamental step in forest mensuration. The error affecting tree height measure, necessarily influences the correspondent tree estimates. The remotely survey of vegetation using PHODAR (PHOtogrammetric Detection And Ranging) or LiDAR (Light Detection And Ranging) techniques generates very high-density point clouds, that result into Canopy Height Models (CHMs) having GSD (Ground Sampling Distance) of few centimetres. This GSD value potentially allows to survey single crown apexes, which, from a forestry point of view, do not represent the actual tree height. Apex height value, in fact, does not represent the prevailing dendrometric height (PDH) but the maximum tree value. In this study we propose a new approach aimed at measuring dendrometric height by PHODAR derived CHM, taking care about this issue. The proposed method defines a correcting factor (found equal to 95% percentile of CHM values distribution within a given crown) for the tree height extraction from CHM based on the PDH concept. The method could be implemented to single crown approach in forest parameters extraction algorithms permitting more reliable results, especially in terms of tree volume and related estimations (e.g., carbon stock quantification, allometric models).


Tree Height, Prevailing Dendrometric Height, CHM, PHODAR, LiDAR

Authors’ address

Samuele De Petris 0000-0001-8184-9871
Roberta Berretti 0000-0002-1944-8855
Filippo Sarvia 0000-0003-4556-446X
Enrico Borgogno Mondino 0000-0003-4570-8013
DISAFA - Department of agriculture, forest and food sciences, University of Torino, Largo P. Braccini 2, Grugliasco, TO (Italy)

Corresponding author

Samuele De Petris


De Petris S, Berretti R, Sarvia F, Borgogno Mondino E (2020). When a definition makes the difference: operative issues about tree height measures from RPAS-derived CHMs. iForest 13: 404-408. - doi: 10.3832/ifor3411-013

Academic Editor

Carlotta Ferrara

Paper history

Received: Mar 23, 2020
Accepted: Jun 24, 2020

First online: Sep 03, 2020
Publication Date: Oct 31, 2020
Publication Time: 2.37 months

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Andersen H-E, Reutebuch SE, McGaughey RJ (2006)
A rigorous assessment of tree height measurements obtained using airborne lidar and conventional field methods. Canadian Journal of Remote Sensing 32: 355-366.
CrossRef | Gscholar
Bevington PR, Robinson DK (1974)
Data reduction and error analysis for the physical sciences. McGraw-Hill, New York, USA, vol. 4, pp. 428.
Bond BJ (2000)
Age-related changes in photosynthesis of woody plants. Trends in Plant Science 5: 349-353.
CrossRef | Gscholar
Borgogno Mondino E, Fissore V, Lessio A, Motta R (2016)
Are the new gridded DSM/DTMs of the Piemonte Region (Italy) proper for forestry? A fast and simple approach for a posteriori metric assessment. iForest - Biogeosciences and Forestry 9: 901-909.
CrossRef | Gscholar
Borgogno Mondino E, Gajetti M (2017)
Preliminary considerations about costs and potential market of remote sensing from UAV in the Italian viticulture context. European Journal of Remote Sensing 50: 310-319.
CrossRef | Gscholar
Bragg DC (2014)
Accurately measuring the height of (real) forest trees. Journal of Forestry 112: 51-54.
CrossRef | Gscholar
Brovelli MA, Crespi M, Fratarcangeli F, Giannone F, Realini E (2008)
Accuracy assessment of high resolution satellite imagery orientation by leave-one-out method. ISPRS Journal of Photogrammetry and Remote Sensing 63: 427-440.
CrossRef | Gscholar
De Petris S, Berretti R, Sarvia F, Borgogno Mondino E (2019)
Precision arboriculture: a new approach to tree risk management based on geomatics tools. In: Proceedings of the Conference “SPIE Remote Sensing 2019”. SPIE, Remote Sensing for Agriculture, Ecosystems, and Hydrology 21: 111491G.
CrossRef | Gscholar
Fritz A, Kattenborn T, Koch B (2013)
UAV-based photogrammetric point clouds - tree stem mapping in open stands in comparison to terrestrial laser scanner point clouds. ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-1/W 2: 141-146.
CrossRef | Gscholar
Hassaan O, Nasir AK, Roth H, Khan MF (2016)
Precision forestry: trees counting in urban areas using visible imagery based on an unmanned aerial vehicle. IFAC-PapersOnLine 49: 16-21.
CrossRef | Gscholar
Hyyppa J, Kelle O, Lehikoinen M, Inkinen M (2001)
A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners. IEEE Transactions on Geoscience and Remote Sensing 39 (5): 969-975.
CrossRef | Gscholar
Isenburg M (2012)
LAStools - efficient tools for LiDAR processing. Web site.
Online | Gscholar
Jakubowski M, Li W, Guo Q, Kelly M (2013)
Delineating individual trees from LiDAR data: a comparison of vector-and raster-based segmentation approaches. Remote Sensing 5: 4163-4186.
CrossRef | Gscholar
Jayaraman K (2000)
A statistical manual for forestry research. Forestry research support programme for Asia and the pacific. FAO-UN Regional Office for Asia and the Pacific, Bangkok, Thailand, pp. 32-34.
Jayathunga S, Owari T, Tsuyuki S (2018)
Evaluating the performance of photogrammetric products using fixed-wing UAV imagery over a mixed conifer-broadleaf forest: comparison with airborne laser scanning. Remote Sensing 10 (2): 187.
CrossRef | Gscholar
Larsen DR, Hann DW, Stearns-Smith SC (1987)
Accuracy and precision of the tangent method for measuring tree height. Western Journal of Applied Forestry 2: 26-28.
CrossRef | Gscholar
Lisein J, Pierrot-Deseilligny M, Bonnet S, Lejeune P (2013)
A Photogrammetric Workflow for the Creation of a forest canopy height model from small unmanned aerial system imagery. Forests 4: 922-944.
CrossRef | Gscholar
Monnet J-M, Mermin E, Chanussot J, Berger F (2010)
Tree top detection using local maxima filtering: a parameter sensitivity analysis. In: Proceedings of the “10th International Conference on LiDAR Applications for Assessing Forest Ecosystems”. Freiburg (Germany) 14-17 Sept 2010. Silvilaser, Freiburg, Germany, pp. 3-5.
Online | Gscholar
Nevalainen O, Honkavaara E, Tuominen S, Viljanen N, Hakala T, Yu X, Hyyppä J, Saari H, Pölönen I, Imai NN (2017)
Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sensing 9 (3): 185.
CrossRef | Gscholar
Ni W, Liu J, Zhang Z, Sun G, Yang A (2015)
Evaluation of UAV-based forest inventory system compared with LiDAR data. In: Proceedings of the “2015 IEEE International Geoscience and Remote Sensing Symposium (IGARSS)”. IEEE, Milan, Italy.
CrossRef | Gscholar
St-Onge B, Audet F-A, Bégin J (2015)
Characterizing the height structure and composition of a boreal forest using an individual tree crown approach applied to photogrammetric point clouds. Forests 6: 3899-3922.
CrossRef | Gscholar
Van Laar A, Akça A (2007)
Forest mensuration (2nd edn), Springer, Dordrecht, Netherlands, pp. 47-54.
Online | Gscholar
Wallace L, Lucieer A, Watson C, Turner D (2012)
Development of a UAV-LiDAR system with application to forest inventory. Remote Sensing 4: 1519-1543.
CrossRef | Gscholar
Wallace L, Musk R, Lucieer A (2014)
An assessment of the repeatability of automatic forest inventory metrics derived from UAV-borne laser scanning data. IEEE Transactions on Geoscience and Remote Sensing 52: 7160-7169.
CrossRef | Gscholar
Wang L, Gong P, Biging GS (2004)
Individual tree-crown delineation and treetop detection in high-spatial-resolution aerial imagery. Photogrammetric Engineering and Remote Sensing 70: 351-357.
CrossRef | Gscholar
West PW (2009)
Tree and forest measurement. Springer, Berlin, Germany, pp. 19-24.
CrossRef | Gscholar
Yang J, He Y, Caspersen JP, Jones TA (2017)
Delineating individual tree crowns in an uneven-aged, mixed broadleaf forest using multispectral watershed segmentation and multiscale fitting. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 10: 1390-1401.
CrossRef | Gscholar
Zambarda A, Cerny M, Vopnka P (2010)
Field-map - the new technology designed by IFER for the collection and processing of forest inventory data. Sherwood - Foreste ed Alberi Oggi 33-38.

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