Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution


  • Ivan Balenović Croatian Forest Research Institute,Zagreb, Croatia
  • Ante Seletković University of Zagreb, Faculty of Forestry, Zagreb, Croatia
  • Renata Pernar University of Zagreb, Faculty of Forestry, Zagreb, Croatia
  • Anamarija Jazbec University of Zagreb, Faculty of Forestry, Zagreb, Croatia



tree height, mean stand height, stereo-measurement, digital aerial images, digital photogrammetric workstation


Tree height is one of the more fundamental measurements in forest inventories. In addition to classical field measurements, tree height may be estimated by remote sensing methods, such as by photogrammetric measurements of aerial images. Since it has been found and generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests, the usefulness of photogrammetric-based forest inventory in many countries remains a controversial issue. Therefore, this paper focuses on investigating the possibility of applying digital photogrammetric method to estimate mean stand height. Photogrammetric stereo-measurements of tree height were conducted on colour infrared images of high spatial resolution (ground sample distance – GSD – of 30 cm and 10 cm) using a digital photogrammetric workstation. The height of each tree within 183 sample plots (14 subcompartments) were calculated as the difference between the tree top elevations determined with the aerial images and the corresponding tree bottom elevations determined from the digital terrain model. To compare the photogrammetric- and field-estimated mean stand heights, the mean plot heights were calculated for both photogrammetric and field estimates of tree heights. Repeated measurements using ANOVA testing did not reveal a statistically significant difference (p > 0.05) between the field-estimated and photogrammetric-estimated mean stand heights using the 30 cm and 10 cm GSD digital aerial images. Deviations of the mean stand heights estimated using the images of both spatial resolutions were similar to the field-estimated heights. Using the 30 cm images the deviations of the photogrammetrically estimated mean stand height amounted to 0.35 m (1.59%) on average, whereas using the 10 cm images the deviations amounted to 0.31 m (1.41%) compared to the field estimation. Therefore, it can be concluded that the 30 cm GSD aerial images allow for the photogrammetric measurement of mean stand heights with accuracy similar to 10 cm GSD aerial images. In addition, 30 cm GSD aerial images are more favourable financially since the same area of interest could be covered with a considerably smaller number of images than of the 10 cm GSD aerial images.


Alberti G., Boscutti F., Pirotti F., Bertacco C., De Simon G., Sigura M., Cazorzi F., Bonfanti P., 2013. ALiDAR-based approach for a multi-purpose characterization of Alpine forests: an Italian case study. iForest - Biogesciences and Forestry 6: 156-168. DOI: 10.3832/ ifor0876-006 Anttila P., 1998. On the accuracy of treewise attributes obtained by analytical stereoplotter and aerial images. MSc thesis,UniversityofJoensuu, Faculty of Forestry, Joensuu, 36 p. Anttila P., 2005. Assessment of manual and automated methods for updating stand-level forest inventories based on aerial photography. PhD thesis,UniversityofJoensuu, Faculty of Forestry, Joensuu, 42 p. Web: Accessed: 2013. Arcangeli C., Klopf M., Hale S.E., Jenkins T.A.R., Hasenauer H., 2013. The uniform height curve method for height–diameter modelling: an application to Sitkaspruce in Britain. Forestry 87: 177-186. DOI: 10.1093/forestry/cpt041 BalenovićI., Marjanović H., Benko M., 2010. Primjena aerosnimaka u uređivanju šuma u Hrvatskoj [Application of aerial photographs in forest management inCroatia]. Šumarski list 134(11-12): 623-631. Balenović I., Seletković A., Pernar R., Marjanović H., Vuletić D., Paladinić E., Kolić J., Benko M., 2011. Digital photogrammetry – State of the art and potential for application in forest management in Croatia. South-east European forestry 2 (2): 81-93. DOI: 10.15177/ seefor.11-09 Balenović I., Seletković A., Pernar R., Marjanović H., Vuletić D., Benko M., 2012. Comparison of classical terrestrial and photogrammetric method in creating management division. In Pentek T., Poršinsky T., Šporčić M. (eds) ''Forest Engineering - Concern, Knowledge and Accountability in Today's Environment'', 8-12 October 2012,Dubrovnik. Forestry Faculty of UniversityZagreb, 13 p. BalenovićI., Alberti G., Marjanović H., 2013. Airborne Laser Scanning - the Status and Perspectives for the Application in the South-East European Forestry. South-east European forestry 4 (2): 59-79. DOI: 10.15177/seefor.13-07 Benko M., 1993. Procjena taksacijskih elemenata sastojina na infracrvenim kolornim aerosnimkama [Assessment of stands elements on colour infrared aerial photographs]. Glasnik za šumske pokuse 29: 199-274. Benko M.,BalenovićI., 2011. Prošlost, sadašnjost i budućnost primjene metoda daljinskih istraživanja pri inventuri šuma u Hrvatskoj [Past, present and future of application of remote sensing methods in Croatian forest inventory]. Šumarski list 135(13): 272-281. Bohlin J., Wallerman J., Fransson J.E.S., 2012. Forestvariable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM. Scandinavian Journal of Forest Research 27(7): 692-699. DOI: 10.1080/02827581.2012. 686625 Coops N.C., Hilker T., Wulder M.A., St-Onge B., Newnham G., Siggins A., Trofymow J.T., 2007. Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees 21(3): 295-310. DOI: 10.1007/s00468-006-0119-6 DavisC.S., 2002. Statistical Methods for the Analysis of Repeated Measurements. Springer,New York, 415 p. Eid T., Gobakken T., Næsset E., 2004. Comparing stand inventories for large areas based on photo-interpretation and laser scanning by means of cost-plus-loss analyses. Scandinavian Journal of ForestResearch 19(6): 512-523. DOI: 10.1080/02827580410019463 Falkowski M.J., Smith A.M.S., Hudak A.T., Gessler P.E., Vierling L.A., Crookston N.L., 2006. Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of lidar data. Canadian Journal of Remote Sensing 32(2): 153-161. DOI: 10.5589/m06-005 Ferdinent J.J., Padmanaban R.C., 2013. Development of a methodology to estimate biomass from tree height using airborne digital image. International Journal of Advanced Remote Sensing and GIS 2(1): 49-58. Gagnon P.A., Agnard J.P., Nolette C., 1993. Evaluation of a soft-copy photogrammetry system for tree-plot measurements. Canadian Journal of Remote Sensing 23(9): 1781-1785. DOI: 10.1139/x93-225 Gruber M., Ponticellia M., Bernögger S., Leberl L., 2008. Ultracamx, the Large Format Digital Aerial Camera System by Vexcel Imaging/Microsoft. In Chen J., Jiang J., Baudoin A. (eds.). Proceedings of ISPRS XXIst Congress "Silk Road for Information from Imagery", 3-11 July 2008,Beijing. ISPRS, Vol. XXXVII, Part B1, pp. 665-670. Heurich M., 2008. Automatic recognition and measurement of single trees based on data from airborne laser scanning over the richly structured natural forests of the BavarianForestNational Park. ForestEcology and Management 255(7): 2416-2433. DOI: 10.1016/j.foreco. 2008.01.022 Hill T., Lewicki P., 2007. STATISTICS: Methods and Applications. StatSoft,Tulsa,OK. Höhle J., Höhle M., 2009. Accuracy assessment of digital elevation models by means of robust statistical methods. ISPRS Journal of Photogrammetry and Remote Sensing 64(4): 398-406. DOI: 10.1016/ j.isprsjprs.2009.02.003 Holmgren J., Persson A., SödermanU., 2008. Species identification of individual trees by combining high resolution LIDAR data with multispectral images. International Journal of Remote Sensing 29(5): 1537-1552. DOI: 10.1080/01431160701736471 Honkavaara E., Arbiol R., Markelin L., Martinez L., Cramer M., Bovet S., Chandelier L., Ilves R., Klonus S., Marshal P., Shläpfer D., Tabor M., Thom C., Veje N., 2009. Digital airborne photogrammetry - a new tool for quantitiative remote sensing? A state-of-the-art review on radiometric aspects of digital photogrammetric images. Remote Sensing 1(3): 577-605. DOI: 10.3390/rs1030577 Hoxha B., 2012. Two-phased inventory of standing volume in mountain forests with the use of aerial photographs. Folia Forestalia Polonica 54(2): 123-133. Hunter M.O., Keller M., Vitoria D., Morton D.C., 2012. Tree height and tropical forest biomass estimation. Biogeosciences Discussions 10: 10491-10529. DOI: 10.5194/bgd-10-10491-2013 Hyyppä J., Hyyppä H., Leckie D., Gougeon F., Yu X., Maltamo M., 2008. Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests. International Journal of Remote Sensing 29(5): 1339-1366. DOI: 10.1080/014311607 01736489 Järndstedt J., Pekkarinen A., Tuominen S., Ginzler C., Holopainen M., Viitala R., 2012. Forestvariable estimation using a high-resolution digital surface model. ISPRS Journal of Photogrammetry and Remote Sensing 74: 78-84. DOI: 10.1016/j.isprsjprs.2012.08.006 Ke Y., Quackenbush L.J., 2011. Areview of methods for automatic individual tree-crown detection and delineation from passive remote sensing. International Journal of Remote Sensing 32(17): 4725-4747. DOI: 10.1080/01431161.2010.494184 KorpelaI., 2004. Individual tree measurements by means of digital aerial photogrammetry. Silva Fennica mon. 3: 1-93. KorpelaI., Anttila P., 2004. Appraisal of the mean height of trees by means of image matching of digitised aerial photographs. Photogrammetric Journal ofFinland19(1): 23-36. Kovats M.,1997. Alarge-scale aerial photographic technique for measuring tree heights on long-term forest installations. Photogrammetric Engineering and Remote Sensing 63(6): 741-747. Lemmens M., 2011. Digital Photogrammetric Workstations - Status and Features. GIM International 25: 12. Web: Accessed 2013. Lin Y., Hyyppä J., Kukko A., Jaakkola A., Kaartinen H., 2012. Tree height growth measurement with single-scan airborne, static terrestrial and mobile laser scanning. Sensors 12(9): 12798-12813. DOI: 10.3390/s120912798 Linder W., 2009. Digital photoogrammetry - A practical course. Springer, Berlin. 220 p. DOI: 10.1007/978-3-540-92725-9 Magnusson M., Fransson J.E.S., 2005. Evaluation of aerial photo-interpretation for estimation of forest stem volume at stand level. In Olsson H (ed.) "Operational Tools in Forestry Using Remote Sensing Techniques", 31 May-3 June, 2005, Borås. Swedish Forest Agency, Report 8, Vol C, pp. 102-106. Magnusson M., Fransson J.E.S., Olsson H., 2007. Aerial photo-interpretation using Z/I DMC images for estimation of forest variables. Scandinavian Journal of ForestResearch 22(3): 254-266. DOI: 10.1080/02827580701262964 Meyer P., Staenz K., Itten K.I., 1996. Semi-automated procedures for tree species identification in high spatial resolution data from digitized colour infrared-aerial photography. ISPRS Journal of Photogrammetry and Remote Sensing 51(1): 5-16. DOI: 10.1016/0924-2716(96)00003-2 MichailoffI., 1943. Zahlenmässiges Verfahren für die Ausführung der Bestandeshöhenkurven. Cbl. und Thar. Forstl. Jahrbuch 6: 273-279 Morgan J.L., Gergel S.E., Coops N.C., 2010. Aerial photography: A rapidly evolving tool for ecological management. BioScience 60(1): 47-59. DOI: 10.1525/bio.2010.60.1.9 Næsset E., 1996. Determination of number of stems in coniferous forest stands by means of aerial photo-interpretation. Scandinavian Journal of ForestResearch 11(1): 76-84. DOI: 10.1080/02827589609 382914 Næsset E., 2002a. Determination of mean tree height of forest stands by means of digital photogrammetry. Scandinavian Journal of ForestResearch 17(5): 446-459. DOI: 10.1080/028275802320435469 Næsset E., 2002b. Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data. Remote Sensing of Environment 80(1): 88-99. DOI: 10.1016/S0034-4257(01)00290-5 Næsset E., Gjevestad J.G., 2008. Performance of GPS Precise Point Positioning Under ConiferForestCanopies. Photogrammetric Engineering & Remote Sensing 74: 661-668. DOI: 10.14358/ PERS.74.5.661 Nurminen K., Karjalainen M., Yu X., Hyyppä J., Honkavaara E., 2013. Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables. ISPRS Journal of Photogrammetry and Remote Sensing 83: 104-115. DOI: 10.1016/ j.isprsjprs.2013.06.005 Paine D.P, Kiser J.D., 2012. Aerial photography and image interpretation. Third Edition. John Wiley & Sons, Inc., Hoboken, New Jersey. DOI: 10.1002/9781118110997 Pernar R., 1994. Način i pouzdanost određivanja oštećenosti hrasta lužnjaka (Quercus robur L.) na infracrvenim kolornim (ICK) aerosnimkama [Method and reliability of assessing pedunculate oak (Quercus robur L.) damage on colour infrared (CIR) aerial photographs]. Glasnik za šumske pokuse 31: 1-34. Pernar R., Seletković A., Ančić M., 2007a. Utvrđivanje oštećenosti šuma Spačvanskog bazena primjenom infracrvenih kolornih aerosnimaka [Assessing forest damage in the Spačva basin with colour infrared aerial photographs]. Šumarski list 131(7-8): 315-322. Pernar R., Ančić M., Seletković A., 2007b. Primjena ICK aerosnimaka za utvrđivanje oštećenosti šuma na području UŠP Gospić [Application of colour infrared aerial photographs for the assessment of forest damage in the Gospić Forest Administration]. Šumarski list 131(11-12): 507-521. PopescuS.C., 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. Photogrammetric Engineering and Remote Sensing 70(5): 589-604. DOI: 10.14358/PERS.70.5.589 Sandau R., 2010. Digital Airborne Camera, Introduction and Technology. Springer, Dordrecht, 343 p. DOI: 10.1007/978-1-4020-8878-0 Shapiro S.S., Wilk M.B., 1965. An analysis of variance test for normality (complete samples). Biometrika 52: 591-611. DOI: 10. 1093/biomet/52.3-4.591 Shapiro S.S., Wilk M.B., Chen H. J., 1968. Acomparative study of various tests for normality. Journal of the American Statistical Association 63: 1343-1372. DOI: 10.1080/01621459.1968.10480932 Spencer R.D., Hall R.J., 1988. Canadian large-scale aerial photographic systems (LSP). Photogrammetric Engineering and Remote Sensing 54(4): 475-482. St-Onge B., Jumelet J., Cobello M., Véga C., 2004. Measuring individual tree height using a combination of stereophotogrammetry and lidar. Canadian Journal of ForestResearch 34: 2122-2130. DOI: 10.1139/x04-093 St‐Onge B., Véga C., Fournier R.A., Hu Y., 2008. Mapping canopy height using a combination of digital stereo‐photogrammetry and lidar. International Journal of Remote Sensing 29(11): 3343-3364. DOI: 10.1080/01431160701469040 Tuominen S., Pitkänen J., Balazs A., Korhonen K. T., Hyvönen P., Muinonen E., 2014. NFI plots as complementary reference data in forest inventory based on airborne laser scanning and aerial photography in Finland. Silva Fennica 48 (2): article id 983. DOI: 10.14214/sf.983 Van Laar A., Akça A., 2007. Forestmensuration. Springer, Dordrecht, 376 p. DOI: 10.1007/978-1-4020-5991-9 Véga C., St-Onge B., 2008. Height growth reconstruction of a boreal forest canopy over a period of 58 years using a combination of photogrammetric and lidar models. Remote Sensing of Environment 112(4): 1784-1794. DOI: 10.1016/j.rse.2007.09.002 White J.C., Wulder M.A., Vastaranta M., Coops N.C., Pitt D., Woods M., 2013. The utility of image-based point clouds for forest inventory: A comparison with airborne laser scanning. Forests 4(3): 518-536. DOI: 10.3390/f4030518 Worley D.P., Landis G.H., 1954. The accuracy of height measurements with parallax instruments on 1:12000 photographs. Photogrammetric Engineering 20(1): 823-829. Zagalikis G., Cameron A.D., Miller D.R., 2005. The application of digital photogrammetry and image analysis techniques to derive tree and stand characteristics. Canadian Journal of ForestResearch 35(5): 1224-1237. DOI: 10.1139/x05-030






Research article