ESTIMATING INDIVIDUAL TREE HEIGHTS AND DBHS FROM VERTICALLY DISPLACED SPHERICAL IMAGE PAIRS

Haozhou Wang, Ting-Ru Yang, Joni Waldy, John A Kershaw Jr.

Abstract


Individual tree parameters, such as diameter at breast height (DBH) and tree height, are fundamental measurements in forest inventory, and often labour intensive and require significant financial expenditures. Applying digital imaging in forest inventory is an efficient way to decrease the workload. In this study, spherical images taken using a novel commercial 360° camera (Ricoh Theta S) and stereographic geometry were applied to obtain these parameters directly without stitching multiple images from common cameras. This technology was validated in both a sparse urban forest (pairwise comparison) and denser real forest (distributional comparison) in Atlantic Canada. The DBH (r2 > 0.76) and height (Dmax < 0.25, K-S test) showed high correspondence with field measures. The spherical camera represents a low-cost option to terrestrial laser scanning and has potential to produce more accurate forest-level estimates with quicker field and office processing time than current under-canopy remote sensing technologies. 

Keywords


panorama images; digital camera; forest inventory; remote sensing; horizontal point sampling

Full Text:

PDF

References


Aghayari, S., Saadatseresht, M., Omidalizarandi,M., Neumann, I., 2017. Geometric Calibrationof Full Spherical Panoramic Ricoh-Theta Camera. ISPRS Annals of Photogrammetry, RemoteSensing and Spatial Information Sciences IV1/W1, 237–245. at: https://doi.org/10.5194/isprs-annals-IV-1-W1-237-2017

Bell, J.F., Iles, K., Marshall, D., 1983. Balancing theratio of tree count-only sample points and VBARmeasurements in variable plot sampling., in: Bell

J.F. and Atterbury, T. (Eds.). Proceedings: Renewable Resource Inventories for Monitoring Changes andTrends. College of Forestry, Oregon State University,Corvallis, OR, pp. 699–702.

Belton, D., Moncrieff, S., Chapman, J., 2013. Processing tree point clouds using Gaussian Mixture Models,in: ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences. Presented atthe ISPRS Workshop Laser Scanning 2013, Copernicus GmbH, Antalya, Turkey, pp. 43–48. at: https://doi.org/10.5194/isprsannals-II-5-W2-43-2013

Berveglieri, A., Tommaselli, A., Liang, X., Honkavaara,E., 2017. Photogrammetric measurement of tree stemsfrom vertical fisheye images. Scandinavian Journal ofForest Research 32, 737–747. at: https://doi.org/10.1080/02827581.2016.1273381

Bitterlich, W., 1984. The relascope idea: Relative measurements in forestry, First. ed. CAB International,Slough, England.

Blake, J., Somers, G., Ruark, G., 1991. Estimating limiting foliar biomass in conifer plantations from allometric relationships and self-thinning behavior. ForSci 37, 296–307.

Celes, C.H.S., Araujo, R.F. de, Emmert, F., Lima,A.J.N., Campos, M.A.A., Celes, C.H.S., Araujo, R.F.de, Emmert, F., Lima, A.J.N., Campos, M.A.A.,2019. Digital Approach for Measuring Tree Diameters in the Amazon Forest. Floresta e Ambiente 26.at: https://doi.org/10.1590/2179-8087.038416

Clark, N., Wynne, R.H., Schmoldt, D.L., Araman, P.A.,Winn, M.F., 1998. Use of a non-metric digital camera for tree stem evaluation, in: Proceedings, 1998ASPRS/RT Annual Convention.(Pre-Published Version).

Clark, N.A., Wynne, R.H., Schmoldt, D.L., 2000a. Areview of past research on dendrometers. For Sci 46,570–576.

Clark, N.A., Wynne, R.H., Schmoldt, D.L., Winn,M., 2000b. An assessment of the utility of anon-metric digital camera for measuring standing trees. Computers and Electronics in Agriculture 28, 151–169. at: https://doi.org/10.1016/S0168-1699(00)00125-3

Dai, X., 2018. Bias correction in panoramic photo-basedangle count sampling. Unpub. BScF Honors. University of New Brunswick, Fredericton, NB, Canada.

Dai, X., Ducey, M.J., Kershaw, J.A., Jr., Wang H., Inreview. Sector subsampling as an alternative to bigBAF sampling. Canadian Journal of Forest Research.

Dean, C., 2003. Calculation of wood volume and stemtaper using terrestrial single-image close-range photogrammetry and contemporary software tools. SilvaFenn. 37, 359–380.

DeCourt, N., 1956. Utilisation de la photographie pourmesurer les surfaces terri`eres (The use of photographyfor measuring basal area). Rev For Fran 8, 505–507.

Dick, A.R., 2012. Forest inventory using a camera: Concept, field implementation and instrument development (Unpublished MScF Thesis). University of NewBrunswick, Fredericton, NB, Canada.

Dick, A.R., Kershaw, J.A., MacLean, D.A., 2010. Spatial Tree Mapping Using Photography. north j applfor 27, 68–74. at: https://doi.org/10.1093/njaf/27.2.68

Donnelly J.G., Lavigne M.B., van Nostrand D.A., 1986.Precommercial Thinning Spacing Trials EstablishedBetween 1979 and 1985. Newfoundland Forestry Centre, St. John’s Newfoundland, Canada.

Fang, R., and B. Strimbu. 2017. Photogrammetric point cloud trees. Mathematical and Computational Forestry & Natural Resource Sciences9:30–33. at: http://www.mcfns.net/index.php/Journal/article/view/9.8.

Fastie, C.L., 2010. Estimating stand basal area from forest panoramas, in: Proceedings of the Fine International Conference on Gigapixel Imaging for Science.Carnegie Mellon University, Pittsburg, PA, p. 8.Forsman, M., B¨orlin, N., Holmgren, J., 2016. Estimation of Tree Stem Attributes Using Terrestrial Photogrammetry with a Camera Rig. Forests 7, 61. at:https://doi.org/10.3390/f7030061

Gadow, K. von, Zhang, C.Y., Zhao, X.H., 2009.Science-based Forest Design. Mathematical and Computational Forestry & Natural-Resource Sciences(MCFNS) 1, 14-25 (12). at: http://mcfns.net/index.php/Journal/article/view/MCFNS.1-14

Gollob, C., Ritter, T., Wassermann, C., Nothdurft, A.,2019. Influence of Scanner Position and Plot Size onthe Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on ForestInventory Plots. Remote Sensing, 11(13), 1602. at:https://doi.org/10.3390/rs11131602.

Grosenbaugh, L.R., 1963. Optical dendrometers for outof-reach diameters: A conspectus and some new theory. For Sci Monog 4, 48. at: https://doi.org/10.1093/forestscience/9.s2.a0001

Guido, van R., 2018. Python (programming language).Python Software Foundation, US.

Hayashi, R., Kershaw, J.A., Jr., Weiskittel, A.R.,2015. Evaluation of alternative methods for usingLiDAR to predict aboveground biomass in mixedspecies and structurally complex forests in northeastern North America. Mathematical and Computational Forestry & Natural Resources Sciences 7,49–65. at: http://mcfns.net/index.php/Journal/article/view/MCFNS7.2_2

Hodges, J.L., 1958. The significance probability of thesmirnov two-sample test. Ark. Mat. 3, 469–486. at:https://doi.org/10.1007/BF02589501

Husch, B., 1980. How to determine what you can afford to spend on inventories, in: IUFRO Workshopon Arid Land Resource Inventories. USDA, ForestService, Washington Office, General Technical ReportWO-28, La Paz, Mexico, pp. 98–102.

Iles, K., 2003. A sampler of inventory topics, 2nd ed.Kim Iles and Associates, Nanaimo, BC.

Iles, K., 2012. Some Current Subsampling Techniques in Forestry. Mathematical and Computational Forestry & Natural-Resource Sciences 4,77–80. at: http://mcfns.net/index.php/Journal/article/view/143/MCNFS-4.2_77

Kershaw, J.A., Jr., Ducey, M.J., Beers, T.W., Husch, B.,2016. Forest Mensuration, 5th ed. Wiley/Blackwell,

Hobokin, NJ.Lambert, M.C., Ung, C.H., Raulier, F., 2005. Canadiannational tree aboveground biomass equations. Can JFor Res 35, 1996–2018. at: https://doi.org/10.1139/x05-112

Larsen, D.R., 2006a. Use of very high resolution digital oblique photography in the development of 3-dimensional models for tree measurements: Examples from ground based and aerial based platforms.Presented at the Proceedings of the 20th BiennialWorkshop on Color Photography, Videography andAirborne Imaging for Resource Assessment., American Society of Photogrammetry and Remote Sensing(published by ASPRS on CD).

Larsen, D.R., 2006b. Development of a photogrammetric method of measuring tree taper outside bark. Gen.Tech. Rep. SRS-92. Asheville, NC: U.S. Departmentof Agriculture, Forest Service, Southern Research Station. pp. 347-350.

Liang, X., Jaakkola, A., Wang, Y., Hyypp¨a, J.,Honkavaara, E., Liu, J., Kaartinen, H., 2014. TheUse of a Hand-Held Camera for Individual Tree3D Mapping in Forest Sample Plots. Remote Sensing 6, 6587–6603. at: https://doi.org/10.3390/rs6076587

Liang, X., Wang, Y., Jaakkola, A., Kukko, A., Kaartinen, H., Hyypp¨a, J., Honkavaara, E., Liu, J.,2015. Forest Data Collection Using Terrestrial ImageBased Point Clouds From a Handheld Camera Compared to Terrestrial and Personal Laser Scanning.IEEE Transactions on Geoscience and Remote Sensing 53, 5117–5132. at: https://doi.org/10.1109/TGRS.2015.2417316

Liu, J., Feng, Z., Yang, L., Mannan, A., Khan, T.U.,Zhao, Z., Cheng, Z., 2018. Extraction of SamplePlot Parameters from 3D Point Cloud Reconstruction Based on Combined RTK and CCD ContinuousPhotography. Remote Sensing 10, 1299. at: https://doi.org/10.3390/rs10081299

Lu, M.K., Lam, T.Y., Perng, B.-H., Lin, H.-T., 2019.Close-range photogrammetry with spherical panoramas for mapping spatial location and measuring diameters of trees under forest canopies. Can. J. For.Res. 49, 865–874. at: https://doi.org/10.1139/cjfr-2018-0430

Marshall, D.D., Iles, K., Bell, J.F., 2004. Using a largeangle gauge to select trees for measurement in variableplot sampling. Can J For Res 34, 840–845. at: https://doi.org/10.1139/x03-240

Miller, J., Morgenroth, J., Gomez, C., 2015. 3D modelling of individual trees using a handheld camera:Accuracy of height, diameter and volume estimates.Urban Forestry & Urban Greening 14, 932–940. at:https://doi.org/10.1016/j.ufug.2015.09.001

Mokroš, M., Výbošťok, J., Tomaštík, J., Grznárová, A., Valent, P., Slavík, M., Merganič, J., 2018. High Precision Individual Tree Diameter and Perimeter Estimation from Close-Range Photogrammetry. Forests 9, 696. at: https://doi.org/10.3390/f9110696

Mulverhill, C., Coops, N.C., Tompalski, P., Bater,C.W., Dick, A.R., 2019. The utility of terrestrialphotogrammetry for assessment of tree volume andtaper in boreal mixedwood forests. Annals of Forest Science 76, 83. at: https://doi.org/10.1007/s13595-019-0852-9

Pan, Y., Birdsey, R.A., Phillips, O.L., Jackson, R.B.,2013. The Structure, Distribution, and Biomass of theWorld’s Forests. Annual Review of Ecology, Evolution, and Systematics 44, 593–622. at: https://doi.org/10.1146/annurev-ecolsys-110512-135914

Pengle, C., Jinhao, L., Dian, W., 2013. Measuring diameters at breast height using combination methodof laser and machine vision (In Chinese). Transactionsof the Chinese Society for Agricultural Machinery 44,271–275.

Perng, B.H., Lam, T.Y., Lu, M.K., 2018. Stereoscopicimaging with spherical panoramas for measuring treedistance and diameter under forest canopies. Forestry(Lond) 91, 662–673. at: https://doi.org/10.1093/forestry/cpy028

Reineke, L.H., 1940. Permanent sample plot photography. Journal of Forestry 38, 813–815.Reu, P. L., Sweatt, W., Miller, T., Fleming, D., 2014.Camera system resolution and its influence on digita;image correlation (Report No. SAND2013-8737J; p.26). Albuquerque, NM: Sandia National Laboratory.

Ricoh Imaging Company, LTD., 2016. Rioch Theta S 360video camera [WWW Document]. THETA S — RICOH IMAGING. at: http://www.ricoh-imaging.co.jp/english/products/theta_s.

Ritter, T., Nothdurft, A., Saborowski, J., 2013. Correcting the nondetection bias of angle count sampling.Canadian Journal of Forest Research. 43, 344–354. at:https://doi.org/10.1139/cjfr-2012-0408.

Ringdahl, O., Hohnloser, P., Hellstr¨om, T., Holmgren,J., Lindroos, O., 2013. Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner.Remote Sensing 5, 4839–4856. at: https://doi.org/10.3390/rs5104839

Rodríguez-García, C., Montes, F., Ruiz, F., Cañellas, I., Pita, P., 2014. Stem mapping and estimating standing volume from stereoscopic hemispherical images. Eur J Forest Res 133, 895–904. at: https://doi.org/10.1007/s10342-014-0806-6

Sánchez-González, M., Cabrera, M., Herrera, P.J., Vallejo, R., Cañellas, I., Montes, F., 2016. Basal Areaand Diameter Distribution Estimation Using Stereoscopic Hemispherical Images. Photogrammetric Engineering & Remote Sensing 82, 605–616. at: https://doi.org/10.14358/PERS.82.8.605

Shimizu, A., Yamada, S., Arita, Y., 2014. DiameterMeasurements of the Upper Parts of Trees Using anUltra-Telephoto Digital Photography System. OpenJournal of Forestry 4, 316–326. at: https://doi.org/10.4236/ojf.2014.44038

Smith, W.B., Brand, G.J., 1983. Allometric biomassequations for 98 species of herbs, shrubs, and smalltrees (Research Note No. RN-NC–299). USDA, ForestService, North Central Forest Experiment Station.

Snavely, N., Seitz, S.M., Szeliski, R., 2008. Modeling theWorld from Internet Photo Collections. InternationalJournal of Computer Vision 80, 189–210. at: https://doi.org/10.1007/s11263-007-0107-3

Stewart, B., 2004. Using a camera as an angle gauge inangle-count sampling (MF Thesis). The University ofGeorgia.

Surový, P., Yoshimoto, A., Panagiotidis, D., 2016. Accuracy of Reconstruction of the Tree Stem SurfaceUsing Terrestrial Close-Range Photogrammetry. Remote Sensing 8, 123. at: https://doi.org/10.3390/rs8020123

Varjo, J., Henttonen, H., Lappi, J., Heikkonen, J.,Juuj¨arvi, J., 2006. Digital horizontal tree measurements for forest inventory. Working papers of theFinnish Forest Research Institute 23.

Wang, H., 2017. Extracting DBH measurements fromRGB photo images. Unpub. BScF Honors. TheUniversity of New Brunswick, Fredericton, NB,Canada. at: http://rgdoi.net/10.13140/RG.2.2.30588.77440

Wang, H., 2019. Estimating Forest Attributes fromSpherical Images. MSc Forestry thesis. The Universityof New Brunswick, Fredericton, NB, Canada. at:https://www.doi.org/10.13140/RG.2.2.35680.64004

Wang, H., Kershaw, J.A., Yang, T.R., Hsu, Y.H.,Ma, X., Chen, Y., 2020. An Integrated System forEstimating Forest Basal Area from Spherical Images. Mathematical and Computational Forestry &Natural-Resource Sciences. at: http://mcfns.net/index.php/Journal/article/view/12.1

Xing, Z., Bourque, C.P.A., Swift, D.E., Clowater,C.W., Krasowski, M., Meng, F.R., 2005. Carbon andbiomass partitioning in balsam fir (Abies balsamea).Tree Physiol 25, 1207–1217.

Yang, T.R., Hsu, Y.H., Kershaw, J.A., McGarrigle, E.,Kilham, D., 2017. Big BAF sampling in mixed speciesforest structures of northeastern North America: influence of count and measure BAF under cost constraints. Forestry (Lond) 90, 649–660. at: https://doi.org/10.1093/forestry/cpx020

Zar, J.H., 2009. Biostatistical analysis, 5th ed. Pearson,New York.

Zianis, D., Muukkonen, P., M¨akip¨a¨a, R., Mencuccini,M., 2005. Biomass and stem volume equations for treespecies in Europe. Silva Fenn Monog 4, 63.


Refbacks

  • There are currently no refbacks.


   

© 2008 Mathematical and Computational Forestry & Natural-Resource Sciences