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Canadian Journal of Remote Sensing
Journal canadien de télédétection
Volume 50, 2024 - Issue 1
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Research Article

Estimating Tree Diameter at Breast Height (DBH) Using iPad Pro LiDAR Sensor in Boreal Forests

Estimation du diamètre des arbres à hauteur de poitrine (DHP) à l’aide du capteur LiDAR iPad Pro dans les forêts boréales

ORCID Icon, ORCID Icon, , &
Article: 2295470 | Received 07 Aug 2023, Accepted 11 Dec 2023, Published online: 18 Jan 2024

References

  • Aijazi, A.K., Checchin, P., Malaterre, L., and Trassoudaine, L. 2017. “Automatic Detection and Parameter Estimation of Trees for Forest Inventory Applications Using 3D Terrestrial LiDAR.” Remote Sensing, Vol. 9 ((No. 9): pp. 946. Article 9 doi:10.3390/rs9090946.
  • Apple 2020. Apple unveils new iPad Pro with LiDAR Scanner and trackpad support in iPadOS. Apple Newsroom. https://www.apple.com/newsroom/2020/03/apple-unveils-new-ipad-pro-with-lidar-scanner-and-trackpad-support-in-ipados/
  • Bauwens, S., Bartholomeus, H., Calders, K., and Lejeune, P. 2016. “Forest Inventory with Terrestrial LiDAR: A Comparison of Static and Hand-Held Mobile Laser Scanning.” Forests, Vol. 7 (No. 12): pp. 127. Article 6 doi:10.3390/f7060127.
  • Bilyk, A., Pulkki, R., Shahi, C., and Larocque, G.R. 2021. “Development of the Ontario Forest Resources Inventory: A historical review.” Canadian Journal of Forest Research, Vol. 51 (No. 2): pp. 198–209. doi:10.1139/cjfr-2020-0234.
  • Blanco, A.C., Tamondong, A.M., Perez, A.M.C., Ang, M.R.C.O., and Paringit, E.C. 2015. “The PHIL-LiDAR 2 Program: National Forest Resource Inventory of the Phillipines using LiDAR and other Remotely Sensed Data.” The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. XL-7/W3 pp. 1123–1127. doi:10.5194/isprsarchives-XL-7-W3-1123-2015.
  • Brede, B., Lau, A., Bartholomeus, H.M., and Kooistra, L. 2017. “Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.” Sensors (Basel, Switzerland), Vol. 17 (No. 10): pp. 2371. Article 10 doi:10.3390/s17102371.
  • Calders, K., Adams, J., Armston, J., Bartholomeus, H., Bauwens, S., Bentley, L.P., Chave, J., et al. 2020. “Terrestrial laser scanning in forest ecology: Expanding the horizon.” Remote Sensing of Environment, Vol. 251 pp. 112102. doi:10.1016/j.rse.2020.112102.
  • Castel, C., and D’Hoedt, M. 2022. Automated forest inventory using the iPad Pro LiDAR scanner [Masters]. Ecole Polytechnique de Louvain, Universite Cathiolique de Louvain.
  • Chen, Q., Gao, T., Zhu, J., Wu, F., Li, X., Lu, D., and Yu, F. 2022. “Individual Tree Segmentation and Tree Height Estimation Using Leaf-Off and Leaf-On UAV-LiDAR Data in Dense Deciduous Forests.” Remote Sensing, Vol. 14 (No. 12): pp. 2787. Article 12 doi:10.3390/rs14122787.
  • Chernov, N. 2022a. Circle Fit (Pratt method) (1.0.0) [MATLAB; Windows]. MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/22643-circle-fit-pratt-method
  • Chernov, N. 2022b. Circle Fit (Taubin method) (1.0.0) [MATLAB; Windows]. MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/22678-circle-fit-taubin-method
  • Chernov, N. 2022c. Ellipse Fit (Taubin Method) (1.0.0) [MATLAB; Windows]. MathWorks. https://www.mathworks.com/matlabcentral/fileexchange/22683-ellipse-fit-taubin-method
  • Chernov, N., and Lesort, C. 2004. “Statistical efficiency of curve fitting algorithms.” Computational Statistics & Data Analysis, Vol. 47 (No. 4): pp. 713–728. doi:10.1016/j.csda.2003.11.008.
  • Chernov, N., and Lesort, C. 2005. “Least squares Fitting of Circles.” Journal of Mathematical Imaging and Vision, Vol. 23 (No. 3): pp. 239–252. doi:10.1007/s10851-005-0482-8.
  • Chiappini, S., Pierdicca, R., Malandra, F., Tonelli, E., Malinverni, E.S., Urbinati, C., and Vitali, A. 2022. “Comparing Mobile Laser Scanner and manual measurements for dendrometric variables estimation in a black pine (Pinus nigra Arn.) plantation.” Computers and Electronics in Agriculture, Vol. 198: pp. 107069. doi:10.1016/j.compag.2022.107069.
  • Corradetti, A., Seers, T., Mercuri, M., Calligaris, C., Busetti, A., and Zini, L. 2022. “Benchmarking Different SfM-MVS Photogrammetric and iOS LiDAR Acquisition Methods for the Digital Preservation of a Short-Lived Excavation: A Case Study from an Area of Sinkhole Related Subsidence.” Remote Sensing, Vol. 14 (No. 20): pp. 5187. Article 20 doi:10.3390/rs14205187.
  • Côté, J.-F., Fournier, R.A., and Egli, R. 2011. “An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR.” Environmental Modelling & Software, Vol. 26 (No. 6): pp. 761–777. doi:10.1016/j.envsoft.2010.12.008.
  • Dassot, M., Constant, T., and Fournier, M. 2011. “The use of terrestrial LiDAR technology in forest science: Application fields, benefits and challenges.” Annals of Forest Science, Vol. 68 (No. 5): pp. 959–974. Article 5 doi:10.1007/s13595-011-0102-2.
  • ESRI 2023. ArcGIS Pro (3.10) [C++; Windows]. Redlands, United States of America: ESRI. esri.com/en-us/arcgis/products/arcgis-pro/overview
  • Girardeau-Montaut, D. 2022. CloudCompare—Open Source project (2.12.4 Kyiv) [C++; Windows]. CloudCompare. https://www.cloudcompare.org/
  • Girardeau-Montaut, D., and Rascale, P. 2022. CloudComPy: Python Wrapper for CloudCompare (2.12.4) [C++, Python; Windows]. CloudCompare (GPL). https://github.com/CloudCompare/CloudComPy
  • Gollob, C., Ritter, T., Kraßnitzer, R., Tockner, A., and Nothdurft, A. 2021. “Measurement of Forest Inventory Parameters with Apple iPad Pro and Integrated LiDAR Technology.” Remote Sensing, Vol. 13 (No. 16): pp. 3129. Article 16 doi:10.3390/rs13163129.
  • Gülci, S., Yurtseven, H., Akay, A.O., and Akgul, M. 2023. “Measuring tree diameter using a LiDAR-equipped smartphone: a comparison of smartphone- and caliper-based DBH.” Environmental Monitoring and Assessment, Vol. 195 (No. 6): pp. 678. doi:10.1007/s10661-023-11366-8.
  • Hopkinson, C., Chasmer, L., Young-Pow, C., and Treitz, P. 2004. “Assessing forest metrics with a ground-based scanning LiDAR.” Canadian Journal of Forest Research, Vol. 34 (No. 3): pp. 573–583. doi:10.1139/x03-225.
  • Hunčaga, M., Chudá, J., Tomaštík, J., Slámová, M., Koreň, M., and Chudý, F. 2020. “The Comparison of Stem Curve Accuracy Determined from Point Clouds Acquired by Different Terrestrial Remote Sensing Methods.” Remote Sensing, Vol. 12 (No. 17): pp. 2739. Article 17 doi:10.3390/rs12172739.
  • Hyyppä, E., Hyyppä, J., Hakala, T., Kukko, A., Wulder, M.A., White, J.C., Pyörälä, J., et al. 2020. “Under-canopy UAV laser scanning for accurate forest field measurements.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 164: pp. 41–60. doi:10.1016/j.isprsjprs.2020.03.021.
  • Hyyppä, E., Yu, X., Kaartinen, H., Hakala, T., Kukko, A., Vastaranta, M., and Hyyppä, J. 2020. “Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests.” Remote Sensing, Vol. 12 (No. 20): pp. 3327. Article 20 doi:10.3390/rs12203327.
  • Lee, J.B., Jung, J.H., and Kim, H.J. 2020. “Segmentation of Seabed Points from Airborne Bathymetric LiDAR Point Clouds Using Cloth Simulation Filtering Algorithm.” Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography, Vol. 38 (No. 1): pp. 1–9. doi:10.7848/ksgpc.2020.38.1.1.
  • Liang, X., Hyyppä, J., Kaartinen, H., Lehtomäki, M., Pyörälä, J., Pfeifer, N., Holopainen, M., et al. 2018. “International benchmarking of terrestrial laser scanning approaches for forest inventories.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 144 pp. 137–179. doi:10.1016/j.isprsjprs.2018.06.021.
  • Liu, G., Wang, J., Dong, P., Chen, Y., and Liu, Z. 2018. “Estimating Individual Tree Height and Diameter at Breast Height (DBH) from Terrestrial Laser Scanning (TLS) Data at Plot Level.” Forests, Vol. 9 (No. 7): pp. 398. Article 7 doi:10.3390/f9070398.
  • Liu, L., Zhang, A., Xiao, S., Hu, S., He, N., Pang, H., Zhang, X., and Yang, S. 2021. “Single Tree Segmentation and Diameter at Breast Height Estimation with Mobile LiDAR.” IEEE Access., Vol. 9: pp. 24314–24325. doi:10.1109/ACCESS.2021.3056877.
  • Lovell, J.L., Jupp, D.L.B., Culvenor, D.S., and Coops, N.C. 2003. “Using airborne and ground-based ranging lidar to measure canopy structure in Australian forests.” Canadian Journal of Remote Sensing, Vol. 29 (No. 5): pp. 607–622. doi:10.5589/m03-026.
  • Luetzenburg, G., Kroon, A., and Bjørk, A.A. 2021. “Evaluation of the Apple iPhone 12 Pro LiDAR for an Application in Geosciences.” Scientific Reports, Vol. 11 (No. 1):Article 22221. doi:10.1038/s41598-021-01763-9.
  • MathWorks 2022. MATLAB (r2022b) [C/C++]. Natick, United States of America: The MathWorks, Inc. https://www.mathworks.com/products/matlab.html
  • McClain, K.M., Morris, D.M., Hills, S.C., and Buse, L.J. 1994. “The effects on initial spacing on growth and crown development for planted northern conifers: 37-year results.” Forestry Chronicle., Vol. 70 (No. 2): pp. 174–182. doi:10.5558/tfc70174-2.
  • Moran, L.A., and Williams, R.A. 2002. “Comparison of Three Dendrometers in Measuring Diameter at Breast Height.” Northern Journal of Applied Forestry, Vol. 19 (No. 1): pp. 28–33. doi:10.1093/njaf/19.1.28.
  • Müller, A., Olschewski, R., Unterberger, C., and Knoke, T. 2020. “The valuation of forest ecosystem services as a tool for management planning – A choice experiment | Elsevier Enhanced Reader.” Journal of Environmental Management, Vol. 271 pp. 111008. doi:10.1016/j.jenvman.2020.111008.
  • [OMNRF] Ontario Ministry of Natural Resources and Forestry 2015. Forest Management Guide to Silviculture in the Great Lakes-St. Lawrence and Boreal Forests of Ontario. Queen’s Printer for Ontario.
  • [OMNRF] Ontario Ministry of Natural Resources and Forestry 2021. Vegetation Sampling Network Protocol: Technical specifications for field plots. Ontario Ministry of Natural Resources and Forestry, Science and Research Branch, Peterborough, ON. Science and Research Technical Manual TM-10. 173pp. + appendices.
  • Pfeifer, N., and Winterhalder, D. 2004. “Modelling of Tree Cross Sections from Terrestrial Laser Scanning Data with Free-Form Curves.” International Archives of Photogrammetry, Remote Sensing, and Spatial Information Sciences, Vol. 36 (No. 8): pp. 76–81.
  • Pratt, V. 1987. “Direct least-squares fitting of algebraic surfaces | Proceedings of the 14th annual conference on Computer graphics and interactive techniques.” ACM SIGGRAPH Computer Graphics, Vol. 21 (No. 4): pp. 145–152. ACM-0-89791-227-6/87/007/0145 doi:10.1145/37401.37420.
  • Szpak, D. Z. L. 2016. Guaranteed Ellipse Fitting with a Confidence Region and an Uncertainty Measure for Centre, Axes and Orientation [Matlab]. https://github.com/zygmuntszpak/guaranteed-ellipse-fitting-with-a-confidence-region-and-an-uncertainty-measure (Original work published 2015)
  • Szpak, Z.L., Chojnacki, W., and van den Hengel, A. 2015. “Guaranteed Ellipse Fitting with a Confidence Region and an Uncertainty Measure for Centre, Axes, and Orientation.” Journal of Mathematical Imaging and Vision, Vol. 52 (No. 2): pp. 173–199. doi:10.1007/s10851-014-0536-x.
  • Tatsumi, S., Yamaguchi, K., and Furuya, N. 2021. “ForestScanner: A mobile application for measuring and mapping trees with LiDAR-equipped iPhone and iPad.” Methods in Ecology and Evolution, Vol. 14 (No. 7): pp. 1603–1609. doi:10.1111/2041-210X.13900.
  • Taubin, G. 1991. “Estimation of planar curves, surfaces, and nonplanar space curves defined by implicit equations with applications to edge and range image segmentation.” IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol. 13 (No. 11): pp. 1115–1138. doi:10.1109/34.103273.
  • Tavani, S., Corradetti, A., Granado, P., Snidero, M., Seers, T.D., and Mazzoli, S. 2019. “Smartphone: An alternative to ground control points for orienting virtual outcrop models and assessing their quality.” Geosphere, Vol. 15 (No. 6): pp. 2043–2052. doi:10.1130/GES02167.1.
  • Tavani, S., Billi, A., Corradetti, A., Mercuri, M., Bosman, A., Cuffaro, M., Seers, T., and Carminati, E. 2022. “Smartphone assisted fieldwork: Towards the digital transition of geoscience fieldwork using LiDAR-equipped iPhones.” Earth-Science Reviews, Vol. 227 pp. 103969. doi:10.1016/j.earscirev.2022.103969.
  • Turner, K. 1974. Computer perception of curved objects using a television camera. Ph.D. Thesis, Dept. of Machine Intelligence, University of Edinburgh.
  • Veesus 2022. ZAPPCHA: Mobile LiDAR Scanner (5.6) [Swift; IOS]. Hastings, United Kingdom: Veesus. https://zappcha.com/
  • Wang, C., Ji, M., Wang, J., Wen, W., Li, T., and Sun, Y. 2019. “An Improved DBSCAN Method for LiDAR Data Segmentation with Automatic Eps Estimation.” Sensors (Basel, Switzerland), Vol. 19 (No. 1): pp. 172. doi:10.3390/s19010172.
  • Wang, X., Singh, A., Pervysheva, Y., Lamatungga, K.E., Murtinová, V., Mukarram, M., Zhu, Q., Song, K., Surový, P., and Mokroš, M. 2021. “Evaluation of iPad Pro 2020 LiDAR for Estimating Tree Diameters in Urban Forest.” ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. VIII-4/W1-2021 pp. 105–110. doi:10.5194/isprs-annals-VIII-4-W1-2021-105-2021.
  • Wang, F., Heenkenda, M.K., and Freeburn, J.T. 2022. “Estimating tree Diameter at Breast Height (DBH) using an iPad Pro LiDAR sensor.” Remote Sensing Letters, Vol. 13 (No. 6): pp. 568–578. doi:10.1080/2150704X.2022.2051635.
  • White, J.C., Coops, N.C., Wulder, M.A., Vastaranta, M., Hilker, T., and Tompalski, P. 2016. “Remote Sensing Technologies for Enhancing Forest Inventories: A Review.” Canadian Journal of Remote Sensing, Vol. 42 (No. 5): pp. 619–641. doi:10.1080/07038992.2016.1207484.
  • Wickham, H. 2016. ggplot2: Elegant Graphics for Data Analysis (1st ed.). Berlin, Germany: Springer-Verlag. ggplot2.tidyverse.org
  • Woods, M., Pitt, D., Penner, M., Lim, K., Nesbitt, D., Etheridge, D., and Treitz, P. 2011. “Operational implementation of a LiDAR inventory in Boreal Ontario.” The Forestry Chronicle, Vol. 87 (No. 04): pp. 512–528. doi:10.5558/tfc2011-050.
  • Yang, A., Wu, Z., Yang, F., Su, D., Ma, Y., Zhao, D., and Qi, C. 2020. “Filtering of airborne LiDAR bathymetry based on bidirectional cloth simulation.” ISPRS Journal of Photogrammetry and Remote Sensing, Vol. 163 pp. 49–61. doi:10.1016/j.isprsjprs.2020.03.004.
  • Yu, D., He, L., Ye, F., Jiang, L., Zhang, C., Fang, Z., and Liang, Z. 2022. “Unsupervised ground filtering of airborne-based 3D meshes using a robust cloth simulation.” International Journal of Applied Earth Observation and Geoinformation, Vol. 111 pp. 102830. doi:10.1016/j.jag.2022.102830.
  • Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., and Yan, G. 2016. “An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation.” Remote Sensing, Vol. 8 (No. 6): pp. 501. Article 6. doi:10.3390/rs8060501.