Browse > Article
http://dx.doi.org/10.17820/eri.2021.8.4.204

Estimation of Single Vegetation Volume Using 3D Point Cloud-based Alpha Shape and Voxel  

Jang, Eun-kyung (Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology)
Ahn, Myeonghui (Department of Hydro Science and Engineering Research, Korea Institute of Civil Engineering and Building Technology)
Publication Information
Ecology and Resilient Infrastructure / v.8, no.4, 2021 , pp. 204-211 More about this Journal
Abstract
In this study, information on vegetation was collected using a point cloud through a 3-D Terrestrial Lidar Scanner, and the physical shape was analyzed by reconfiguring the object based on the refined data. Each filtering step of the raw data was optimized, and the reference volume and the estimated results using the Alpha Shape and Voxel techniques were compared. As a result of the analysis, when the volume was calculated by applying the Alpha Shape, it was overestimated than reference volume regardless of data filtering. In addition, the Voxel method to be the most similar to the reference volume after the 8th filtering, and as the filtering proceeded, it was underestimated. Therefore, when re-implementing an object using a point cloud, internal voids due to the complex shape of the target object must be considered, and it is necessary to pay attention to the filtering process for optimal data analyzed in the filtering process.
Keywords
3-D Point Cloud; Alpha Shape; Terrestrial Laser Scanning; Vegetation; Voxel;
Citations & Related Records
연도 인용수 순위
  • Reference
1 Lee, C. D. G. S.-Y. Y. S. S. H. 2019. Dataset of Long-term Investigation on Change in Hydrology, Channel Morphology, Landscape and Vegetation Along the Naeseong Stream (II). Ecology and Resilient Infrastructure 6(1): 34-48.
2 Boothroyd, R. and James. (2017). Flow-vegetation interactions at the plant-scale: the importance of volumetric canopy morphology on flow field dynamics [Durham University]. Retrieved from https://pdfs.semanticscholar.org/82b7/1f0302e83632ee076f40169f14b5cd272318.pdf?_ga=2.200340270.1671434650.1566237458-639639868.1565275494
3 Jalonen, J., Jarvela, J., Virtanen, J.P., Vaaja, M., Kurkela, M. and Hyyppa, H. 2015. Determining characteristic vegetation areas by terrestrial laser scanning for floodplain flow modeling. Water (Switzerland) 7(2): 420-437. doi: 10.3390/w7020420   DOI
4 Li, Y., Hess, C., Von Wehrden, H., Hardtle, W. and Von Oheimb, G. 2014. Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning. Annals of Forest Science 71(4): 453-462. doi: 10.1007/s13595-014-0358-4   DOI
5 Maas, H.G., Bienert, A., Scheller, S. and Keane, E. 2008. Automatic forest inventory parameter determination from terrestrial laser scanner data. International Journal of Remote Sensing 29(5): 1579-1593. doi: 10.1080/01431160701736406   DOI
6 Wikipedia. 2006. Voxel. Retrieved from https://wikipedia.org/wiki/voxel
7 Woo, H., Cho, K.-H., Jang, C.L. and Lee, C.J. 2019. Fluvial processes and vegetation-research trends and implications. Ecology and Resilient Infrastructure 6(2): 89-100.
8 Yan, Z., Liu, R., Cheng, L., Zhou, X., Ruan, X. and Xiao, Y. 2019. A Concave Hull Methodology for Calculating the Crown Volume of Individual Trees Based on Vehicle-Borne LiDAR Data. Remote Sensing 11(6): 623. doi: 10.3390/rs11060623   DOI
9 Woo, H. and Park, M. 2016. Cause-based Categorization of the Riparian Vegetative Recruitment and Corresponding Research Direction. Ecology and Resilient Infrastructure 3(3): 207-211. doi: 10.17820/eri.2016.3.3.207   DOI
10 Jang, E., Ahn, M. and Ji, U. 2020. Introduction and Application of 3D Terrestrial Laser Scanning for Estimating Physical Structurers of Vegetation in the Channel. Ecology and Res ilient Infras tructure 7(2): 90-96. doi: 10.17820/eri.2020.7.2.090   DOI
11 Grau, E., Durrieu, S., Fournier, R., Gastellu-Etchegorry, J. P. and Yin, T. 2017. Estimation of 3D vegetation density with Terrestrial Laser Scanning data using voxels. A sensitivity analysis of influencing parameters. Remote Sensing of Environment 191: 373-388. doi: 10.1016/j.rse.2017.01.032   DOI
12 Jin, S.-N. and Cho, K.-H. 2016. Expansion of Riparian Vegetation Due to Change of Flood Regime in the Cheongmi-cheon Stream, Korea. Ecology and Resilient Infrastructure 3(4): 322-326. doi: 10.17820/eri.2016.3.4.322   DOI
13 Kankare, V., Holopainen, M., Vastaranta, M., Puttonen, E., Yu, X., Hyyppa, J., Vaaja, M., Hyyppa, H. and Alho, P. 2013. Individual tree biomass estimation using terrestrial laser scanning. ISPRS Journal of Photogrammetry and Remote Sensing 75: 64-75. doi: 10.1016/j.isprsjprs.2012.10.003   DOI
14 Rutzinger, M., Pratihast, A.K., Oude Elberink, S. and Vosselman, G. 2010. Detection and modelling of 3D trees from mobile laser scanning data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 38(PART 5).
15 Ahn, M., Jang, E.-K., Bae, I. and Ji, U. 2020. Reconfiguration of Physical Structure of Vegetation by Voxelization Based on 3D Point Clouds. KSCE Journal of Civil and Environmental Engineering Research 40(6): 571-581. doi: 10.12652/Ksce.2020.40.6.0571   DOI
16 Bienert, A., Hess, C., Maas, H.G. and Von Oheimb, G. 2014. A Voxel-based technique to estimate the volume of trees from terrestrial laser scanner data. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives 40(5): 101-106. doi: 10.5194/isprsarchives-XL-5-101-2014   DOI
17 Bienert, A., Queck, R., Schmidt, A., Bernhofer, C. and Maas, H.-G. 2010. Voxel space analysis of terrestrial laser scans in forests for wind field modeling. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives, 38(PART 5).
18 Dassot, M., Colin, A., Santenoise, P., Fournier, M. and Constant, T. 2012. Terrestrial laser scanning for measuring the solid wood volume, including branches, of adult standing trees in the forest environment. Computers and Electronics in Agriculture 89: 86-93. doi: 10.1016/j.compag.2012.08.005   DOI
19 Jalonen, J., Jarvela, J., Koivusalo, H. and Hyyppa, H. 2014. Deriving Floodplain Topography and Vegetation Characteristics for Hydraulic Engineering Applications by Means of Terrestrial Laser Scanning. Journal of Hydraulic Engineering 140(11): 04014056. doi: 10.1061/(asce)hy.1943-7900.0000928   DOI
20 Hosoi, F., Nakai, Y. and Omasa, K. 2013. Voxel tree modeling for estimating leaf area density and woody material volume using 3-D LIDAR data. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2(5W2), 115-120. doi: 10.5194/isprsannals-II-5-W2-115-2013   DOI