All Issue

2021 Vol.8, Issue 4 Preview Page

Original Article

31 December 2021. pp. 204-211
Abstract
References
1
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
2
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 10.5194/isprsarchives-XL-5-101-2014
3
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).
4
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
5
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 10.1016/j.compag.2012.08.005
6
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 10.1016/j.rse.2017.01.032
7
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 10.5194/isprsannals-II-5-W2-115-2013
8
Jalonen, J., Järvelä, J., Koivusalo, H. and Hyyppä, 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 10.1061/(ASCE)HY.1943-7900.0000928
9
Jalonen, J., Järvelä, J., Virtanen, J.P., Vaaja, M., Kurkela, M. and Hyyppä, H. 2015. Determining characteristic vegetation areas by terrestrial laser scanning for floodplain flow modeling. Water (Switzerland) 7(2): 420-437. doi: 10.3390/w7020420 10.3390/w7020420
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 Resilient Infrastructure 7(2): 90-96. doi: 10.17820/eri.2020.7.2.090
11
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 10.17820/eri.2016.3.4.322
12
Kankare, V., Holopainen, M., Vastaranta, M., Puttonen, E., Yu, X., Hyyppä, J., Vaaja, M., Hyyppä, 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 10.1016/j.isprsjprs.2012.10.003
13
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.
14
Li, Y., Hess, C., Von Wehrden, H., Härdtle, 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 10.1007/s13595-014-0358-4
15
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: 10.1080/01431 160701736406 10.1080/01431160701736406
16
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).
17
Wikipedia. 2006. Voxel. Retrieved from https://wikipedia. org/wiki/voxel
18
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.
19
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 10.17820/eri.2016.3.3.207
20
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 10.3390/rs11060623
Information
  • Publisher :Korean Society of Ecology and Infrastructure Engineering
  • Publisher(Ko) :응용생태공학회
  • Journal Title :Ecology and Resilient Infrastructure
  • Journal Title(Ko) :응용생태공학회 논문집
  • Volume : 8
  • No :4
  • Pages :204-211
  • Received Date : 2021-11-15
  • Revised Date : 2021-11-23
  • Accepted Date : 2021-12-01