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2023 Vol.13, Issue 1 Preview Page

Research Article

31 March 2023. pp. 22-32
Abstract
References
1
Anglin, J. M., Miller, G. A., Wakefield, P. C. (1993). Vocabulary development: A morphological analysis. Monographs of the society for research in child development, pp. i-186. 10.2307/1166112
2
Barbosa, F., Woetzel, J., Mischke, J. (2017). Reinventing construction: A route of higher productivity. McKinsey Global Institute.
3
Bello, S. A., Yu, S., Wang, C., Adam, J. M., Li, J. (2020). Deep learning on 3D point clouds. Remote Sensing, 12(11), 1729, DOI:10.3390/rs12111729. 10.3390/rs12111729
4
Chen, C., Li, Y., Zhao, N., Guo, J., Liu, G. (2017). A fast and robust interpolation filter for airborne lidar point clouds. PloS One, 12(5), e0176954. 10.1371/journal.pone.017695428467478PMC5415094
5
Jaccard, P. (1912). The Distribution of the Flora in the Alpine Zone. New Phytologist, 11(2), pp. 37-50. 10.1111/j.1469-8137.1912.tb05611.x
6
Kim, S., Park, J. W. (2015). Analysis of Accuracy and Productivity of Terrestrial Laser Scanner for Earthwork. The Journal of the Korea Contents Association, 15(10), pp. 587-596. 10.5392/JKCA.2015.15.10.587
7
Kim, S., Park, J. W., Kim, K. H. (2017). A Study on Terrain Digitalization for Earthwork Automation. In Proceedings of the Korea Contents Association Conference pp. 407-408.
8
Kim, Y. G., Park, S. Y., Kim, S. (2022). Development of Registration Post-Processing Technology to Homogenize the Density of Scan Data of Earthwork site. KSCE Journal of Civil and Environmental Engineering Research, 42(5), pp. 689-699.
9
Kim, Y. G., Park, S. Y., Kim, S. (2022). Development of Registration Post-Processing Technology to Homogenize the Density of Scan Data of Earthwork site. KSCE Journal of Civil and Environmental Engineering Research, 42(5). pp. 689-699.
10
Kramer, O. (2016). Scikit-learn. In Machine learning for evolution strategies pp. 45-53. 10.1007/978-3-319-33383-0_5
11
Pan, M., Linner, T., Pan, W., Cheng, H., Bock, T. (2018). A framework of indicators for assessing construction automation and robotics in the sustainability context. Journal of Cleaner Production, 182, pp. 82-95. 10.1016/j.jclepro.2018.02.053
12
Park, J. W., Kim, S. (2019). MMS Accuracy Analysis for Earthwork Site Application. Journal of the Korean Society of Industry Convergence, 22(2), pp. 183-189.
13
Park, S. Y., Kim, S. (2020). Performance Evaluation of Denoising Algorithms for the 3D Construction Digital Map. Journal of KIBIM, 10(4), pp. 32-39.
14
Park, S. Y., Kim, S. (2021). Analysis of overlap ratio for registration accuracy improvement of 3D point cloud data at construction sites. Journal of KIBIM, 11(4), pp. 1-9.
15
Park, S. Y., Kim, Y. G., Choi, Y. J., Lim, Y. J., Kim, S. (2021). A Study on the Process for Automatic Analysis of Digital Maps in the Earthworks Site. Proceedings of The Korean Society for Railway, pp. 124-124.
16
Pingel, T. J., Clarke, K. C., McBride, W. A. (2013). An improved simple morphological filter for the terrain classification of airborne LIDAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 77, pp. 21-30. 10.1016/j.isprsjprs.2012.12.002
17
Qin, R., Tian, J., Reinartz, P. (2016). 3D change detection-approaches and applications. ISPRS Journal of Photogrammetry and Remote Sensing, 122, pp. 41-56. 10.1016/j.isprsjprs.2016.09.013
18
Ruspini, E. H. (1969). A new approach to clustering. Information and control, 15(1), pp. 22-32. 10.1016/S0019-9958(69)90591-9
19
Shen, J., Liu, J., Zhao, R., Lin, X. (2011). A Kd-tree-based outlier detection method for airborne LiDAR point clouds. In 2011 international symposium on image and data fusion, pp. 1-4. 10.1109/ISIDF.2011.6024307
20
Stroner, M., Urban, R., Lidmila, M., Kolář, V. and Křemen, T. (2021). Vegetation filtering of a steep rugged terrain: The performance of standard algorithms and a newly proposed workflow on an example of a railway ledge. Remote Sensing, 13(2), 3050.
21
Tanimoto, T. T. (1958). An elementary mathematical theory of classification and prediction. Internal Report IBM Corp.
22
Wang, Q., Kim, M. K. (2019). Applications of 3D point cloud data in the construction industry: A fifteen-year review from 2004 to 2018. Advanced Engineering Informatics, 39, pp. 306-319, DOI:10.1016/j.aei.2019.02.007. 10.1016/j.aei.2019.02.007
23
Wei, L., Yangz, B., Jiang, J., Cao, G., Wu, M. (2017). Vegetation filtering algorithm for UAV-borne lidar point clouds: a case study in the middle-lower Yangtze River riparian zone. International Journal of Remote Sensing, 38, pp. 2991-3002. 10.1080/01431161.2016.1252476
24
Zhang, K., Chen, S. C., Whitman, D., Shyu, M. L., Yan, J., Zhang, C. (2003). A progressive morphological filter for removing nonground measurements from airborne LIDAR data. IEEE transactions on geoscience and remote sensing, 41(4), pp. 872-882. 10.1109/TGRS.2003.810682
25
Zhang, W., Qi, J., Wan, P., Wang, H., Xie, D., Wang, X., Yan, G. (2016). An easy-to-use airborne LiDAR data filtering method based on cloth simulation. Remote sensing, 8(6), p. 501. 10.3390/rs8060501
Information
  • Publisher :Journal of KIBIM
  • Publisher(Ko) :한국BIM학회
  • Journal Title :Journal of KIBIM
  • Journal Title(Ko) :한국BIM학회논문집
  • Volume : 13
  • No :1
  • Pages :22-32
  • Received Date : 2023-03-03; 2023-03-22
  • Accepted Date : 2023-03-29