Combination of morphological and distributional filtering for UAV - LiDAR point cloud density to establish the Digital Terrain Model
- Authors: Anh Trung Tran 1*, Hanh Hong Tran 1, Tuan Manh Quach 2
1 Hanoi University of Mining and Geology, Ha Noi, Vietnam
2 Northern QT Trading and Construction Joint Stock Company, Ha Noi, Vietnam
- Keywords: DTM, Filtering, Land cover, Point Cloud, UAV-LiDAR.
- Received: 24th-Apr-2022
- Revised: 11st-Aug-2022
- Accepted: 5th-Sept-2022
- Online: 31st-Oct-2022
- Section: Geomatics and Land Administration
Filtering the LiDAR point cloud based the Unmaned Aerial Vehilce (UAV - LiDAR) in the dense land cover areas to build a Digital Terrain Model (DTM) is a basic requirement of large-scale topographic mapping. The aim of this paper is to study the use of the Simple Morphological Filter (SMRF) with suitable parameters to separate the non-terrain points (trees, noise points, etc.) and the topographical points. The methods of this article are algorithmic programming and combining the two filtering algorithms including SMRF and distributed filtering. The various data input was studied in the Ba Be case study. These parameters include the grid width called Gcell (m), the radius of filters called nwd and the threshold of the feature elevation called Eth (m). The point cloud of the terrain obtained after applying the SMRF continues to be filtered using distributional filter with the algorithm keeping only minimum elevation in the filtering window in order to remove the locations of high density of points. Then, it will contribute to lighten the point capacity to build DTM, to accurately interpolate the contour lines and to ensure the aesthetics of large-scale topographic maps. The results of the study are the fomulas to estimate reasonable input parameters (Gcell = 3 m, nwd = 3, Eth = 0.2 m) of the two filters for the establishment of a topographic map of 1:2000 scale, 1 m level in the Ba Be national forest, Bac Kan province, Vietnam.
Axelsson, P., (2000). DEM generation from laser scanner data using adaptive TIN models. International archives of photogrammetry, Remote Sensing and Spatial Information Sciences 33 (Part B4), 110-117.
Baudelet, M., (Ed.). (2014). Laser spectroscopy for sensing: Fundamentals, techniques and applications. Elsevier. Pages 292-312. https://doi. org/10.1533/9780857098733. 2.292.
Ministry of Natural Resources and Environment (2015). Circular No. 68/2015/TT-BTNMT of the Ministry of Natural Resources and Environment: Technical regulations of the field topographic survey for topographic map establishment and geographic base database at scale 1:500, 1:1000, 1:2000, 1:5000. Ministry of Natural Resources and Environment. (in Vietnamese).
Chen, C., Guo, J., Wu, H., Li, Y., Shi, B., (2021). Performance Comparison of Filtering Algorithms for High-Density Airborne LiDAR Point Clouds over Complex LandScapes. Remote Sens. 2021, 13, 2663. https://doi.org/ 10.3390/rs13142663.
Jahromi, A. B., Zoej, M. J. V., Mohammadzadeh, A., Sadeghian, S., (2011). A novel filtering algorithm for bare-earth extraction from airborne laser scanning data using an artificial neural network. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 4 (4), 836-843. DOI: 10.1109/ JSTARS. 2011.2132793.
Kraus, K., Pfeifer, N., (1998). Determination of terrain models in wooded areas with airborne laser scanner data. ISPRS Journal of Photogrammetry and Remote Sensing 53 (4), 193-203. https://doi.org/10.1016/S0924-2716(98)00009-4.
Le, M., Luong, C.K., (2008). Basis of DEM accuracy assessment established by LiDAR technology. Remote Sensing and Geoinformatics. National Center for Remote Sensing - Ministry of Natural Resources and Environment. (No. 4 - 5/2008). (in Vietnamese).
Lin, Y., Hyyppä, J., Jaakkola, A., (2010). Mini-UAV-borne LIDAR for fine-scale mapping. IEEE Geoscience and Remote Sensing Letters, 8(3), 426-430. DOI: 10.1109/LGRS.2010.2079913.
Mathworks, (2022). SegmentGroundSMRF, Segment ground from LiDAR data using a SMRF algorithm. Mathworks.com. Available at: https://www.mathworks.com/help/LiDAR/ref/segmentgroundsmrf.html. (accessed at 21-April-2022).
Meng, X., Currit, N., Zhao, K., (2010). Ground filtering algorithms for airborne LiDAR data: A review of critical issues. Remote Sensing, 2(3), 833-860.
Nguyen, N., (2011). Ba Be National Park - Bac Kan Province. Electronic portal of Bac Kan province. https://backan.gov.vn/pages/vuon-quoc-gia-ba-be-tinh-bac-kan.aspx. (in Vietnamese).
Nguyen, T.H.P., Dang, V.D., Nguyen, T.X., (2017). LiDAR data exploitation in the object research on the topographic surface. Proceedings of the 10th National Conference on Fundamental and Applied IT Research (FAIR), Da Nang, August 17-18, 2017. DOI: 10.15625/vap.2017,00039. (in Vietnamese).
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, 21-30.
Stenning, D., Kashyap, V., Lee T. C. M., Van Dyk, D. A., and Young, C. A., (2013). Morphological Image Analysis and Its Application to Sunspot Classification. Available at: https://www. researchgate.net/publication/265259717_Morphological_Image_Analysis_and_Its_Application_to_Sunspot_Classification (accessed at 21-April-2022) DOI: 10.1007/978-1-4614-3520-4-31.
Tran, D.L., Nguyen, T.K.D., Luu, T.T.T., Tran, H.H., (2015). The applicability of LiDAR technology to build a Digital Terrain Model of the coastal alluvial plain in Vietnam's conditions. Journal of Natural Resources and Environment, 1, pp. 24-28. (in Vietnamese).