Accuracy Assessment of LIDAR-Derived Elevation Value Over Vegetated Terrain in Tropical Region

Authors

  • Zamri Ismail Photogrammetry & Laser Scanning Research Group
  • Muhammad Zulkarnain Abdul Rahman TropicalMAP Research Group, Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Mohd Radhie Mohd Salleh TropicalMAP Research Group, Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia
  • Abdul Razak Mohd Yusof TropicalMAP Research Group, Department of Geoinformation, Faculty of Geoinformation and Real Estate, Universiti Teknologi Malaysia, 81310 UTM Johor Bahru, Johor, Malaysia

DOI:

https://doi.org/10.11113/jt.v73.4335

Keywords:

Airborne LiDAR, accuracy, vegetation, slope

Abstract

Airborne LiDAR has been widely used to generate good quality of Digital Terrain Model (DTM). Normally, good quality of DTM would require high density and quality of airborne LiDAR data acquisition which increase the cost and processing time. This study focuses on investigating the capability of low density airborne LiDAR data captured by the Riegl system mounted on an aircraft. The LiDAR data sampling densities is about 2.2 points per m2. The study area is covered by rubber trees with moderately dense understorey vegetation and mixed forest. The ground filtering procedure employs the adaptive triangulation irregular network (ATIN) technique. A reference DTM is generated using 76 ground reference points collected using total station. Based on this DTM the study area is divided into different classes of terrain slopes. The point clouds belong to non-terrain features are then used to calculate the relative percentage of crown cover. The overall root mean square error (RMSE) of elevation values obtained from airborne LiDAR data is 0.611 m. The slope of the study area is divided into class-1 (0-5 degrees), class-2 (5-10 degrees), class-3 (10-15 degrees) and class-4 (15-20 degrees). The results show that the slope class has high correlation (0.916) with the RMSE of the LiDAR ground points. The percentage of crown cover is divided into class-1 (60-70%), class-2 (70-80%), class-3 (80-90%) and class-4 (90-100%). The correlation between percentage of crown cover and RMSE of the LiDAR ground points is slightly lower than the slope class with the correlation coefficient of 0.663.

References

Bater, C. W., and Coops, N. C. 2009. Evaluating Error Associated with LiDAR-derived DEM Interpolation. Comput. Geosci. 35(2): 289–300.

Ackermann, F. 1999. Airborne Laser Scanning-Present Status and Future Expectations. ISPRS Journal of Photogrammetry and Remote Sensing. 54(4): 64–67.

Flood, M., (2004). ASPRS guidelines. Vertical accuracy reporting for LiDAR data. http://www.asprs.org/society/divisions/ppd/standards/LiDAR%20guidelines.pdf [Accessed: 01 January 2011].

Lim, K., Treitz, P., Wulder, M.A., St-Onge, B., Flood, M. 2003. LiDAR Remote Sensing of Forest Structure. Progress Phys Geogr. 27: 88–106.

Raber, G. T., Jensen, J. R., Schill, S. R. and Schuckman, K. 2002. Creation of Digital Terrain Models Using an Adaptive Lidar Vegetation Point Removal Process. Photogrammetric Engineering& Remote Sensing. 68(12): 1307–1315.

Hodgson, M. E. and Bresnahan, P. 2004. Accuracy of airborne LiDAR Derived Elevation: Empirical Assessment and Error Budget. Photogrammetric Engineering & Remote Sensing. 70(3): 331–33.

Su, J., Bork, E., 2006. Influence of Vegetation, Slope and Lidar Sampling Angle on DEM Accuracy. Photogrammetric Engineering and Remote Sensing. 72(11): 1265–1274.

Gonçalves-Seco, L., Miranda, D., Crecente, R., Farto J., 2006. Digital Terrain Model Generation using Airborne LIDAR in Forested Area of Galicia, Spain. Proceedings of 7th International Symposium on Spatial Accuracy.

Gomes Pereira, L. M. and Wicherson, R. J. 1999. Suitability of Laser Data for Deriving Geographical Information: A Case Study in the Context of Management of Fluvial Zones. ISPRS J. Photogramm. Rem. Sens. 54 (2/3): 105–114.

Hodgson, M. E., Jensen, J. R., Raber, G. T., Tullis, J. A., B. Davis, Schuckman, K. and Thompson, G.2005. An Evaluation of LiDAR-derived Elevation and Terrain Slope in Leaf-Off Conditions. Photogrammetric Engineering & Remote Sensing. 71(12): 817–823.

Cobby, D. M., Mason, D. C., and Davenport, I. J. 2001. Image processing of Airborne Scanning Laser Altimetry Data for Improved River Flood Modelling. ISPRS Journal of Photogrammetry and Remote Sensing. 56: 121–138.

Hodgson, M.E., Jensen, J., Schmidt, L., Schill, S., & Davis, B. 2003. An Evaluation of LiDAR- and IFSAR-derived Digital Elevation Models in Leaf-on Conditions with USGS Level 1 and Level 2 DEMs. Remote Sensing of Environment. 70(3): 295–308.

Spaete, L., Glenn, N., Derryberry, D., Sankey, T., Mitchell, J., and Hardegree, S. 2011. Vegetation and Slope Effects on Accuracy of a LiDAR-derived DEM in the Sagebrush Steppe. Remote Sensing Letters. 2(4): 317–326.

Hodgson, M.E. and Bresnahan, P. 2004. Accuracy of airborne LiDAR Derived Elevation: Empirical Assessment and Error Budget. Photogrammetric Engineering & Remote Sensing. 70(3): 331–33.

Lewis, P. and Hancock, S. 2007. LiDAR for Vegetation Applications. UCL, Gower St, London, United Kingdom.

Axelsson, P., 2000. DEM Generation from Laser Scanner Data Using Adaptive TIN Models. International Archive of Photogrammetry and Remote Sensing. XXXIII(Part B4): 110–17.

Rahman, M. Z. A., B. Gorte, and A. K. Bucksch. 2009. A New Method for Individual Tree Measurement from Airborne LiDAR. In Proc. Of Silvilaser 2009, The 9th International Conference on LiDAR Applications for Assessing Forest Ecosystem, College Station, Texas, USA.

Caruso, C., and F. Quarta, 1998. Interpolation Methods Comparison. Computer and Mathematics with Application. 35(12): 109–126.

Cressie, N., 1988. Spatial Prediction and Ordinary Kriging. Mathematical Geology. 20(4): 405–421.

Gong, J., Z. Li, Q. Zhu, H. Sui, and Y. Zhou, 2000. Effects of Various Factors on the Accuracy of DEMs: An Intensive Experimental Investigation. Photogrammetric Engineering & Remote Sensing. 66(9): 1113-1117.

Aguilar, F. J., F. Agüera, M. A. Aguilar, and C. Fernando, 2005. Effects of Terrain Morphology, Sampling Density, and Interpolation Methods on Grid DEM Accuracy. Photogrammetric Engineering & Remote Sensing. 71(7): 805–816.

Guo, Q. W., Li, H. Yu., and Alvarez, O. 2010. Effects of Topographic Variability and LiDAR Sampling Density on Assessment in Natural Resources and Environmental Sciences.Págs.169-180. Lisbon, Portugal. Several DEM Interpolation Methods. Photogrammetric Engineering and Remote Sensing. 76(6): 701–712.

Su, J., Bork, E. 2006. Influence of Vegetation, Slope and LiDAR Sampling Angle on DEM Accuracy. Photogrammetric Engineering and Remote Sensing. 72 (11): 1265–1274.

Peng, M. H. and T. Y. Shih, 2006. Error Assessment in Two Lidar-derived Datasets. Photogrammetric Engineering & Remote Sensing. 72(8): 933–947.

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Published

2015-03-31

How to Cite

Accuracy Assessment of LIDAR-Derived Elevation Value Over Vegetated Terrain in Tropical Region. (2015). Jurnal Teknologi (Sciences & Engineering), 73(5). https://doi.org/10.11113/jt.v73.4335