Data Verification of LiDAR-Derived DEM from Different Interpolation Techniques

Abstract

Sustainable development makes light detection and ranging (LiDAR) as an accurate technology in providing the accurate data sources for deriving digital terrain model (DTM) and digital elevation model (DEM). This study is focusing on accuracy assessment of generated LiDAR DEM based on different interpolation techniques in GIS environment. In the beginning, LiDAR point clouds were used to generate DEM surface based upon three different interpolation methods: (i) inverse distance weighting (IDW), (ii) Kriging and (iii) Spline. Next, 31 ground control points (GCP) from global positioning system (GPS) observation were used to perform accuracy assessment of LiDAR DEM that generate through IDW, Kriging and Spline interpolation techniques. As result, LiDAR data used in this study met the requirement of LiDAR accuracy with root mean square error (RMSE) below 0.3m. The finding reveals that the overall RMSE (x, y) for IDW, Kriging and Spline methods is between 0.0124 and 0.1120 m. Besides, the RMSE (z) for Kriging stated the smallest value of 0.2135 m, followed by Spline with values of 0.2141 m. Concurrently, IDW techniques gave the highest RMSE (z) value with 0.2276 m. In conclusion, Kriging interpolation technique has been proved as the best methods which gave the highest accuracy of LiDAR-derived DEM compared to other interpolation methods.