Effects of point cloud density, interpolation method and grid size on derived Digital Terrain Model accuracy at micro topography level

摘要

The objective of this study was to evaluate the effects of the three dimensional (3D) point cloud density derived from Unmanned Aerial Vehicle (UAV) photogrammetry (using Structure from Motion (SfM) and Multi-View Stereopsis (MVS) techniques), the interpolation method for generating a digital terrain model (DTM), and the resolution (grid size (GS)) of the derived DTM on the accuracy of estimated heights in small areas, where a very accurate high spatial resolution is required. A UAV-photogrammetry project was carried out on 13 m x 13 m bare soil with a rotatory wing UAV at 10 m flight altitude (equivalent ground sample distance = 0.4 cm), and the 3D point cloud was derived. A stratified random sample (200 points in each square metre) was extracted and from the rest of the cloud, 15 stratified random samples representing 1, 2, 3, 4, 5, 10, 15, 20, 30, 40, 50, 60, 70, 80, and 90% were extracted. Five replications of each percentage were extracted to analyse the effect of cloud density on DTM accuracy. For each of these 15 x 5 = 75 samples, DTMs were derived using four different interpolation methods (Inverse Distance Weighted (IDW), Multiquadric Radial Basis Function (MRBF), Kriging (KR), and Triangulation with Linear Interpolation (TLI)) and 15 DTM GS values (20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0.67, 0.50, and 0.40 cm). Then, 75 x 4 x 15 = 4500 DTMs were analysed. The results showed an optimal GS value for each interpolation method and each density (most of the cases were equal to 1 cm) for which the Root Mean Square Error (RMSE) was the minimum. IDW was the interpolator that yielded the best accuracies for all combinations of densities and GS. Its RMSE when considering the raw cloud was 1.054 cm and increased by 3% when a point cloud with 80% extracted from the raw cloud was used to generate the DTM. When the point cloud included 40% of the raw cloud, RMSE increased by 5%. For densities lower than 15%, RMSE increased exponentially (45% for 1% of raw cloud). The GS minimizing RMSE for densities of 20% or higher was 1 cm, which represents 2.5 times the ground sample distance of the pictures used for developing the photogrammetry project.