Laser Scanning Systems in Highway and Safety Assessment by Biswajeet Pradhan & Maher Ibrahim Sameen

Author:Biswajeet Pradhan & Maher Ibrahim Sameen
Language: eng
Format: epub
ISBN: 9783030103743
Publisher: Springer International Publishing

5.5.1 Data Preprocessing

5.5.1.1 Generation of Digital Elevation Model (DEM)

The raw LiDAR data include three-dimensional coordinates of ground points and surface points. Those two sets of data can be used to generate DEM and digital surface model (DSM) in grid form (Briese et al. 2002). In this study, the raw LiDAR point clouds, first, were filtered based on the last pulse return and then a DSM was generated using the nearest neighbor interpolation technique in ArcMap 10.3 software (Fig. 5.3a). Next, the multiscale curvature classification (MCC) algorithm was used in the same software to remove the non-ground points (Fig. 5.3b). MCC is an iterative multiscale algorithm for classifying LiDAR returns as ground and non-ground (Evans and Hudak 2007). The MCC algorithm was developed at the Moscow Forestry Sciences Laboratory of the USFS Rocky Mountain Research Station. In short, the algorithm integrates curvature filtering with a scale component and variable curvature tolerance. During this stage, a surface was interpolated at different resolutions using the thin-plate spline method (Evans and Hudak 2007) and points were classified based on a progressive curvature threshold parameter; the curvature tolerance parameter increases as resolution coarsens to compensate for slope effect as the data are generalized. Figure 5.3b shows the DEM generated using MCC algorithm in ArcMap 10.3 software.

Fig. 5.3Products derived from the raw LiDAR data, a DSM, b DEM

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