Generation of digital terrain model from multispectral LiDar using different ground filtering techniques

Abstract

Multi-spectral LiDAR point clouds provide more information about the terrain surface than mono- wavelength LiDAR, especially in water bodies’ areas. The TITAN LiDAR provided by Teledyne Optech is an example of the multispectral LiDAR system. It has three different wavelengths; mid-infrared (CH-1), near-infrared (CH-2), and green (CH-3) (1.550, 1.064, and 0.532 µm) respectively. This study aims to generate a Digital Terrain Model (DTM) through filtering of Airborne LiDAR point cloud using LiDAR open-source software. Four different ground-filtering algorithms were used; Adaptive TIN (ATIN), Elevation Threshold with Expansion Window (ETEW), Progressive Morphological Algorithms (MORPH), and Maximum Local Slope (SLOPE). These algorithms were executed in Open Source software (Airborne LiDAR Data Processing and Analysis Tools (ALDPAT)). Also, the same data was processed using commercial software (ENVI-LiDAR). The study is focused on the extraction of terrain points from each channel separately and making a visual and quantitative comparison between the performance of the four open-source filtering algorithms and that of the ENVI-LiDAR filter. A quantitative analysis was done by the Cloud to Cloud distance (C2C) to provide the values of standard deviation and RMSE. The results showed that the MORPH and ATIN filtering algorithms gave DTMs similar to that produced by ENVI-LiDAR due to their efficiency in dealing with the forested area. In addition to this MORPH gave better results than ATIN in the removal of non-ground points in coastal barrier islands with a standard deviation of ±93 and ±91 mm for channels −1, 2 respectively. In the third channel, the performance of the SLOPE and the ETEW are well in the water area.

Keywords

• LiDAR
• Multispectral LiDAR
• Multi-wavelength ALS
• Filtering
• DTM
• ALDPAT