Evaluating the quality of ground surfaces generated from Terrestrial Laser Scanning (TLS) data

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2019-06-24

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Virginia Tech

Abstract

Researchers and GIS analysts have used Aerial Laser Scanning (ALS) data to generate Digital Terrain Models (DTM) since the 1990s, and various algorithms developed for ground point extraction have been proposed based on the characteristics of ALS data. However, Terrestrial Laser Scanning (TLS) data, which might be a better indicator of ground morphological features under dense tree canopies and more accessible for small areas, have been long ignored. In this research, the aim was to evaluate if TLS data were as qualified as ALS to serve as a source of a DTM. To achieve this goal, there were three steps: acquiring and aligning ALS and TLS of the same region, applying ground filters on both of the data sets, and comparing the results.

Our research area was a 100m by 140m region of grass, weeds and small trees along Strouble's Creek on the Virginia Tech campus. Four popular ground filter tools (ArcGIS, LASTools, PDAL, MCC) were applied to both ALS and TLS data. The output ground point clouds were then compared with a DTM generated from ALS data of the same region. Among the four ground filter tools employed in this research, the distances from TLS ground points to the ALS ground surface were no more than 0.06m with standard deviations less than 0.3m. The results indicated that the differences between the ground extracted from TLS and that extracted from ALS were subtle. The conclusion is that Digital Terrain Models (DTM) generated from TLS data are valid.

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Keywords

point cloud, ground filter, classification

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