Parametric Investigation of the Performance of Lidar Filters Using Different Surface Contexts
Lidar technology has provided an accurate and efficient way to obtain digital elevation models. While digital terrain models (DTMs) are essential products for three-dimensional spatial applications, extraction of ground points from a mixture of ground and non-ground points is not
straightforward, and interactive classification of massive point data sets is prohibitive. To automate the filtering process, many algorithms have been proposed and demonstrated to produce satisfactory results when applied with suitably tuned parameters. For obtaining quality products using
lidar filters, however, not only to figure out their optimal performance, but also to analyze the cause and effect relationships between filtering steps and their effects under variable conditions is important. Hence, this study examined the performance of three popular surface models for
lidar data filtering: morphological operations, triangulation, and linear prediction. For the test, consistent setting of parameters was applied across considerably different landscape datasets. The strengths and weaknesses of the test filters were investigated by comparing the metrics of
omission and commission errors and volumetric distortions, and by observing resulting DTMs and relevant surface profiles.
Document Type: Research Article
Publication date: 01 March 2008
- The official journal of the American Society for Photogrammetry and Remote Sensing - the Imaging and Geospatial Information Society (ASPRS). This highly respected publication covers all facets of photogrammetry and remote sensing methods and technologies.
Founded in 1934, the American Society for Photogrammetry and Remote Sensing (ASPRS) is a scientific association serving over 7,000 professional members around the world. Our mission is to advance knowledge and improve understanding of mapping sciences to promote the responsible applications of photogrammetry, remote sensing, geographic information systems (GIS), and supporting technologies. - Editorial Board
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