Abstract
One of the intrinsic properties of conventional terrestrial laser scanning technology is the unevenness of its point density over the scene where objects rendered closer to the scanner are more densely covered than the ones far away. This uneven distribution can be amplified as the working range of a laser scanner gets longer. In such case a higher pulse repetition rate (PRR) is applied to the whole scanning area and the scanning time will be dramatically increased. To improve the efficiency of the conventional laser scanning technology, a prototype of adaptive scanning technology, the HRS3D-AS scanner has been developed by Blackmore Sensors and Analytics, Inc. This paper briefly describes the working principles of the adaptive scanner and presents a thorough evaluation on the distributions of the point density in comparison to the conventional scanning. Based on this study, we show that such a new technology can produce a point cloud of more uniform density and less data volume. The overall field scanning time can be reduced by several times compared to the conventional, PRR-fixed scanning. Such properties are expected to significantly simplify the algorithmic development and increase the productivity in data acquisition and processing. The limitations of this new adaptive scanning technology are also discussed in terms of redundant and unresolved details. Finally, recommendations related to the practicing of such adaptive scan are discussed.
Highlights
Point density, commonly described by the number of lidar measured points per unit area on a given target [1], is one of the most important metrics that characterizes the quality of point clouds produced by topographic laser scanners [1,2,3]
Nonuniformity of point density is a common problem in terrestrial laser scanning (TLS) since the targets far away from the scanner are more sparely measured than closer objects
This paper introduces a new paradigm of terrestrial laser scanning and evaluates its performance
Summary
Commonly described by the number of lidar (light detection and ranging) measured points per unit area on a given target [1], is one of the most important metrics that characterizes the quality of point clouds produced by topographic laser scanners [1,2,3]. Nonuniformity of point density is a common problem in terrestrial laser scanning (TLS) since the targets far away from the scanner are more sparely measured than closer objects. Due to the unavoidable existence of nonuniformity in point density, many studies have been undertaken reporting on the effect of point density relating to lidar data processing and information extraction. Most terrestrial commercial laser scanners apply a “full dome” scanning approach This means the instrument scans the scene at a fixed angular resolution (i.e., angular sampling density) and PRR regardless of the target’s range. Some suggested to rotate the scanner with high frequency to acquire dense point clouds [24] This usually results in an over-sampled, large number of pulses being generated to the detriment of the scene. Our testing and evaluation focused on the spatial distribution of point density with the objective to understand the properties of this new scanning technology in terms of its expected design specifications and resulting data quality
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