Comparative study of building footprint estimation methods from LiDAR point clouds

Rozas, Emilia Vázquez; Rivera, Francisco F.; Dominguez, Jessica A.; Pena, Tomás F.; Vilariño, D.L.

doi:10.1117/12.2280094

Cited by 2 publications

(1 citation statement)

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“…Empirical works include the effect of point density on canopy height [6], biomass estimation [7][8][9], tree structure delineation [10], and the measurement accuracy of forestry in general [11]. The quality of building extraction affected by point density was also discussed by [12,13]. Given the nonuniformity of point density, people intended to find more optimal and reasonable ways to define and calculate the point density [14,15] or to preprocess point clouds to generate uniform point density [16].…”

Section: Introductionmentioning

confidence: 99%

Towards Uniform Point Density: Evaluation of an Adaptive Terrestrial Laser Scanner

Anderson³

et al. 2019

Remote Sensing

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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.

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