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Home / Photogrammetric Engineering & Remote Sensing, Number 2 / February 2013

Open Access New Approaches for Estimating the Local Point Density and its Impact on Lidar Data Segmentation

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Lidar systems have been proven as a cost-effective tool for the collection of high density and accurate point cloud over physical surfaces. The collected point cloud does not exhibit homogenous point distribution due to the characteristics of the scanning system and/or the physical properties of the scanned surfaces. In order to effectively process the lidar point clouds, local point density variations should be quantified and taken into account for the definition of processing parameters. In this paper, new approaches are presented for the estimation of local point density indices while considering the 3D relationship among lidar points, the physical properties of the reflecting surfaces, and the noise level in the datasets collected by different laser scanners. The impact of considering the estimated local point density variations on the quality of lidar data segmentation results is then investigated by performing a quality control procedure. Quantitative evaluation of segmentation results highlights the efficacy of utilizing the estimated local point density indices for the derivation of more accurate segmentation.

Document Type: Research Article

Publication date: 01 February 2013

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  • 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.
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